docs: update namespace table of contents

PR-URL: #3918

Co-authored-by: Philipp Burckhardt <[email protected]>
Reviewed-by: Philipp Burckhardt <[email protected]>
Signed-off-by: stdlib-bot <[email protected]>

Author: stdlib-bot

lib/node_modules/@stdlib/blas/ext/base/README.md

@@ -85,7 +85,7 @@ var ns = extblas;
 -   <span class="signature">[`dssumors( N, x, strideX )`][@stdlib/blas/ext/base/dssumors]</span><span class="delimiter">: </span><span class="description">calculate the sum of single-precision floating-point strided array elements using ordinary recursive summation with extended accumulation and returning an extended precision result.</span>
 -   <span class="signature">[`dssumpw( N, x, strideX )`][@stdlib/blas/ext/base/dssumpw]</span><span class="delimiter">: </span><span class="description">calculate the sum of single-precision floating-point strided array elements using pairwise summation with extended accumulation and returning an extended precision result.</span>
 -   <span class="signature">[`dsum( N, x, stride )`][@stdlib/blas/ext/base/dsum]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements.</span>
--   <span class="signature">[`dsumkbn( N, x, stride )`][@stdlib/blas/ext/base/dsumkbn]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using an improved Kahan–Babuška algorithm.</span>
+-   <span class="signature">[`dsumkbn( N, x, strideX )`][@stdlib/blas/ext/base/dsumkbn]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using an improved Kahan–Babuška algorithm.</span>
 -   <span class="signature">[`dsumkbn2( N, x, stride )`][@stdlib/blas/ext/base/dsumkbn2]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm.</span>
 -   <span class="signature">[`dsumors( N, x, stride )`][@stdlib/blas/ext/base/dsumors]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using ordinary recursive summation.</span>
 -   <span class="signature">[`dsumpw( N, x, stride )`][@stdlib/blas/ext/base/dsumpw]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using pairwise summation.</span>

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

@@ -83,11 +83,14 @@ 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">[`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>
 -   <span class="signature">[`flag( x, name )`][@stdlib/ndarray/flag]</span><span class="delimiter">: </span><span class="description">return a specified flag for a provided ndarray.</span>
 -   <span class="signature">[`flags( x )`][@stdlib/ndarray/flags]</span><span class="delimiter">: </span><span class="description">return the flags of a provided ndarray.</span>
 -   <span class="signature">[`scalar2ndarray( value[, options] )`][@stdlib/ndarray/from-scalar]</span><span class="delimiter">: </span><span class="description">convert a scalar value to a zero-dimensional ndarray.</span>
 -   <span class="signature">[`ind2sub( shape, idx[, options] )`][@stdlib/ndarray/ind2sub]</span><span class="delimiter">: </span><span class="description">convert a linear index to an array of subscripts.</span>
 -   <span class="signature">[`indexModes()`][@stdlib/ndarray/index-modes]</span><span class="delimiter">: </span><span class="description">list of ndarray index modes.</span>
+-   <span class="signature">[`map( x[, options], fcn[, thisArg] )`][@stdlib/ndarray/map]</span><span class="delimiter">: </span><span class="description">apply a callback function to elements in an input ndarray and assign results to elements in a new output ndarray.</span>
 -   <span class="signature">[`maybeBroadcastArray( x, shape )`][@stdlib/ndarray/maybe-broadcast-array]</span><span class="delimiter">: </span><span class="description">broadcast an ndarray to a specified shape if and only if the specified shape differs from the provided ndarray's shape.</span>
 -   <span class="signature">[`maybeBroadcastArrays( arrays )`][@stdlib/ndarray/maybe-broadcast-arrays]</span><span class="delimiter">: </span><span class="description">broadcast ndarrays to a common shape.</span>
 -   <span class="signature">[`minDataType( value )`][@stdlib/ndarray/min-dtype]</span><span class="delimiter">: </span><span class="description">determine the minimum ndarray data type of the closest "kind" necessary for storing a provided scalar value.</span>
@@ -102,6 +105,7 @@ In addition, the namespace contains the following multidimensional array utility
 -   <span class="signature">[`orders()`][@stdlib/ndarray/orders]</span><span class="delimiter">: </span><span class="description">list of ndarray orders.</span>
 -   <span class="signature">[`outputDataTypePolicies()`][@stdlib/ndarray/output-dtype-policies]</span><span class="delimiter">: </span><span class="description">list of output ndarray data type policies.</span>
 -   <span class="signature">[`promotionRules( [dtype1, dtype2] )`][@stdlib/ndarray/promotion-rules]</span><span class="delimiter">: </span><span class="description">return the ndarray data type with the smallest size and closest "kind" to which ndarray data types can be **safely** cast.</span>
+-   <span class="signature">[`reject( x[, options], predicate[, thisArg] )`][@stdlib/ndarray/reject]</span><span class="delimiter">: </span><span class="description">return a shallow copy of an ndarray containing only those elements which fail a test implemented by a predicate function.</span>
 -   <span class="signature">[`safeCasts( [dtype] )`][@stdlib/ndarray/safe-casts]</span><span class="delimiter">: </span><span class="description">return a list of ndarray data types to which a provided ndarray data type can be safely cast.</span>
 -   <span class="signature">[`sameKindCasts( [dtype] )`][@stdlib/ndarray/same-kind-casts]</span><span class="delimiter">: </span><span class="description">return a list of ndarray data types to which a provided ndarray data type can be safely cast or cast within the same "kind".</span>
 -   <span class="signature">[`shape( x )`][@stdlib/ndarray/shape]</span><span class="delimiter">: </span><span class="description">return the shape of a provided ndarray.</span>
@@ -184,6 +188,10 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/ndarray/fancy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/fancy
 
+[@stdlib/ndarray/filter-map]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/filter-map
+
+[@stdlib/ndarray/filter]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/filter
+
 [@stdlib/ndarray/flag]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/flag
 
 [@stdlib/ndarray/flags]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/flags
@@ -194,6 +202,8 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/ndarray/index-modes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/index-modes
 
+[@stdlib/ndarray/map]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/map
+
 [@stdlib/ndarray/maybe-broadcast-array]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/maybe-broadcast-array
 
 [@stdlib/ndarray/maybe-broadcast-arrays]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/maybe-broadcast-arrays
@@ -222,6 +232,8 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/ndarray/promotion-rules]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/promotion-rules
 
+[@stdlib/ndarray/reject]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/reject
+
 [@stdlib/ndarray/safe-casts]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/safe-casts
 
 [@stdlib/ndarray/same-kind-casts]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/same-kind-casts