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feat: add examples and benchmarks
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‎lib/node_modules/@stdlib/lapack/base/dlatrs/benchmark/benchmark.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 bench = require( '@stdlib/bench' );
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var uniform = require( '@stdlib/random/array/uniform' );
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var Float64Array = require( '@stdlib/array/float64' );
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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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 pkg = require( './../package.json' ).name;
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var dlatrs = require( './../lib/dlatrs.js' );
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// VARIABLES //
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var LAYOUTS = [
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'row-major',
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'column-major'
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];
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var MATRIX_TRIANGLES = [
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'upper',
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'lower'
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];
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var TRANSPOSE_OPS = [
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'transpose',
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'no-transpose'
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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 {string} order - storage layout
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* @param {PositiveInteger} N - number of elements along each dimension
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* @param {string} uplo - specifies whether `A` is an upper or lower triangular matrix
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* @param {string} trans - specifies whether `A` should be transposed or not transposed
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* @returns {Function} benchmark function
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*/
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function createBenchmark( order, N, uplo, trans ) {
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var CNORM;
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var X;
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var A;
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A = uniform( N*N, 2.0, 10.0, {
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'dtype': 'float64'
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});
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X = uniform( N, 1.0, 10.0, {
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'dtype': 'float64'
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});
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CNORM = new Float64Array( N );
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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 = dlatrs( order, uplo, trans, 'non-unit', 'no', N, A, N, X, CNORM );
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if ( isnan( z ) ) {
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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 ) ) {
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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 trans;
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var uplo;
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var min;
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var max;
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var ord;
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var N;
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var f;
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var i;
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var j;
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var k;
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var l;
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min = 1; // 10^min
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max = 6; // 10^max
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for ( k = 0; k < LAYOUTS.length; k++ ) {
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ord = LAYOUTS[ k ];
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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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for ( j = 0; j < MATRIX_TRIANGLES.length; j++ ) {
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uplo = MATRIX_TRIANGLES[ j ];
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for ( l = 0; l < TRANSPOSE_OPS.length; l++ ) {
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trans = TRANSPOSE_OPS[ l ];
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f = createBenchmark( ord, N, uplo, trans );
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bench( pkg+'::square_matrix:order='+ord+',uplo='+uplo+',trans='+trans+',size='+(N*N), f );
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}
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}
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}
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}
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}
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main();

‎lib/node_modules/@stdlib/lapack/base/dlatrs/benchmark/benchmark.ndarray.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 bench = require( '@stdlib/bench' );
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var uniform = require( '@stdlib/random/array/uniform' );
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var Float64Array = require( '@stdlib/array/float64' );
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string' );
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var floor = require( '@stdlib/math/base/special/floor' );
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var pkg = require( './../package.json' ).name;
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var dlatrs = require( './../lib/ndarray.js' );
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// VARIABLES //
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var LAYOUTS = [
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'row-major',
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'column-major'
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];
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var MATRIX_TRIANGLES = [
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'upper',
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'lower'
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];
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var TRANSPOSE_OPS = [
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'transpose',
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'no-transpose'
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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 {string} order - storage layout
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* @param {PositiveInteger} N - number of elements along each dimension
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* @param {string} uplo - specifies whether `A` is an upper or lower triangular matrix
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* @param {string} trans - specifies whether `A` should be transposed or not transposed
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* @returns {Function} benchmark function
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*/
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function createBenchmark( order, N, uplo, trans ) {
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var CNORM;
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var sa1;
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var sa2;
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var X;
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var A;
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A = uniform( N*N, 2.0, 10.0, {
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'dtype': 'float64'
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});
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X = uniform( N, 1.0, 10.0, {
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'dtype': 'float64'
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});
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if ( isColumnMajor( order ) ) {
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sa1 = 1;
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sa2 = N;
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} else { // order === 'row-major'
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sa1 = N;
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sa2 = 1;
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}
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CNORM = new Float64Array( N );
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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 = dlatrs( uplo, trans, 'non-unit', 'no', N, A, sa1, sa2, 0, X, 1, 0, CNORM, 1, 0 );
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if ( isnan( z ) ) {
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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 ) ) {
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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 trans;
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var uplo;
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var min;
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var max;
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var ord;
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var N;
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var f;
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var i;
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var j;
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var k;
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var l;
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min = 1; // 10^min
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max = 6; // 10^max
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for ( k = 0; k < LAYOUTS.length; k++ ) {
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ord = LAYOUTS[ k ];
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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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for ( j = 0; j < MATRIX_TRIANGLES.length; j++ ) {
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uplo = MATRIX_TRIANGLES[ j ];
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for ( l = 0; l < TRANSPOSE_OPS.length; l++ ) {
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trans = TRANSPOSE_OPS[ l ];
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f = createBenchmark( ord, N, uplo, trans );
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bench( pkg+'::square_matrix:order='+ord+',uplo='+uplo+',trans='+trans+',size='+(N*N), f );
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}
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}
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}
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}
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}
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main();

‎lib/node_modules/@stdlib/lapack/base/dlatrs/examples/index.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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var Float64Array = require( '@stdlib/array/float64' );
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var numel = require( '@stdlib/ndarray/base/numel' );
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var uniform = require( '@stdlib/random/array/uniform' );
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var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
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var dlatrs = require( './../lib' );
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// Specify matrix meta data:
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var shape = [ 3, 3 ];
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var strides = [ 3, 1 ];
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var offset = 0;
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var N = numel( shape );
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var order = 'row-major';
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// Create a matrix stored in linear memory:
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var A = uniform( N, 2.0, 10.0, {
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'dtype': 'float64'
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});
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console.log( ndarray2array( A, shape, strides, offset, order ) );
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var X = uniform( shape[ 0 ], 0.0, 10.0, {
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'dtype': 'float64'
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});
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var CNORM = new Float64Array( shape[ 0 ] );
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var scale = dlatrs( order, 'upper', 'no-transpose', 'non-unit', 'no', shape[ 0 ], A, strides[ 0 ], X, CNORM );
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console.log( ndarray2array( A, shape, strides, offset, order ) );
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console.log( 'scaling factor: ', scale );

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