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feat: add blas/base/cher2
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‎lib/node_modules/@stdlib/blas/base/cher2/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 isnanf = require( '@stdlib/math/base/assert/is-nanf' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var Complex64Array = require( '@stdlib/array/complex64' );
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var Complex64 = require( '@stdlib/complex/float32/ctor' );
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var pkg = require( './../package.json' ).name;
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var cher2 = require( './../lib/cher2.js' );
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// VARIABLES //
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var options = {
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'dtype': 'float32'
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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} len - array length
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* @returns {Function} benchmark function
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*/
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function createBenchmark( len ) {
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var alpha;
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var xbuf;
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var ybuf;
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var Abuf;
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var x;
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var y;
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var A;
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xbuf = uniform( len*2, -100.0, 100.0, options );
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x = new Complex64Array( xbuf.buffer );
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ybuf = uniform( len*2, -100.0, 100.0, options );
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y = new Complex64Array( ybuf.buffer );
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Abuf = uniform( (len*len)*2, -100.0, 100.0, options );
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A = new Complex64Array( Abuf.buffer );
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alpha = new Complex64( 1.0, 0.0 );
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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 i;
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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cher2( 'row-major', 'lower', len, alpha, x, 1, y, 1, A, len );
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if ( isnanf( Abuf[ i%(len*2) ] ) ) {
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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 ( isnanf( Abuf[ i%(len*2) ] ) ) {
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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 len;
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var min;
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var max;
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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 = 4; // 10^max
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for ( i = min; i <= max; i++ ) {
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len = pow( 10, i );
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f = createBenchmark( len );
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bench( pkg+':len='+len, f );
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}
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}
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main();

‎lib/node_modules/@stdlib/blas/base/cher2/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 isnanf = require( '@stdlib/math/base/assert/is-nanf' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var Complex64Array = require( '@stdlib/array/complex64' );
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var Complex64 = require( '@stdlib/complex/float32/ctor' );
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var pkg = require( './../package.json' ).name;
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var cher2 = require( './../lib/ndarray.js' );
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// VARIABLES //
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var options = {
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'dtype': 'float32'
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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} len - array length
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* @returns {Function} benchmark function
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*/
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function createBenchmark( len ) {
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var alpha;
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var xbuf;
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var ybuf;
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var Abuf;
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var x;
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var y;
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var A;
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xbuf = uniform( len*2, -100.0, 100.0, options );
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x = new Complex64Array( xbuf.buffer );
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ybuf = uniform( len*2, -100.0, 100.0, options );
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y = new Complex64Array( ybuf.buffer );
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Abuf = uniform( (len*len)*2, -100.0, 100.0, options );
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A = new Complex64Array( Abuf.buffer );
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alpha = new Complex64( 1.0, 0.0 );
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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 i;
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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cher2( 'lower', len, alpha, x, 1, 0, y, 1, 0, A, len, 1, 0 );
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if ( isnanf( Abuf[ i%(len*2) ] ) ) {
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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 ( isnanf( Abuf[ i%(len*2) ] ) ) {
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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 len;
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var min;
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var max;
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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 = 4; // 10^max
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for ( i = min; i <= max; i++ ) {
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len = pow( 10, i );
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f = createBenchmark( len );
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bench( pkg+':ndarray:len='+len, f );
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}
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}
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main();

‎lib/node_modules/@stdlib/blas/base/cher2/docs/repl.txt‎

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{{alias}}( order, uplo, N, α, x, strideX, y, strideY, LDA )
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Performs the hermitian rank 2 operation
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`A = alpha*x*y**H + conjg( alpha )*y*x**H + A`, where `alpha` is a scalar,
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`x` and `y` are `N` element vectors and `A` is an `N` by `N` hermitian
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matrix.
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Indexing is relative to the first index. To introduce an offset, use typed
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array views.
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If `N` is equal to `0`, the function returns `A` unchanged.
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If `α` is equal to `0`, the function returns `A` unchanged.
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Parameters
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----------
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order: string
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Row-major (C-style) or column-major (Fortran-style) order.
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uplo: string
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Specifies whether the upper or lower triangular matrix of `A` is
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supplied. Must be either 'upper' or 'lower'.
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N: integer
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Number of elements along each dimension of `A`.
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α: number
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Scalar constant.
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x: Complex64Array
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First input array.
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strideX: integer
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Index increment for `x`.
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y: Complex64Array
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Second input array.
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strideY: integer
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Index increment for `y`.
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A: Complex64Array
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Input matrix.
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LDA: integer
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Stride of the first dimension of `A` (a.k.a., leading dimension of the
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matrix `A`).
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Returns
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-------
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A: Complex64Array
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Input matrix.
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Examples
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--------
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// Standard usage:
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> var x = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0 ] );
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> var y = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0 ] );
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> var A = new {{alias:@stdlib/array/complex64}}( [ 1.0, 0.0, 0.0, 0.0, 5.0, 6.0, 7.0, 0.0 ] );
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> var alpha = new {{alias:@stdlib/complex/float32/ctor}}( 1.0, 0.0 );
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> {{alias}}( 'row-major', 'lower', 2, alpha, x, 1, y, 1, A, 2 )
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<Complex64Array>[ 11.0, 0.0, 0.0, 0.0, 27.0, 2.0, 57.0, 0.0 ]
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// Advanced indexing:
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> var x = new {{alias:@stdlib/array/complex64}}( [ 3.0, 4.0, 1.0, 2.0 ] );
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> var y = new {{alias:@stdlib/array/complex64}}( [ 3.0, 4.0, 1.0, 2.0 ] );
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> var A = new {{alias:@stdlib/array/complex64}}( [ 1.0, 0.0, 0.0, 0.0, 5.0, 6.0, 7.0, 0.0 ] );
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> var alpha = new {{alias:@stdlib/complex/float32/ctor}}( 1.0, 0.0 );
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> {{alias}}( 'row-major', 'lower', 2, alpha, x, -1, y, -1, A, 2 )
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<Complex64Array>[ 11.0, 0.0, 0.0, 0.0, 27.0, 2.0, 57.0, 0.0 ]
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// Using typed array views:
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> var x0 = new {{alias:@stdlib/array/complex64}}( [ 0.0, 0.0, 3.0, 4.0, 1.0, 2.0 ] );
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> var y0 = new {{alias:@stdlib/array/complex64}}( [ 0.0, 0.0, 3.0, 4.0, 1.0, 2.0 ] );
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> var x1 = new {{alias:@stdlib/array/complex64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
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> var y1 = new {{alias:@stdlib/array/complex64}}( y0.buffer, y0.BYTES_PER_ELEMENT*1 );
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> var A = new {{alias:@stdlib/array/complex64}}( [ 1.0, 0.0, 0.0, 0.0, 5.0, 6.0, 7.0, 0.0 ] );
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> var alpha = new {{alias:@stdlib/complex/float32/ctor}}( 1.0, 0.0 );
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> {{alias}}( 'row-major', 'lower', 2, alpha, x1, -1, y1, -1, A, 2 )
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<Complex64Array>[ 11.0, 0.0, 0.0, 0.0, 27.0, 2.0, 57.0, 0.0 ]
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{{alias}}.ndarray( uplo, N, α, x, strideX, offsetX, y, strideY, offsetY, A, sa1, sa2, offsetA )
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Performs the hermitian rank 2 operation
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`A = alpha*x*y**H + conjg( alpha )*y*x**H + A`, where `alpha` is a scalar,
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`x` and `y` are `N` element vectors and `A` is an `N` by `N` hermitian
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matrix using alternative indexing semantics.
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While typed array views mandate a view offset based on the underlying
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buffer, the offset parameter supports indexing semantics based on a starting
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index.
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Parameters
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----------
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uplo: string
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Specifies whether the upper or lower triangular matrix of `A` is
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supplied. Must be either 'upper' or 'lower'.
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N: integer
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Number of elements along each dimension of `A`.
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α: number
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Scalar constant.
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x: Complex64Array
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First input array.
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strideX: integer
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Index increment for `x`.
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offsetX: integer
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Starting index for `x`.
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y: Complex64Array
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Second input array.
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strideY: integer
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Index increment for `y`.
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offsetY: integer
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Starting index for `y`.
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A: Complex64Array
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Input matrix.
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sa1: integer
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Stride of the first dimension of `A`.
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sa2: integer
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Stride of the second dimension of `A`.
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offsetA: integer
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Starting index for `A`.
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Returns
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-------
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A: Complex64Array
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Input matrix.
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Examples
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--------
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> var x = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0 ] );
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> var y = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0 ] );
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> var A = new {{alias:@stdlib/array/complex64}}( [ 1.0, 0.0, 0.0, 0.0, 5.0, 6.0, 7.0, 0.0 ] );
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> var alpha = new {{alias:@stdlib/complex/float32/ctor}}( 1.0, 0.0 );
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> {{alias}}.ndarray( 'lower', 2, alpha, x, 1, 0, y, 1, 0, A, 2, 1, 0 )
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<Complex64Array>[ 11.0, 0.0, 0.0, 0.0, 27.0, 2.0, 57.0, 0.0 ]
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See Also
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--------

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