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ndarray-base-unary-reduce-subarray

Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.

https://github.com/stdlib-js/ndarray-base-unary-reduce-subarray

Science Score: 44.0%

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accumulate accumulation array base javascript ndarray node node-js nodejs reduce reduction stdlib strided subarray unary
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Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.

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accumulate accumulation array base javascript ndarray node node-js nodejs reduce reduction stdlib strided subarray unary
Created 9 months ago · Last pushed 5 months ago
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README.md

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unaryReduceSubarray

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Perform a reduction over a list of specified dimensions in an input ndarray and assign results to a provided output ndarray.

## Installation ```bash npm install @stdlib/ndarray-base-unary-reduce-subarray ``` 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 unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); ``` #### unaryReduceSubarray( fcn, arrays, dims\[, options] ) Performs a reduction over a list of specified dimensions in an input ndarray and assigns results to a provided output ndarray. ```javascript var Float64Array = require( '@stdlib/array-float64' ); var filled = require( '@stdlib/array-base-filled' ); var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); var every = require( '@stdlib/ndarray-base-every' ); // Create data buffers: var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); var ybuf = filled( false, 3 ); // Define the array shapes: var xsh = [ 1, 3, 2, 2 ]; var ysh = [ 1, 3 ]; // Define the array strides: var sx = [ 12, 4, 2, 1 ]; var sy = [ 3, 1 ]; // Define the index offsets: var ox = 0; var oy = 0; // Create an input ndarray-like object: var x = { 'dtype': 'float64', 'data': xbuf, 'shape': xsh, 'strides': sx, 'offset': ox, 'order': 'row-major' }; // Create an output ndarray-like object: var y = { 'dtype': 'generic', 'data': ybuf, 'shape': ysh, 'strides': sy, 'offset': oy, 'order': 'row-major' }; // Perform a reduction: unaryReduceSubarray( every, [ x, y ], [ 2, 3 ] ); var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ); // returns [ [ true, false, true ] ] ``` The function accepts the following arguments: - **fcn**: function which will be applied to a subarray and should reduce the subarray to a single scalar value. - **arrays**: array-like object containing one input ndarray and one output ndarray, followed by any additional ndarray arguments. - **dims**: list of dimensions over which to perform a reduction. - **options**: function options which are passed through to `fcn` (_optional_). Each provided ndarray should be an object with the following properties: - **dtype**: data type. - **data**: data buffer. - **shape**: dimensions. - **strides**: stride lengths. - **offset**: index offset. - **order**: specifies whether an ndarray is row-major (C-style) or column major (Fortran-style). #### TODO: document factory method
## Notes - The output ndarray and any additional ndarray arguments are expected to have the same dimensions as the non-reduced dimensions of the input ndarray. When calling the reduction function, any additional ndarray arguments are provided as zero-dimensional ndarray-like objects. - The reduction function is expected to have the following signature: ```text fcn( arrays[, options] ) ``` where - **arrays**: array containing a subarray of the input ndarray and any additional ndarray arguments as zero-dimensional ndarrays. - **options**: function options (_optional_). - For very high-dimensional ndarrays which are non-contiguous, one should consider copying the underlying data to contiguous memory before performing a reduction in order to achieve better performance.
## Examples ```javascript var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); var filled = require( '@stdlib/array-base-filled' ); var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); var every = require( '@stdlib/ndarray-base-every' ); var unaryReduceSubarray = require( '@stdlib/ndarray-base-unary-reduce-subarray' ); var N = 10; var x = { 'dtype': 'generic', 'data': discreteUniform( N, -5, 5, { 'dtype': 'generic' }), 'shape': [ 1, 5, 2 ], 'strides': [ 10, 2, 1 ], 'offset': 0, 'order': 'row-major' }; var y = { 'dtype': 'generic', 'data': filled( false, 2 ), 'shape': [ 1, 2 ], 'strides': [ 2, 1 ], 'offset': 0, 'order': 'row-major' }; unaryReduceSubarray( every, [ x, y ], [ 1 ] ); console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) ); ```
* * * ## 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] --- ## Copyright Copyright © 2016-2025. The Stdlib [Authors][stdlib-authors].

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