feat: add blas/ext/base/ndarray/dcusumors

lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumors/README.md

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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.
+
+-->
+
+# dcusumors
+
+> Compute the cumulative sum of a one-dimensional double-precision floating-point ndarray using ordinary recursive summation.
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var dcusumors = require( '@stdlib/blas/ext/base/ndarray/dcusumors' );
+```
+
+#### dcusumors( arrays )
+
+Computes the cumulative sum of a one-dimensional double-precision floating-point ndarray using ordinary recursive summation.
+
+```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' );
+
+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 = dcusumors( [ x, y, initial ] );
+// returns <ndarray>
+
+var bool = ( v === y );
+// returns true
+
+var arr = ndarray2array( v );
+// returns [ 1.0, 4.0, 8.0, 10.0 ]
+```
+
+The function has the following parameters:
+
+-   **arrays**: array-like object containing a one-dimensional input ndarray, a one-dimensional output ndarray, and a zero-dimensional ndarray containing the initial sum.
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   If provided an empty one-dimensional input ndarray, the function returns the output ndarray unchanged.
+-   Ordinary recursive summation (i.e., a "simple" sum) is performant, but can incur significant numerical error. If performance is paramount and error tolerated, using ordinary recursive summation is acceptable; in all other cases, exercise due caution.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```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 dcusumors = require( '@stdlib/blas/ext/base/ndarray/dcusumors' );
+
+var xbuf = discreteUniform( 10, -50, 50, {
+    'dtype': 'float64'
+});
+var x = new ndarray( 'float64', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var y = zerosLike( x );
+console.log( ndarray2array( y ) );
+
+var initial = scalar2ndarray( 100.0, {
+    'dtype': 'float64'
+});
+
+var v = dcusumors( [ x, y, initial ] );
+console.log( ndarray2array( v ) );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+</section>
+
+<!-- /.links -->

lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumors/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.
+*/
+
+'use strict';
+
+// MODULES //
+
+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 dcusumors = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* 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;
+
+	xbuf = uniform( len, -10.0, 10.0, options );
+	x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' );
+
+	initial = scalar2ndarray( 0.0, options.dtype, 'row-major' );
+
+	ybuf = zeros( len, options.dtype );
+	y = new ndarray( options.dtype, ybuf, [ len ], [ 1 ], 0, 'row-major' );
+
+	return benchmark;
+
+	function benchmark( b ) {
+		var v;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			v = dcusumors( [ 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();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( pkg+':len='+len, f );
+	}
+}
+
+main();

lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumors/docs/repl.txt

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+
+{{alias}}( arrays )
+    Computes the cumulative sum of a one-dimensional double-precision floating-
+    point ndarray using ordinary recursive summation.
+
+    If provided an empty input ndarray, the function returns the output ndarray
+    unchanged.
+
+    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.
+
+    Returns
+    -------
+    out: ndarray
+        Output ndarray.
+
+    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 ]
+
+    See Also
+    --------
+

lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumors/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.
+*/
+
+// TypeScript Version: 4.1
+
+/// <reference types="@stdlib/types"/>
+
+import { float64ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Computes the cumulative sum of a one-dimensional double-precision floating-point ndarray using ordinary recursive summation.
+*
+* @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 = dcusumors( [ 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 dcusumors( arrays: [ float64ndarray, float64ndarray, float64ndarray ] ): float64ndarray;
+
+
+// EXPORTS //
+
+export = dcusumors;