blas-ext-sum

Compute the sum along one or more ndarray dimensions.

https://github.com/stdlib-js/blas-ext-sum

Science Score: 44.0%

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Keywords

blas extended javascript math mathematics ndarray node node-js nodejs statistics stats stdlib sum summation total

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Compute the sum along one or more ndarray dimensions.

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Host: GitHub
Owner: stdlib-js
License: apache-2.0
Language: JavaScript
Default Branch: main
Homepage: https://github.com/stdlib-js/stdlib
Size: 4.53 MB

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blas extended javascript math mathematics ndarray node node-js nodejs statistics stats stdlib sum summation total

Created 10 months ago · Last pushed 8 months ago

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Readme Changelog Contributing License Code of conduct Citation Security

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

sum

Compute the sum along one or more ndarray dimensions.

## Installation ```bash npm install @stdlib/blas-ext-sum ``` Alternatively, - To load the package in a website via a `script` tag without installation and bundlers, use the [ES Module][es-module] available on the [`esm`][esm-url] branch (see [README][esm-readme]). - If you are using Deno, visit the [`deno`][deno-url] branch (see [README][deno-readme] for usage intructions). - For use in Observable, or in browser/node environments, use the [Universal Module Definition (UMD)][umd] build available on the [`umd`][umd-url] branch (see [README][umd-readme]). The [branches.md][branches-url] file summarizes the available branches and displays a diagram illustrating their relationships. To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

## Usage ```javascript var sum = require( '@stdlib/blas-ext-sum' ); ``` #### sum( x\[, options] ) Computes the sum along one or more [ndarray][@stdlib/ndarray/ctor] dimensions. ```javascript var array = require( '@stdlib/ndarray-array' ); var x = array( [ -1.0, 2.0, -3.0 ] ); var y = sum( x ); // returns var v = y.get(); // returns -2.0 ``` The function has the following parameters: - **x**: input [ndarray][@stdlib/ndarray/ctor]. Must have a numeric or "generic" [data type][@stdlib/ndarray/dtypes]. - **options**: function options (_optional_). The function accepts the following options: - **dims**: list of dimensions over which to perform a reduction. If not provided, the function performs a reduction over all elements in a provided input [ndarray][@stdlib/ndarray/ctor]. - **dtype**: output ndarray [data type][@stdlib/ndarray/dtypes]. Must be a numeric or "generic" [data type][@stdlib/ndarray/dtypes]. - **keepdims**: boolean indicating whether the reduced dimensions should be included in the returned [ndarray][@stdlib/ndarray/ctor] as singleton dimensions. Default: `false`. By default, the function performs a reduction over all elements in a provided input [ndarray][@stdlib/ndarray/ctor]. To perform a reduction over specific dimensions, provide a `dims` option. ```javascript var ndarray2array = require( '@stdlib/ndarray-to-array' ); var array = require( '@stdlib/ndarray-array' ); var x = array( [ -1.0, 2.0, -3.0, 4.0 ], { 'shape': [ 2, 2 ], 'order': 'row-major' }); var v = ndarray2array( x ); // returns [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ] var y = sum( x, { 'dims': [ 0 ] }); // returns v = ndarray2array( y ); // returns [ -4.0, 6.0 ] y = sum( x, { 'dims': [ 1 ] }); // returns v = ndarray2array( y ); // returns [ 1.0, 1.0 ] y = sum( x, { 'dims': [ 0, 1 ] }); // returns v = y.get(); // returns 2.0 ``` By default, the function excludes reduced dimensions from the output [ndarray][@stdlib/ndarray/ctor]. To include the reduced dimensions as singleton dimensions, set the `keepdims` option to `true`. ```javascript var ndarray2array = require( '@stdlib/ndarray-to-array' ); var array = require( '@stdlib/ndarray-array' ); var x = array( [ -1.0, 2.0, -3.0, 4.0 ], { 'shape': [ 2, 2 ], 'order': 'row-major' }); var v = ndarray2array( x ); // returns [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ] var y = sum( x, { 'dims': [ 0 ], 'keepdims': true }); // returns v = ndarray2array( y ); // returns [ [ -4.0, 6.0 ] ] y = sum( x, { 'dims': [ 1 ], 'keepdims': true }); // returns v = ndarray2array( y ); // returns [ [ 1.0 ], [ 1.0 ] ] y = sum( x, { 'dims': [ 0, 1 ], 'keepdims': true }); // returns v = ndarray2array( y ); // returns [ [ 2.0 ] ] ``` By default, the function returns an [ndarray][@stdlib/ndarray/ctor] having a [data type][@stdlib/ndarray/dtypes] determined by the function's output data type [policy][@stdlib/ndarray/output-dtype-policies]. To override the default behavior, set the `dtype` option. ```javascript var getDType = require( '@stdlib/ndarray-dtype' ); var array = require( '@stdlib/ndarray-array' ); var x = array( [ -1.0, 2.0, -3.0 ], { 'dtype': 'generic' }); var y = sum( x, { 'dtype': 'float64' }); // returns var dt = getDType( y ); // returns 'float64' ``` #### sum.assign( x, out\[, options] ) Computes the sum along one or more [ndarray][@stdlib/ndarray/ctor] dimensions and assigns results to a provided output [ndarray][@stdlib/ndarray/ctor]. ```javascript var array = require( '@stdlib/ndarray-array' ); var zeros = require( '@stdlib/ndarray-zeros' ); var x = array( [ -1.0, 2.0, -3.0 ] ); var y = zeros( [] ); var out = sum.assign( x, y ); // returns var v = out.get(); // returns -2.0 var bool = ( out === y ); // returns true ``` The method has the following parameters: - **x**: input [ndarray][@stdlib/ndarray/ctor]. Must have a numeric or generic [data type][@stdlib/ndarray/dtypes]. - **out**: output [ndarray][@stdlib/ndarray/ctor]. - **options**: function options (_optional_). The method accepts the following options: - **dims**: list of dimensions over which to perform a reduction. If not provided, the function performs a reduction over all elements in a provided input [ndarray][@stdlib/ndarray/ctor].

## Notes - Setting the `keepdims` option to `true` can be useful when wanting to ensure that the output [ndarray][@stdlib/ndarray/ctor] is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with ndarrays having the same shape as the input [ndarray][@stdlib/ndarray/ctor]. - The output data type [policy][@stdlib/ndarray/output-dtype-policies] only applies to the main function and specifies that, by default, in order to avoid issues arising from integer overflow, the function must return an [ndarray][@stdlib/ndarray/ctor] having a [data type][@stdlib/ndarray/dtypes] amenable to accumulation. This means that, for integer data types having small value ranges (e.g., `int8`, `uint8`, etc), the main function returns an [ndarray][@stdlib/ndarray/ctor] having at least a 32-bit integer data type. By default, if an input [ndarray][@stdlib/ndarray/ctor] has a floating-point data type, the main function returns an [ndarray][@stdlib/ndarray/ctor] having the same data type. For the `assign` method, the output [ndarray][@stdlib/ndarray/ctor] is allowed to have any supported output [data type][@stdlib/ndarray/dtypes]. - When summing a large number of lower precision floating-point numbers (e.g., as found in an [ndarray][@stdlib/ndarray/ctor] having a `'float32'` data type), the accumulated numerical error can become significant. In such cases, casting the input [ndarray][@stdlib/ndarray/ctor] to a higher precision floating-point data type, such as `'float64'`, prior to computation is advisable.

## Examples ```javascript var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); var getDType = require( '@stdlib/ndarray-dtype' ); var ndarray2array = require( '@stdlib/ndarray-to-array' ); var ndarray = require( '@stdlib/ndarray-ctor' ); var sum = require( '@stdlib/blas-ext-sum' ); // Generate an array of random numbers: var xbuf = discreteUniform( 25, 0, 20, { 'dtype': 'generic' }); // Wrap in an ndarray: var x = new ndarray( 'generic', xbuf, [ 5, 5 ], [ 5, 1 ], 0, 'row-major' ); console.log( ndarray2array( x ) ); // Perform a reduction: var y = sum( x, { 'dims': [ 0 ] }); // Resolve the output array data type: var dt = getDType( y ); console.log( dt ); // Print the results: console.log( ndarray2array( y ) ); ```

* * * ## Notice This package is part of [stdlib][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][stdlib], see the main project [repository][stdlib]. #### Community [![Chat][chat-image]][chat-url] --- ## License See [LICENSE][stdlib-license]. ## Copyright Copyright © 2016-2025. The Stdlib [Authors][stdlib-authors].

Owner

Name: stdlib
Login: stdlib-js
Kind: organization

Website: https://stdlib.io
Twitter: stdlibjs
Repositories: 3,692
Profile: https://github.com/stdlib-js

Standard library for JavaScript.

Citation (CITATION.cff)

cff-version: 1.2.0
title: stdlib
message: >-
  If you use this software, please cite it using the
  metadata from this file.

type: software

authors:
  - name: The Stdlib Authors
    url: https://github.com/stdlib-js/stdlib/graphs/contributors

repository-code: https://github.com/stdlib-js/stdlib
url: https://stdlib.io

abstract: |
  Standard library for JavaScript and Node.js.

keywords:
  - JavaScript
  - Node.js
  - TypeScript
  - standard library
  - scientific computing
  - numerical computing
  - statistical computing

license: Apache-2.0 AND BSL-1.0

date-released: 2016

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package.json npm

@stdlib/array-zeros ^0.2.2 development
@stdlib/assert-is-method ^0.2.2 development
@stdlib/assert-is-ndarray-like ^0.2.2 development
@stdlib/bench-harness ^0.2.2 development
@stdlib/math-base-assert-is-nan ^0.2.2 development
@stdlib/math-base-special-pow ^0.3.0 development
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@stdlib/ndarray-ctor ^0.2.2 development
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@stdlib/ndarray-empty ^0.3.0 development
@stdlib/ndarray-empty-like ^0.3.0 development
@stdlib/ndarray-order ^0.2.2 development
@stdlib/ndarray-shape ^0.2.2 development
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@stdlib/ndarray-zeros ^0.3.0 development
@stdlib/random-array-discrete-uniform ^0.2.1 development
@stdlib/random-array-uniform ^0.2.1 development
istanbul ^0.4.1 development
tap-min git+https://github.com/Planeshifter/tap-min.git development
tape git+https://github.com/kgryte/tape.git#fix/globby development
@stdlib/blas-ext-base-ndarray-dsum github:stdlib-js/blas-ext-base-ndarray-dsum#main
@stdlib/blas-ext-base-ndarray-gsum github:stdlib-js/blas-ext-base-ndarray-gsum#main
@stdlib/blas-ext-base-ndarray-ssum github:stdlib-js/blas-ext-base-ndarray-ssum#main
@stdlib/ndarray-base-unary-reduce-strided1d-dispatch-factory github:stdlib-js/ndarray-base-unary-reduce-strided1d-dispatch-factory#main
@stdlib/ndarray-dtypes ^0.3.0
@stdlib/types ^0.4.3

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