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feat: add blas/ext/base/ndarray/dcusumkbn
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146 changes: 146 additions & 0 deletions
146
lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn/README.md
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| <!-- | ||
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| @license Apache-2.0 | ||
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| Copyright (c) 2025 The Stdlib Authors. | ||
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| Licensed under the Apache License, Version 2.0 (the "License"); | ||
| you may not use this file except in compliance with the License. | ||
| You may obtain a copy of the License at | ||
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| http://www.apache.org/licenses/LICENSE-2.0 | ||
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| Unless required by applicable law or agreed to in writing, software | ||
| distributed under the License is distributed on an "AS IS" BASIS, | ||
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| See the License for the specific language governing permissions and | ||
| limitations under the License. | ||
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| --> | ||
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| # dcusumkbn | ||
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| > Compute the cumulative sum of a one-dimensional double-precision floating-point ndarray using an improved Kahan–Babuška algorithm. | ||
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| <section class="intro"> | ||
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| </section> | ||
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| <!-- /.intro --> | ||
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| <section class="usage"> | ||
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| ## Usage | ||
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| ```javascript | ||
| var dcusumkbn = require( '@stdlib/blas/ext/base/ndarray/dcusumkbn' ); | ||
| ``` | ||
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| #### dcusumkbn( arrays ) | ||
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| Computes the cumulative sum of a one-dimensional double-precision floating-point ndarray using an improved Kahan–Babuška algorithm. | ||
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| ```javascript | ||
| var Float64Array = require( '@stdlib/array/float64' ); | ||
| var ndarray2array = require( '@stdlib/ndarray/to-array' ); | ||
| var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); | ||
| var ndarray = require( '@stdlib/ndarray/base/ctor' ); | ||
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| var xbuf = new Float64Array( [ 1.0, 3.0, 4.0, 2.0 ] ); | ||
| var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); | ||
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| var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); | ||
| var y = new ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' ); | ||
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| var initial = scalar2ndarray( 0.0, 'float64', 'row-major' ); | ||
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| var v = dcusumkbn( [ x, y, initial ] ); | ||
| // returns <ndarray> | ||
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| var bool = ( v === y ); | ||
| // returns true | ||
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| var arr = ndarray2array( v ); | ||
| // returns [ 1.0, 4.0, 8.0, 10.0 ] | ||
| ``` | ||
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| The function has the following parameters: | ||
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| - **arrays**: array-like object containing a one-dimensional input ndarray, a one-dimensional output ndarray, and a zero-dimensional ndarray containing the initial sum. | ||
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| </section> | ||
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| <!-- /.usage --> | ||
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| <section class="notes"> | ||
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| ## Notes | ||
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| - If provided an empty one-dimensional input ndarray, the function returns the output ndarray unchanged. | ||
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| </section> | ||
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| <!-- /.notes --> | ||
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| <section class="examples"> | ||
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| ## Examples | ||
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| <!-- eslint no-undef: "error" --> | ||
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| ```javascript | ||
| var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); | ||
| var ndarray = require( '@stdlib/ndarray/base/ctor' ); | ||
| var zerosLike = require( '@stdlib/ndarray/zeros-like' ); | ||
| var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); | ||
| var ndarray2array = require( '@stdlib/ndarray/to-array' ); | ||
| var dcusumkbn = require( '@stdlib/blas/ext/base/ndarray/dcusumkbn' ); | ||
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| var xbuf = discreteUniform( 10, -50, 50, { | ||
| 'dtype': 'float64' | ||
| }); | ||
| var x = new ndarray( 'float64', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); | ||
| console.log( ndarray2array( x ) ); | ||
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| var y = zerosLike( x ); | ||
| console.log( ndarray2array( y ) ); | ||
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| var initial = scalar2ndarray( 100.0, { | ||
| 'dtype': 'float64' | ||
| }); | ||
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| var v = dcusumkbn( [ x, y, initial ] ); | ||
| console.log( ndarray2array( v ) ); | ||
| ``` | ||
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| </section> | ||
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| <!-- /.examples --> | ||
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| <section class="references"> | ||
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| ## References | ||
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| - Klein, Andreas. 2005. "A Generalized Kahan-Babuška-Summation-Algorithm." _Computing_ 76 (3): 279–93. doi:[10.1007/s00607-005-0139-x][@klein:2005a]. | ||
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| </section> | ||
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| <!-- /.references --> | ||
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| <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. --> | ||
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| <section class="related"> | ||
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| </section> | ||
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| <!-- /.related --> | ||
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| <!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. --> | ||
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| <section class="links"> | ||
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| [@klein:2005a]: https://doi.org/10.1007/s00607-005-0139-x | ||
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| </section> | ||
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| <!-- /.links --> | ||
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112
lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn/benchmark/benchmark.js
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| /** | ||
| * @license Apache-2.0 | ||
| * | ||
| * Copyright (c) 2025 The Stdlib Authors. | ||
| * | ||
| * Licensed under the Apache License, Version 2.0 (the "License"); | ||
| * you may not use this file except in compliance with the License. | ||
| * You may obtain a copy of the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| */ | ||
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| 'use strict'; | ||
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| // MODULES // | ||
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| var bench = require( '@stdlib/bench' ); | ||
| var uniform = require( '@stdlib/random/array/uniform' ); | ||
| var zeros = require( '@stdlib/array/zeros' ); | ||
| var isnan = require( '@stdlib/math/base/assert/is-nan' ); | ||
| var pow = require( '@stdlib/math/base/special/pow' ); | ||
| var ndarray = require( '@stdlib/ndarray/base/ctor' ); | ||
| var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); | ||
| var pkg = require( './../package.json' ).name; | ||
| var dcusumkbn = require( './../lib' ); | ||
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| // VARIABLES // | ||
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| var options = { | ||
| 'dtype': 'float64' | ||
| }; | ||
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| // FUNCTIONS // | ||
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| /** | ||
| * Creates a benchmark function. | ||
| * | ||
| * @private | ||
| * @param {PositiveInteger} len - array length | ||
| * @returns {Function} benchmark function | ||
| */ | ||
| function createBenchmark( len ) { | ||
| var initial; | ||
| var xbuf; | ||
| var ybuf; | ||
| var x; | ||
| var y; | ||
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| xbuf = uniform( len, -10.0, 10.0, options ); | ||
| x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); | ||
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| initial = scalar2ndarray( 0.0, options.dtype, 'row-major' ); | ||
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| ybuf = zeros( len, options.dtype ); | ||
| y = new ndarray( options.dtype, ybuf, [ len ], [ 1 ], 0, 'row-major' ); | ||
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| return benchmark; | ||
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| function benchmark( b ) { | ||
| var v; | ||
| var i; | ||
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| b.tic(); | ||
| for ( i = 0; i < b.iterations; i++ ) { | ||
| v = dcusumkbn( [ x, y, initial ] ); | ||
| if ( typeof v !== 'object' ) { | ||
| b.fail( 'should return an ndarray' ); | ||
| } | ||
| } | ||
| b.toc(); | ||
| if ( isnan( v.get( i%len ) ) ) { | ||
| b.fail( 'should not return NaN' ); | ||
| } | ||
| b.pass( 'benchmark finished' ); | ||
| b.end(); | ||
| } | ||
| } | ||
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| // MAIN // | ||
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| /** | ||
| * Main execution sequence. | ||
| * | ||
| * @private | ||
| */ | ||
| function main() { | ||
| var len; | ||
| var min; | ||
| var max; | ||
| var f; | ||
| var i; | ||
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| min = 1; // 10^min | ||
| max = 6; // 10^max | ||
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| for ( i = min; i <= max; i++ ) { | ||
| len = pow( 10, i ); | ||
| f = createBenchmark( len ); | ||
| bench( pkg + ':len=' + len, f ); | ||
| } | ||
| } | ||
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| main(); |
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39
lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn/docs/repl.txt
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| {{alias}}( arrays ) | ||
| Computes the cumulative sum of a one-dimensional double-precision floating- | ||
| point ndarray using an improved Kahan–Babuška algorithm. | ||
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| If provided an empty input ndarray, the function returns the output ndarray | ||
| unchanged. | ||
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| Parameters | ||
| ---------- | ||
| arrays: ArrayLikeObject<ndarray> | ||
| Array-like object containing a one-dimensional input ndarray, a one- | ||
| dimensional output ndarray, and a zero-dimensional ndarray containing | ||
| the initial sum. | ||
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| Returns | ||
| ------- | ||
| out: ndarray | ||
| Output ndarray. | ||
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| Examples | ||
| -------- | ||
| > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] ); | ||
| > var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0 ] ); | ||
| > var dt = 'float64'; | ||
| > var sh = [ xbuf.length ]; | ||
| > var st = [ 1 ]; | ||
| > var oo = 0; | ||
| > var ord = 'row-major'; | ||
| > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, st, oo, ord ); | ||
| > var y = new {{alias:@stdlib/ndarray/ctor}}( dt, ybuf, sh, st, oo, ord ); | ||
| > var s = {{alias:@stdlib/ndarray/from-scalar}}( 0.0, { 'dtype': dt } ); | ||
| > {{alias}}( [ x, y, s ] ); | ||
| > {{alias:@stdlib/ndarray/to-array}}( y ) | ||
| [ 1.0, -1.0, 1.0 ] | ||
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| See Also | ||
| -------- | ||
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59
lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn/docs/types/index.d.ts
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| /* | ||
| * @license Apache-2.0 | ||
| * | ||
| * Copyright (c) 2025 The Stdlib Authors. | ||
| * | ||
| * Licensed under the Apache License, Version 2.0 (the "License"); | ||
| * you may not use this file except in compliance with the License. | ||
| * You may obtain a copy of the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| */ | ||
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| // TypeScript Version: 4.1 | ||
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| /// <reference types="@stdlib/types"/> | ||
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| import { float64ndarray } from '@stdlib/types/ndarray'; | ||
|
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| /** | ||
| * Computes the cumulative sum of a one-dimensional double-precision floating-point ndarray using an improved Kahan–Babuška algorithm. | ||
| * | ||
| * @param arrays - array-like object containing an input ndarray, an output ndarray, and an ndarray containing the initial sum | ||
| * @returns output ndarray | ||
| * | ||
| * @example | ||
| * var Float64Array = require( '@stdlib/array/float64' ); | ||
| * var ndarray2array = require( '@stdlib/ndarray/to-array' ); | ||
| * var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' ); | ||
| * var ndarray = require( '@stdlib/ndarray/base/ctor' ); | ||
| * | ||
| * var xbuf = new Float64Array( [ 1.0, 3.0, 4.0, 2.0 ] ); | ||
| * var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); | ||
| * | ||
| * var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); | ||
| * var y = new ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' ); | ||
| * | ||
| * var initial = scalar2ndarray( 0.0, 'float64', 'row-major' ); | ||
| * | ||
| * var v = dcusumkbn( [ x, y, initial ] ); | ||
| * // returns <ndarray> | ||
| * | ||
| * var bool = ( v === y ); | ||
| * // returns true | ||
| * | ||
| * var arr = ndarray2array( v ); | ||
| * // returns [ 1.0, 4.0, 8.0, 10.0 ] | ||
| */ | ||
| declare function dcusumkbn( arrays: [ float64ndarray, float64ndarray, float64ndarray ] ): float64ndarray; | ||
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| // EXPORTS // | ||
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| export = dcusumkbn; |
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