docs: update REPL namespace documentation

PR-URL: #3917

Co-authored-by: Philipp Burckhardt <pburckhardt@outlook.com>
Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>
Signed-off-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>

Author: stdlib-bot

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

@@ -4124,6 +4124,7 @@ ndat,"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nndat( x, 0, 1 )\nndat( x, 1, 0 )
 ndempty,"var arr = ndempty( [ 2, 2 ] )\nvar sh = arr.shape\nvar dt = arr.dtype\n"
 ndemptyLike,"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = ndemptyLike( x )\nsh = y.shape\ndt = y.dtype\n"
 ndfilter,"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v > 2.0; };\nvar y = ndfilter( x, f );\nndarray2array( y )\n"
+ndfilterMap,"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\nvar y = ndfilterMap( x, f );\nndarray2array( y )\n"
 ndims,"var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n"
 nditerColumnEntries,"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumnEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n"
 nditerColumns,"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumns( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n"

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

@@ -1970,8 +1970,8 @@ base.strided.dstdevyc,"\nbase.strided.dstdevyc( N:integer, correction:number, x:
 base.strided.dstdevyc.ndarray,"\nbase.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n"
 base.strided.dsum,"\nbase.strided.dsum( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of double-precision floating-point strided array elements.\n"
 base.strided.dsum.ndarray,"\nbase.strided.dsum.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using alternative indexing semantics.\n"
-base.strided.dsumkbn,"\nbase.strided.dsumkbn( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n"
-base.strided.dsumkbn.ndarray,"\nbase.strided.dsumkbn.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n"
+base.strided.dsumkbn,"\nbase.strided.dsumkbn( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n"
+base.strided.dsumkbn.ndarray,"\nbase.strided.dsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n"
 base.strided.dsumkbn2,"\nbase.strided.dsumkbn2( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n"
 base.strided.dsumkbn2.ndarray,"\nbase.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n"
 base.strided.dsumors,"\nbase.strided.dsumors( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation.\n"
@@ -4125,6 +4125,7 @@ ndat,"\nndat( x:ndarray[, ...indices:integer] )\n    Returns an ndarray element.
 ndempty,"\nndempty( shape:ArrayLikeObject<integer>|integer[, options:Object] )\n    Returns an uninitialized ndarray having a specified shape and data type.\n"
 ndemptyLike,"\nndemptyLike( x:ndarray[, options:Object] )\n    Returns an uninitialized ndarray having the same shape and data type as a\n    provided input ndarray.\n"
 ndfilter,"\nndfilter( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n    Returns a shallow copy of an ndarray containing only those elements which\n    pass a test implemented by a predicate function.\n"
+ndfilterMap,"\nndfilterMap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n    Filters and maps elements in an input ndarray to elements in a new output\n    ndarray according to a callback function.\n"
 ndims,"\nndims( x:ndarray )\n    Returns the number of ndarray dimensions.\n"
 nditerColumnEntries,"\nnditerColumnEntries( x:ndarray[, options:Object] )\n    Returns an iterator which returns [index, column] pairs for each column in a\n    matrix (or stack of matrices).\n"
 nditerColumns,"\nnditerColumns( x:ndarray[, options:Object] )\n    Returns an iterator which iterates over each column in a matrix (or stack of\n    matrices).\n"

lib/node_modules/@stdlib/repl/help/data/data.csv

@@ -1971,8 +1971,8 @@ base.strided.dstdevyc,"base.strided.dstdevyc( N, correction, x, stride )"
 base.strided.dstdevyc.ndarray,"base.strided.dstdevyc.ndarray( N, correction, x, stride, offset )"
 base.strided.dsum,"base.strided.dsum( N, x, stride )"
 base.strided.dsum.ndarray,"base.strided.dsum.ndarray( N, x, stride, offset )"
-base.strided.dsumkbn,"base.strided.dsumkbn( N, x, stride )"
-base.strided.dsumkbn.ndarray,"base.strided.dsumkbn.ndarray( N, x, stride, offset )"
+base.strided.dsumkbn,"base.strided.dsumkbn( N, x, strideX )"
+base.strided.dsumkbn.ndarray,"base.strided.dsumkbn.ndarray( N, x, strideX, offsetX )"
 base.strided.dsumkbn2,"base.strided.dsumkbn2( N, x, stride )"
 base.strided.dsumkbn2.ndarray,"base.strided.dsumkbn2.ndarray( N, x, stride, offset )"
 base.strided.dsumors,"base.strided.dsumors( N, x, stride )"
@@ -4177,6 +4177,7 @@ ndat,"ndat( x[, ...indices] )"
 ndempty,"ndempty( shape[, options] )"
 ndemptyLike,"ndemptyLike( x[, options] )"
 ndfilter,"ndfilter( x[, options], predicate[, thisArg] )"
+ndfilterMap,"ndfilterMap( x[, options], fcn[, thisArg] )"
 ndims,"ndims( x )"
 nditerColumnEntries,"nditerColumnEntries( x[, options] )"
 nditerColumns,"nditerColumns( x[, options] )"

lib/node_modules/@stdlib/repl/help/data/data.json

@@ -1971,8 +1971,8 @@ base.strided.dstdevyc,"base.strided.dstdevyc( N:integer, correction:number, x:Fl
 base.strided.dstdevyc.ndarray,"base.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )"
 base.strided.dsum,"base.strided.dsum( N:integer, x:Float64Array, stride:integer )"
 base.strided.dsum.ndarray,"base.strided.dsum.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )"
-base.strided.dsumkbn,"base.strided.dsumkbn( N:integer, x:Float64Array, stride:integer )"
-base.strided.dsumkbn.ndarray,"base.strided.dsumkbn.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )"
+base.strided.dsumkbn,"base.strided.dsumkbn( N:integer, x:Float64Array, strideX:integer )"
+base.strided.dsumkbn.ndarray,"base.strided.dsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"
 base.strided.dsumkbn2,"base.strided.dsumkbn2( N:integer, x:Float64Array, stride:integer )"
 base.strided.dsumkbn2.ndarray,"base.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )"
 base.strided.dsumors,"base.strided.dsumors( N:integer, x:Float64Array, stride:integer )"
@@ -4177,6 +4177,7 @@ ndat,"ndat( x:ndarray[, ...indices:integer] )"
 ndempty,"ndempty( shape:ArrayLikeObject<integer>|integer[, options:Object] )"
 ndemptyLike,"ndemptyLike( x:ndarray[, options:Object] )"
 ndfilter,"ndfilter( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )"
+ndfilterMap,"ndfilterMap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )"
 ndims,"ndims( x:ndarray )"
 nditerColumnEntries,"nditerColumnEntries( x:ndarray[, options:Object] )"
 nditerColumns,"nditerColumns( x:ndarray[, options:Object] )"