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docs: add ts declaration file and test.ts
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‎lib/node_modules/@stdlib/lapack/base/dgttrf/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 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 Int32Array = require( '@stdlib/array/int32' );
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var Float64Array = require( '@stdlib/array/float64' );
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var pkg = require( './../package.json' ).name;
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var dgttrf = require( './../lib/dgttrf.js' );
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// VARIABLES //
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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} 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 IPIV = new Int32Array( len );
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var DU2 = new Float64Array( len-2 );
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var DL = uniform( len-1, 0.0, 100.0, options );
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var DU = uniform( len-1, 0.0, 100.0, options );
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var D = uniform( len, 0.0, 100.0, options );
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return benchmark;
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function benchmark( b ) {
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var d;
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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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d = dgttrf( len, DL, D, DU, DU2, IPIV );
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if ( isnan( d ) ) {
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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( d ) ) {
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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 = 6; // 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/lapack/base/dgttrf/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 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 Int32Array = require( '@stdlib/array/int32' );
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var Float64Array = require( '@stdlib/array/float64' );
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var pkg = require( './../package.json' ).name;
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var dgttrf = require( './../lib/ndarray.js' );
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// VARIABLES //
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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} 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 IPIV = new Int32Array( len );
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var DU2 = new Float64Array( len-2 );
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var DL = uniform( len-1, 0.0, 100.0, options );
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var DU = uniform( len-1, 0.0, 100.0, options );
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var D = uniform( len, 0.0, 100.0, options );
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return benchmark;
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function benchmark( b ) {
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var d;
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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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d = dgttrf( len, DL, 1, 0, D, 1, 0, DU, 1, 0, DU2, 1, 0, IPIV, 1, 0 ); // eslint-disable-line max-len
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if ( isnan( d ) ) {
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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( d ) ) {
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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 = 6; // 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/lapack/base/dgttrf/docs/types/index.d.ts

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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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// TypeScript Version: 4.1
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/**
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* Status code.
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*
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* ## Notes
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*
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* The status code indicates the following conditions:
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*
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* - if equal to zero, then the factorization was successful.
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* - if less than zero, then the k-th argument had an illegal value, where `k = -StatusCode`.
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* - if greater than zero, then the leading principal minor of order `k` is not positive, where `k = StatusCode`. If `k < N`, then the factorization could not be completed. If `k = N`, then the factorization was completed, but `D(N) <= 0`, meaning that the matrix `A` is not positive definite.
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*/
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type StatusCode = number;
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/**
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* Interface describing `dgttrf`.
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*/
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interface Routine {
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/**
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* Computes an LU factorization of a real tri diagonal matrix A using elimination with partial pivoting and row interchanges.
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*
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* @param N - order of matrix `A`
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* @param DL - the `N-1` subdiagonal elements of `A`
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* @param D - the `N` diagonal elements of `A`
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* @param DU - the `N-1` superdiagonal elements of `A`
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* @param DU2 - the `N-2` elements of the second superdiagonal of `A`
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* @param IPIV - vector of pivot indices
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* @returns status code
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*
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* @example
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* var Float64Array = require( '@stdlib/array/float64' );
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* var Int32Array = require( '@stdlib/array/int32' );
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*
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* var DL = new Float64Array( [ 1.0, 1.0 ] );
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* var D = new Float64Array( [ 2.0, 3.0, 1.0 ] );
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* var DU = new Float64Array( [ 1.0, 1.0 ] );
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* var DU2 = new Float64Array( 1 );
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* var IPIV = new Int32Array( 3 );
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*
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* dgttrf( 3, DL, D, DU, DU2, IPIV );
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* // DL => <Float64Array>[ 0.5, 0.4 ]
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* // D => <Float64Array>[ 2, 2.5, 0.6 ]
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* // DU => <Float64Array>[ 1, 1 ]
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* // DU2 => <Float64Array>[ 0 ]
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*/
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( N: number, DL: Float64Array, D: Float64Array, DU: Float64Array, DU2: Float64Array, IPIV: Int32Array ): StatusCode;
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/**
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* Computes an LU factorization of a real tri diagonal matrix A using elimination with partial pivoting and row interchanges and alternative indexing semantics.
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*
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* @param N - order of matrix `A`
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* @param DL - the `N-1` subdiagonal elements of `A`
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* @param strideDL - stride of the subdiagonal elements of `A`
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* @param offsetDL - offset of the subdiagonal elements of `A`
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* @param D - the `N` diagonal elements of `A`
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* @param strideD - stride of the diagonal elements of `A`
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* @param offsetD - offset of the diagonal elements of `A`
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* @param DU - the `N-1` superdiagonal elements of `A`
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* @param strideDU - stride of the first superdiagonal elements of `A`
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* @param offsetDU - offset of the first superdiagonal elements of `A`
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* @param DU2 - the `N-2` elements of the second superdiagonal of `A`
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* @param strideDU2 - stride of the second superdiagonal elements of `A`
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* @param offsetDU2 - offset of the second superdiagonal elements of `A`
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* @param IPIV - vector of pivot indices
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* @param strideIPIV - `IPIV` stride length
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* @param offsetIPIV - index offset for `IPIV`
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* @returns status code
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*
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* @example
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* var DL = new Float64Array( [ 1.0, 1.0 ] );
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* var D = new Float64Array( [ 2.0, 3.0, 1.0 ] );
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* var DU = new Float64Array( [ 1.0, 1.0 ] );
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* var DU2 = new Float64Array( 1 );
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* var IPIV = new Int32Array( 3 );
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*
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* dgttrf.ndarray( 3, DL, 1, 0, D, 1, 0, DU, 1, 0, DU2, 1, 0, IPIV, 1, 0 );
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* // DL => <Float64Array>[ 0.5, 0.4 ]
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* // D => <Float64Array>[ 2, 2.5, 0.6 ]
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* // DU => <Float64Array>[ 1, 1 ]
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* // DU2 => <Float64Array>[ 0 ]
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*/
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ndarray( N: number, DL: Float64Array, strideDL: number, offsetDL: number, D: Float64Array, strideD: number, offsetD: number, DU: Float64Array, strideDU: number, offsetDU: number, DU2: Float64Array, strideDU2: number, offsetDU2: number, IPIV: Int32Array, strideIPIV: number, offsetIPIV: number ): StatusCode;
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}
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/**
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* LAPACK routine to compute an LU factorization of a real tri diagonal matrix A using elimination with partial pivoting and row interchanges.
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*
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* @param N - order of matrix `A`
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* @param DL - the `N-1` subdiagonal elements of `A`
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* @param D - the `N` diagonal elements of `A`
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* @param DU - the `N-1` superdiagonal elements of `A`
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* @param DU2 - the `N-2` elements of the second superdiagonal of `A`
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* @param IPIV - vector of pivot indices
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* @returns status code
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*
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* @example
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* var Float64Array = require( '@stdlib/array/float64' );
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* var Int32Array = require( '@stdlib/array/int32' );
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*
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* var DL = new Float64Array( [ 1.0, 1.0 ] );
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* var D = new Float64Array( [ 2.0, 3.0, 1.0 ] );
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* var DU = new Float64Array( [ 1.0, 1.0 ] );
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* var DU2 = new Float64Array( 1 );
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* var IPIV = new Int32Array( 3 );
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*
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* dgttrf( 3, DL, D, DU, DU2, IPIV );
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* // DL => <Float64Array>[ 0.5, 0.4 ]
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* // D => <Float64Array>[ 2, 2.5, 0.6 ]
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* // DU => <Float64Array>[ 1, 1 ]
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* // DU2 => <Float64Array>[ 0 ]
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*
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* @example
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* var Float64Array = require( '@stdlib/array/float64' );
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* var Int32Array = require( '@stdlib/array/int32' );
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*
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* var DL = new Float64Array( [ 1.0, 1.0 ] );
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* var D = new Float64Array( [ 2.0, 3.0, 1.0 ] );
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* var DU = new Float64Array( [ 1.0, 1.0 ] );
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* var DU2 = new Float64Array( 1 );
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* var IPIV = new Int32Array( 3 );
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*
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* dgttrf.ndarray( 3, DL, 1, 0, D, 1, 0, DU, 1, 0, DU2, 1, 0, IPIV, 1, 0 );
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* // DL => <Float64Array>[ 0.5, 0.4 ]
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* // D => <Float64Array>[ 2, 2.5, 0.6 ]
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* // DU => <Float64Array>[ 1, 1 ]
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* // DU2 => <Float64Array>[ 0 ]
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*/
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declare var dgttrf: Routine;
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// EXPORTS //
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export = dgttrf;

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