@stdlib/blas-ext-base-ndarray-gcusumors
v0.1.1
Published
Compute the cumulative sum of a one-dimensional ndarray using ordinary recursive summation.
Readme
gcusumors
Compute the cumulative sum of a one-dimensional ndarray using ordinary recursive summation.
Installation
npm install @stdlib/blas-ext-base-ndarray-gcusumorsUsage
var gcusumors = require( '@stdlib/blas-ext-base-ndarray-gcusumors' );gcusumors( arrays )
Computes the cumulative sum of a one-dimensional ndarray using ordinary recursive summation.
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var scalar2ndarray = require( '@stdlib/ndarray-base-from-scalar' );
var ndarray = require( '@stdlib/ndarray-base-ctor' );
var xbuf = [ 1.0, 3.0, 4.0, 2.0 ];
var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
var ybuf = [ 0.0, 0.0, 0.0, 0.0 ];
var y = new ndarray( 'generic', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );
var initial = scalar2ndarray( 0.0, 'generic', 'row-major' );
var v = gcusumors( [ 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.
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.
Examples
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 gcusumors = require( '@stdlib/blas-ext-base-ndarray-gcusumors' );
var xbuf = discreteUniform( 10, -50, 50, {
'dtype': 'generic'
});
var x = new ndarray( 'generic', 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': 'generic'
});
var v = gcusumors( [ x, y, initial ] );
console.log( ndarray2array( v ) );Notice
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
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License
See LICENSE.
Copyright
Copyright © 2016-2026. The Stdlib Authors.
