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feat: add blas/ext/base/ndarray/dcusum
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‎lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusum/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");
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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# dcusum
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> Compute the cumulative sum of a one-dimensional double-precision floating-point ndarray.
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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
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var dcusum = require( '@stdlib/blas/ext/base/ndarray/dcusum' );
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```
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#### dcusum( arrays )
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Computes the cumulative sum of a one-dimensional double-precision floating-point ndarray.
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```javascript
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var Float64Array = require( '@stdlib/array/float64' );
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var ndarray2array = require( '@stdlib/ndarray/to-array' );
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var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' );
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var ndarray = require( '@stdlib/ndarray/base/ctor' );
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var xbuf = new Float64Array( [ 1.0, 3.0, 4.0, 2.0 ] );
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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 ] );
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var y = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
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var initial = scalar2ndarray( 0.0, 'float64', 'row-major' );
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var v = dcusum( [ x, y, initial ] );
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// returns <ndarray>
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var bool = ( v === y );
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// returns true
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var arr = ndarray2array( v );
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// returns [ 1.0, 4.0, 8.0, 10.0 ]
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```
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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
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var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
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var ndarray = require( '@stdlib/ndarray/base/ctor' );
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var zerosLike = require( '@stdlib/ndarray/zeros-like' );
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var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
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var ndarray2array = require( '@stdlib/ndarray/to-array' );
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var dcusum = require( '@stdlib/blas/ext/base/ndarray/dcusum' );
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var xbuf = discreteUniform( 10, -50, 50, {
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'dtype': 'float64'
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});
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var x = new ndarray( 'float64', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
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console.log( ndarray2array( x ) );
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var y = zerosLike( x );
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console.log( ndarray2array( y ) );
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var initial = scalar2ndarray( 100.0, {
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'dtype': 'float64'
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});
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var v = dcusum( [ x, y, initial ] );
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console.log( ndarray2array( v ) );
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```
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</section>
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<!-- /.examples -->
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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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</section>
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<!-- /.links -->

‎lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusum/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 zeros = require( '@stdlib/array/zeros' );
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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 ndarray = require( '@stdlib/ndarray/base/ctor' );
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var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' );
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var pkg = require( './../package.json' ).name;
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var dcusum = require( './../lib' );
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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 initial;
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var xbuf;
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var ybuf;
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var x;
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var y;
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xbuf = uniform( len, -10.0, 10.0, options );
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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 );
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y = new ndarray( options.dtype, ybuf, [ len ], [ 1 ], 0, 'row-major' );
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return benchmark;
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function benchmark( b ) {
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var v;
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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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v = dcusum( [ x, y, initial ] );
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if ( typeof v !== 'object' ) {
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b.fail( 'should return an ndarray' );
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}
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}
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b.toc();
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if ( isnan( v.get( i%len ) ) ) {
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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/blas/ext/base/ndarray/dcusum/docs/repl.txt

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{{alias}}( arrays )
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Computes the cumulative sum of a one-dimensional double-precision floating-
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point ndarray.
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If provided an empty input ndarray, the function returns the output ndarray
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unchanged.
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Parameters
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----------
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arrays: ArrayLikeObject<ndarray>
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Array-like object containing a one-dimensional input ndarray, a one-
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dimensional output ndarray, and zero-dimensional ndarray containing the
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initial sum.
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Returns
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-------
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out: ndarray
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Output ndarray.
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Examples
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--------
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> var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] );
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> var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0 ] );
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> var dt = 'float64';
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> var sh = [ xbuf.length ];
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> var st = [ 1 ];
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> var oo = 0;
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> var ord = 'row-major';
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> var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, st, oo, ord );
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> var y = new {{alias:@stdlib/ndarray/ctor}}( dt, ybuf, sh, st, oo, ord );
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> var s = {{alias:@stdlib/ndarray/from-scalar}}( 0.0, { 'dtype': dt } );
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> {{alias}}( [ x, y, s ] );
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> {{alias:@stdlib/ndarray/to-array}}( y )
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[ 1.0, -1.0, 1.0 ]
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See Also
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--------
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‎lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusum/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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/// <reference types="@stdlib/types"/>
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import { float64ndarray } from '@stdlib/types/ndarray';
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/**
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* Computes the cumulative sum of a one-dimensional double-precision floating-point ndarray.
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*
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* @param arrays - array-like object containing an input ndarray and an output ndarray
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* @returns output ndarray
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*
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* @example
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* var Float64Array = require( '@stdlib/array/float64' );
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* var ndarray2array = require( '@stdlib/ndarray/to-array' );
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* var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' );
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* var ndarray = require( '@stdlib/ndarray/base/ctor' );
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*
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* var xbuf = new Float64Array( [ 1.0, 3.0, 4.0, 2.0 ] );
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* var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
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*
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* var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );
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* var y = new ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );
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*
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* var initial = scalar2ndarray( 0.0, 'float64', 'row-major' );
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*
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* var v = dcusum( [ x, y, initial ] );
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* // returns <ndarray>
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*
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* var bool = ( v === y );
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* // returns true
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*
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* var arr = ndarray2array( v );
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* // returns [ 1.0, 4.0, 8.0, 10.0 ]
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*/
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declare function dcusum( arrays: [ float64ndarray, float64ndarray, float64ndarray ] ): float64ndarray;
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// EXPORTS //
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export = dcusum;

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