Merge branch 'develop' of https://github.com/stdlib-js/stdlib into develop

Author: kgryte

lib/node_modules/@stdlib/ndarray/README.md

@@ -83,7 +83,7 @@ In addition, the namespace contains the following multidimensional array utility
 -   <span class="signature">[`emptyLike( x[, options] )`][@stdlib/ndarray/empty-like]</span><span class="delimiter">: </span><span class="description">create an uninitialized ndarray having the same shape and data type as a provided ndarray.</span>
 -   <span class="signature">[`empty( shape[, options] )`][@stdlib/ndarray/empty]</span><span class="delimiter">: </span><span class="description">create an uninitialized ndarray having a specified shape and data type.</span>
 -   <span class="signature">[`FancyArray( dtype, buffer, shape, strides, offset, order[, options] )`][@stdlib/ndarray/fancy]</span><span class="delimiter">: </span><span class="description">fancy multidimensional array constructor.</span>
--   <span class="signature">[`fillBy( x, fcn[, thisArg] )`][@stdlib/ndarray/fill-by]</span><span class="delimiter">: </span><span class="description">fill an input `ndarray` according to a callback function.</span>
+-   <span class="signature">[`fillBy( x, fcn[, thisArg] )`][@stdlib/ndarray/fill-by]</span><span class="delimiter">: </span><span class="description">fill an input ndarray according to a callback function.</span>
 -   <span class="signature">[`fill( x, value )`][@stdlib/ndarray/fill]</span><span class="delimiter">: </span><span class="description">fill an input `ndarray` with a specified value.</span>
 -   <span class="signature">[`filterMap( x[, options], fcn[, thisArg] )`][@stdlib/ndarray/filter-map]</span><span class="delimiter">: </span><span class="description">filter and map elements in an input ndarray to elements in a new output ndarray according to a callback function.</span>
 -   <span class="signature">[`filter( x[, options], predicate[, thisArg] )`][@stdlib/ndarray/filter]</span><span class="delimiter">: </span><span class="description">return a shallow copy of an ndarray containing only those elements which pass a test implemented by a predicate function.</span>

lib/node_modules/@stdlib/repl/code-blocks/data/data.csv

@@ -1853,8 +1853,8 @@ base.strided.dnannsumpw,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nv
 base.strided.dnannsumpw.ndarray,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n"
 base.strided.dnanrange,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanrange( 3, x1, 2 )\n"
 base.strided.dnanrange.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanrange.ndarray( 3, x, 2, 1 )\n"
-base.strided.dnanstdev,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdev( N, 1, x1, stride )\n"
-base.strided.dnanstdev.ndarray,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n"
+base.strided.dnanstdev,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dnanstdev( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdev( 3, 1, x1, 2 )\n"
+base.strided.dnanstdev.ndarray,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dnanstdev.ndarray( 3, 1, x, 2, 1 )\n"
 base.strided.dnanstdevch,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevch( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevch( 4, 1, x1, 2 )\n"
 base.strided.dnanstdevch.ndarray,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevch.ndarray( 4, 1, x, 2, 1 )\n"
 base.strided.dnanstdevpn,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevpn( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevpn( 4, 1, x1, 2 )\n"
@@ -2156,8 +2156,8 @@ base.strided.nanmeanpn,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn
 base.strided.nanmeanpn.ndarray,"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n"
 base.strided.nanmeanwd,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanwd( N, x1, stride )\n"
 base.strided.nanmeanwd.ndarray,"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n"
-base.strided.nanmin,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmin( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmin( N, x1, stride )\n"
-base.strided.nanmin.ndarray,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmin.ndarray( N, x, 2, 1 )\n"
+base.strided.nanmin,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanmin( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmin( 4, x1, 2 )\n"
+base.strided.nanmin.ndarray,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmin.ndarray( 4, x, 2, 1 )\n"
 base.strided.nanminabs,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanminabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanminabs( N, x1, stride )\n"
 base.strided.nanminabs.ndarray,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminabs.ndarray( N, x, 2, 1 )\n"
 base.strided.nanminBy,"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanminBy( N, x1, 2, accessor )\n"