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feat: add blas/base/dtrsv
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‎lib/node_modules/@stdlib/blas/base/dtrsv/README.md

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@@ -184,24 +184,75 @@ console.log( x );
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<section class="usage">
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<!-- C usage documentation. -->
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<section class="usage">
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### Usage
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```c
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TODO
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#include "stdlib/blas/base/dtrsv.h"
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```
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#### c_dtrsv( order, uplo, trans, diag, N, \*A, LDA, \*X, strideX )
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Solves one of the systems of equations `A*x = b` or `A^T*x = b` where `b` and `x` are `N` element vectors and `A` is an `N` by `N` unit, or non-unit, upper or lower triangular matrix.
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```c
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#include "stdlib/blas/base/shared.h"
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double A[] = { 1.0, 2.0, 3.0, 0.0, 1.0, 2.0, 0.0, 0.0, 1.0 };
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const double x[] = { 1.0, 2.0, 3.0 };
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c_dtrsv( CblasRowMajor, CblasUpper, CblasNoTrans, CblasUnit, 3, A, 3, x, 1 );
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```
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The function accepts the following arguments:
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- **order**: `[in] CBLAS_LAYOUT` storage layout.
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- **uplo**: `[in] CBLAS_UPLO` specifies whether `A` is an upper or lower triangular matrix.
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- **trans**: `[in] CBLAS_TRANSPOSE` specifies whether `A` should be transposed, conjugate-transposed, or not transposed.
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- **diag**: `[in] CBLAS_DIAG` specifies whether `A` has a unit diagonal.
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- **N**: `[in] CBLAS_INT` number of elements along each dimension of `A`.
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- **A**: `[inout] double*` input matrix.
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- **LDA**: `[in] CBLAS_INT` stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`).
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- **X**: `[in] double*` input vector.
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- **strideX**: `[in] CBLAS_INT` index increment for `X`.
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```c
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void c_dtrsv( const CBLAS_LAYOUT order, const CBLAS_UPLO uplo, const CBLAS_TRANSPOSE trans, const CBLAS_DIAG diag, const CBLAS_INT N, const double *A, const CBLAS_INT LDA, double *x, const CBLAS_INT strideX )
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```
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#### TODO
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<!-- lint disable maximum-heading-length -->
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#### c_dtrsv_ndarray( uplo, trans, diag, N, \*A, strideA1, strideA2, offsetA, \*X, strideX, offsetA )
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TODO.
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Performs one of the matrix-vector operations `x = A*x` or `x = A^T*x` using alternative indexing semantics, where `x` is an `N` element vector and `A` is an `N` by `N` unit, or non-unit, upper or lower triangular matrix.
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```c
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TODO
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#include "stdlib/blas/base/shared.h"
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double A[] = { 1.0, 2.0, 3.0, 0.0, 1.0, 2.0, 0.0, 0.0, 1.0 };
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const double x[] = { 1.0, 2.0, 3.0 };
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c_dtrsv_ndarray( CblasUpper, CblasNoTrans, CblasUnit, 3, A, 3, 1, 0, x, 1, 0 );
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```
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TODO
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The function accepts the following arguments:
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- **uplo**: `[in] CBLAS_UPLO` specifies whether `A` is an upper or lower triangular matrix.
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- **trans**: `[in] CBLAS_TRANSPOSE` specifies whether `A` should be transposed, conjugate-transposed, or not transposed.
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- **diag**: `[in] CBLAS_DIAG` specifies whether `A` has a unit diagonal.
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- **N**: `[in] CBLAS_INT` number of elements along each dimension of `A`.
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- **A**: `[inout] double*` input matrix.
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- **strideA1**: `[in] CBLAS_INT` stride of the first dimension of `A`.
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- **strideA2**: `[in] CBLAS_INT` stride of the second dimension of `A`.
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- **offsetA**: `[in] CBLAS_INT` starting index for `A`.
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- **X**: `[in] double*` input vector.
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- **strideX**: `[in] CBLAS_INT` index increment for `X`.
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- **offsetX**: `[in] CBLAS_INT` starting index for `X`.
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```c
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TODO
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void c_dtrsv_ndarray( const CBLAS_UPLO uplo, const CBLAS_TRANSPOSE trans, const CBLAS_DIAG diag, const CBLAS_INT N, const double *A, const CBLAS_INT strideA1, const CBLAS_INT strideA2, const CBLAS_INT offsetA, double *x, const CBLAS_INT strideX, const CBLAS_INT offsetX )
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```
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</section>
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### Examples
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```c
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TODO
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#include "stdlib/blas/base/dtrsv.h"
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#include "stdlib/blas/base/shared.h"
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#include <stdio.h>
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int main( void ) {
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// Create a strided array:
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const double A[] = { 1.0, 0.0, 0.0, 2.0, 1.0, 0.0, 3.0, 2.0, 1.0 };
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double X[] = { 1.0, 2.0, 3.0 };
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// Specify the number of elements along each dimension of `A`:
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const int N = 3;
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// Perform the matrix-vector operations `A*X = b` for `lower` triangular matrix `A`:
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c_dtrsv( CblasRowMajor, CblasLower, CblasNoTrans, CblasNonUnit, N, A, N, X, 1 );
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// Print the result:
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for ( int i = 0; i < N; i++ ) {
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printf( "X[ %i ] = %f\n", i, X[ i ] );
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}
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// Perform the matrix-vector operations `A*X = b` for `lower` triangular matrix `A`:
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c_dtrsv_ndarray( CblasLower, CblasNoTrans, CblasNonUnit, N, A, N, 1, 0, X, 1, 0 );
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// Print the result:
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for ( int i = 0; i < N; i++ ) {
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printf( "X[ %i ] = %f\n", i, X[ i ] );
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}
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}
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```
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</section>

‎lib/node_modules/@stdlib/blas/base/dtrsv/benchmark/benchmark.native.js

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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2025 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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// MODULES //
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var resolve = require( 'path' ).resolve;
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var bench = require( '@stdlib/bench' );
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
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var zeros = require( '@stdlib/array/zeros' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var floor = require( '@stdlib/math/base/special/floor' );
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var tryRequire = require( '@stdlib/utils/try-require' );
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var pkg = require( './../package.json' ).name;
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// VARIABLES //
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var dtrsv = tryRequire( resolve( __dirname, './../lib/dtrsv.native.js' ) );
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var opts = {
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'skip': ( dtrsv instanceof Error )
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};
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var options = {
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'dtype': 'float64'
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};
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// FUNCTIONS //
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/**
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* Creates a benchmark function.
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*
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* @private
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* @param {PositiveInteger} N - number of elements along each dimension
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* @returns {Function} benchmark function
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*/
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function createBenchmark( N ) {
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var A = discreteUniform( N*N, -10.0, 10.0, options );
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var x = zeros( N, options.dtype );
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return benchmark;
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/**
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* Benchmark function.
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*
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* @private
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* @param {Benchmark} b - benchmark instance
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*/
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function benchmark( b ) {
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var z;
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var i;
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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z = dtrsv( 'row-major', 'upper', 'transpose', 'non-unit', N, A, N, x, 1 );
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if ( isnan( z[ i%z.length ] ) ) {
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b.fail( 'should not return NaN' );
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}
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}
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b.toc();
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if ( isnan( z[ i%z.length ] ) ) {
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b.fail( 'should not return NaN' );
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}
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b.pass( 'benchmark finished' );
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b.end();
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}
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}
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// MAIN //
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/**
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* Main execution sequence.
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*
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* @private
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*/
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function main() {
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var min;
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var max;
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var N;
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var f;
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var i;
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min = 1; // 10^min
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max = 6; // 10^max
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for ( i = min; i <= max; i++ ) {
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N = floor( pow( pow( 10, i ), 1.0/2.0 ) );
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f = createBenchmark( N );
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bench( pkg+':size='+(N*N), opts, f );
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}
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}
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main();

‎lib/node_modules/@stdlib/blas/base/dtrsv/benchmark/benchmark.ndarray.native.js

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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2025 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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// MODULES //
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var resolve = require( 'path' ).resolve;
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var bench = require( '@stdlib/bench' );
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
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var zeros = require( '@stdlib/array/zeros' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var floor = require( '@stdlib/math/base/special/floor' );
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var tryRequire = require( '@stdlib/utils/try-require' );
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var pkg = require( './../package.json' ).name;
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// VARIABLES //
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var dtrsv = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) );
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var opts = {
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'skip': ( dtrsv instanceof Error )
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};
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var options = {
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'dtype': 'float64'
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};
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// FUNCTIONS //
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/**
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* Creates a benchmark function.
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*
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* @private
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* @param {PositiveInteger} N - number of elements along each dimension
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* @returns {Function} benchmark function
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*/
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function createBenchmark( N ) {
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var A = discreteUniform( N*N, -10.0, 10.0, options );
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var x = zeros( N, options.dtype );
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return benchmark;
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/**
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* Benchmark function.
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*
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* @private
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* @param {Benchmark} b - benchmark instance
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*/
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function benchmark( b ) {
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var z;
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var i;
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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z = dtrsv( 'upper', 'transpose', 'non-unit', N, A, N, 1, 0, x, 1, 0 );
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if ( isnan( z[ i%z.length ] ) ) {
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b.fail( 'should not return NaN' );
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}
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}
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b.toc();
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if ( isnan( z[ i%z.length ] ) ) {
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b.fail( 'should not return NaN' );
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}
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b.pass( 'benchmark finished' );
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b.end();
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}
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}
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// MAIN //
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/**
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* Main execution sequence.
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*
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* @private
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*/
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function main() {
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var min;
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var max;
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var N;
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var f;
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var i;
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min = 1; // 10^min
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max = 6; // 10^max
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for ( i = min; i <= max; i++ ) {
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N = floor( pow( pow( 10, i ), 1.0/2.0 ) );
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f = createBenchmark( N );
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bench( pkg+':ndarray:size='+(N*N), opts, f );
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}
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}
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main();

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