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feat: update blas/ext/base TypeScript declarations #13709

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kgryte merged 1 commit into from
Jul 28, 2026
Merged

feat: update blas/ext/base TypeScript declarations #13709

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165 changes: 165 additions & 0 deletions lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -87,6 +87,7 @@ import dlastIndexOfTruthy = require( '@stdlib/blas/ext/base/dlast-index-of-truth
import dlinspace = require( '@stdlib/blas/ext/base/dlinspace' );
import dlogspace = require( '@stdlib/blas/ext/base/dlogspace' );
import dminheapSiftDown = require( '@stdlib/blas/ext/base/dminheap-sift-down' );
import dminheapify = require( '@stdlib/blas/ext/base/dminheapify' );
import dmskrev = require( '@stdlib/blas/ext/base/dmskrev' );
import dnanasum = require( '@stdlib/blas/ext/base/dnanasum' );
import dnanasumors = require( '@stdlib/blas/ext/base/dnanasumors' );
Expand Down Expand Up @@ -229,12 +230,14 @@ import gsumkbn = require( '@stdlib/blas/ext/base/gsumkbn' );
import gsumkbn2 = require( '@stdlib/blas/ext/base/gsumkbn2' );
import gsumors = require( '@stdlib/blas/ext/base/gsumors' );
import gsumpw = require( '@stdlib/blas/ext/base/gsumpw' );
import gtriu = require( '@stdlib/blas/ext/base/gtriu' );
import gunitspace = require( '@stdlib/blas/ext/base/gunitspace' );
import gvander = require( '@stdlib/blas/ext/base/gvander' );
import gwapx = require( '@stdlib/blas/ext/base/gwapx' );
import gwax = require( '@stdlib/blas/ext/base/gwax' );
import gwaxpb = require( '@stdlib/blas/ext/base/gwaxpb' );
import gwhere = require( '@stdlib/blas/ext/base/gwhere' );
import gwxmy = require( '@stdlib/blas/ext/base/gwxmy' );
import gwxpy = require( '@stdlib/blas/ext/base/gwxpy' );
import gwxsa = require( '@stdlib/blas/ext/base/gwxsa' );
import gwxsy = require( '@stdlib/blas/ext/base/gwxsy' );
Expand Down Expand Up @@ -336,6 +339,8 @@ import wasm = require( '@stdlib/blas/ext/base/wasm' );
import zapx = require( '@stdlib/blas/ext/base/zapx' );
import zaxpb = require( '@stdlib/blas/ext/base/zaxpb' );
import zaxpby = require( '@stdlib/blas/ext/base/zaxpby' );
import zcartesianProduct = require( '@stdlib/blas/ext/base/zcartesian-product' );
import zcartesianSquare = require( '@stdlib/blas/ext/base/zcartesian-square' );
import zdiff = require( '@stdlib/blas/ext/base/zdiff' );
import zfill = require( '@stdlib/blas/ext/base/zfill' );
import zindexOf = require( '@stdlib/blas/ext/base/zindex-of' );
Expand Down Expand Up @@ -2588,6 +2593,36 @@ interface Namespace {
*/
dminheapSiftDown: typeof dminheapSiftDown;

/**
* Converts a double-precision floating-point strided array to a min-heap.
*
* ## Notes
*
* - The min-heap algorithm is sensitive to the presence of `NaN` values. Since `NaN` comparisons always return `false`, if `NaN` values are present in the input array, the results may be unpredictable.
*
* @param N - number of indexed elements
* @param x - input array
* @param strideX - stride length
* @returns input array
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var x = new Float64Array( [ 7.0, 5.0, 3.0, 1.0, 9.0 ] );
*
* ns.dminheapify( 5, x, 1 );
* // x => <Float64Array>[ 1.0, 5.0, 3.0, 7.0, 9.0 ]
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var x = new Float64Array( [ 7.0, 0.0, 5.0, 0.0, 3.0, 0.0, 1.0, 0.0, 9.0 ] );
*
* ns.dminheapify.ndarray( 5, x, 2, 0 );
* // x => <Float64Array>[ 1.0, 0.0, 5.0, 0.0, 3.0, 0.0, 7.0, 0.0, 9.0 ]
*/
dminheapify: typeof dminheapify;

/**
* Reverses a double-precision floating-point strided array in-place according to a mask.
*
Expand Down Expand Up @@ -6536,6 +6571,35 @@ interface Namespace {
*/
gsumpw: typeof gsumpw;

/**
* Copies the upper triangular part of a matrix `A` to another matrix `B`.
*
* @param order - storage layout of `A` and `B`
* @param M - number of rows in matrix `A`
* @param N - number of columns in matrix `A`
* @param k - diagonal below which to ignore
* @param A - input matrix
* @param LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`)
* @param B - output matrix
* @param LDB - stride of the first dimension of `B` (a.k.a., leading dimension of the matrix `B`)
* @returns `B`
*
* @example
* var A = [ 1.0, 2.0, 3.0, 4.0 ];
* var B = [ 0.0, 0.0, 0.0, 0.0 ];
*
* ns.gtriu( 'row-major', 2, 2, 0, A, 2, B, 2 );
* // B => [ 1.0, 2.0, 0.0, 4.0 ]
*
* @example
* var A = [ 1.0, 2.0, 3.0, 4.0 ];
* var B = [ 0.0, 0.0, 0.0, 0.0 ];
*
* ns.gtriu.ndarray( 2, 2, 0, A, 2, 1, 0, B, 2, 1, 0 );
* // B => [ 1.0, 2.0, 0.0, 4.0 ]
*/
gtriu: typeof gtriu;

/**
* Fills a strided array with linearly spaced numeric elements which increment by `1` starting from a specified value.
*
Expand Down Expand Up @@ -6704,6 +6768,36 @@ interface Namespace {
*/
gwhere: typeof gwhere;

/**
* Multiplies elements of a strided array `x` by the corresponding elements of a strided array `y` and assigns the results to elements in a strided array `w`.
*
* @param N - number of indexed elements
* @param x - first input array
* @param strideX - `x` stride length
* @param y - second input array
* @param strideY - `y` stride length
* @param w - output array
* @param strideW - `w` stride length
* @returns `w`
*
* @example
* var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];
* var y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ];
* var w = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
*
* ns.gwxmy( x.length, x, 1, y, 1, w, 1 );
* // w => [ 2.0, 6.0, 12.0, 20.0, 30.0 ]
*
* @example
* var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];
* var y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ];
* var w = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
*
* ns.gwxmy.ndarray( x.length, x, 1, 0, y, 1, 0, w, 1, 0 );
* // w => [ 2.0, 6.0, 12.0, 20.0, 30.0 ]
*/
gwxmy: typeof gwxmy;

/**
* Adds elements of a strided array `x` to the corresponding elements of a strided array `y` and assigns the results to elements in a strided array `w`.
*
Expand Down Expand Up @@ -9727,6 +9821,77 @@ interface Namespace {
*/
zaxpby: typeof zaxpby;

/**
* Computes the Cartesian product for two double-precision complex floating-point strided arrays.
*
* ## Notes
*
* - Pairs are stored as rows in the output matrix, where the first column contains the first element of each pair and the second column contains the second element.
*
* @param order - storage layout
* @param M - number of indexed elements in `x`
* @param N - number of indexed elements in `y`
* @param x - first input array
* @param strideX - stride length for `x`
* @param y - second input array
* @param strideY - stride length for `y`
* @param out - output array
* @param LDO - stride length between successive contiguous vectors of the matrix `out` (a.k.a., leading dimension of `out`)
* @returns output array
*
* @example
* var Complex128Array = require( '@stdlib/array/complex128' );
*
* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );
* var y = new Complex128Array( [ 5.0, 6.0, 7.0, 8.0 ] );
* var out = new Complex128Array( 8 );
*
* ns.zcartesianProduct( 'row-major', x.length, y.length, x, 1, y, 1, out, 2 );
* // out => <Complex128Array>[ 1.0, 2.0, 5.0, 6.0, 1.0, 2.0, 7.0, 8.0, 3.0, 4.0, 5.0, 6.0, 3.0, 4.0, 7.0, 8.0 ]
*
* @example
* var Complex128Array = require( '@stdlib/array/complex128' );
*
* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );
* var y = new Complex128Array( [ 5.0, 6.0, 7.0, 8.0 ] );
* var out = new Complex128Array( 8 );
*
* ns.zcartesianProduct.ndarray( x.length, y.length, x, 1, 0, y, 1, 0, out, 2, 1, 0 );
* // out => <Complex128Array>[ 1.0, 2.0, 5.0, 6.0, 1.0, 2.0, 7.0, 8.0, 3.0, 4.0, 5.0, 6.0, 3.0, 4.0, 7.0, 8.0 ]
*/
zcartesianProduct: typeof zcartesianProduct;

/**
* Computes the Cartesian square for a double-precision complex floating-point strided array.
*
* @param order - storage layout
* @param N - number of indexed elements
* @param x - input array
* @param strideX - stride length for `x`
* @param out - output array
* @param LDO - stride length between successive contiguous vectors of the matrix `out` (a.k.a., leading dimension of `out`)
* @returns output array
*
* @example
* var Complex128Array = require( '@stdlib/array/complex128' );
*
* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );
* var out = new Complex128Array( 8 );
*
* ns.zcartesianSquare( 'row-major', x.length, x, 1, out, 2 );
* // out => <Complex128Array>[ 1.0, 2.0, 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0 ]
*
* @example
* var Complex128Array = require( '@stdlib/array/complex128' );
*
* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );
* var out = new Complex128Array( 8 );
*
* ns.zcartesianSquare.ndarray( x.length, x, 1, 0, out, 2, 1, 0 );
* // out => <Complex128Array>[ 1.0, 2.0, 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0 ]
*/
zcartesianSquare: typeof zcartesianSquare;

/**
* Calculates the k-th discrete forward difference of a double-precision complex floating-point strided array.
*
Expand Down