@stdlib/ndarray-base-unary-by

Apply a unary function to each element retrieved from a input ndarray according to a callback function and assign results to elements in an output ndarray.

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

Science Score: 44.0%

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Keywords

accessor apply array base foreach javascript map ndarray node node-js nodejs stdlib strided transform unary

Last synced: 6 months ago · JSON representation ·

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Apply a unary function to each element retrieved from a input ndarray according to a callback function and assign results to elements in an output ndarray.

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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: 2.41 MB

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accessor apply array base foreach javascript map ndarray node node-js nodejs stdlib strided transform unary

Created about 3 years ago · Last pushed 10 months ago

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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!

unaryBy

Apply a unary function to each element in an input ndarray according to a callback function and assign results to elements in an output ndarray.

## Installation ```bash npm install @stdlib/ndarray-base-unary-by ``` 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 unaryBy = require( '@stdlib/ndarray-base-unary-by' ); ``` #### unaryBy( arrays, fcn, clbk\[, thisArg] ) Applies a unary function to each element retrieved from an input ndarray according to a callback function and assigns results to elements in an output ndarray. ```javascript var Float64Array = require( '@stdlib/array-float64' ); function scale( x ) { return x * 10.0; } function accessor( v ) { return v * 2.0; } // Create data buffers: var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); var ybuf = new Float64Array( 6 ); // Define the shape of the input and output arrays: var shape = [ 3, 1, 2 ]; // Define the array strides: var sx = [ 4, 4, 1 ]; var sy = [ 2, 2, 1 ]; // Define the index offsets: var ox = 1; var oy = 0; // Create the input and output ndarray-like objects: var x = { 'dtype': 'float64', 'data': xbuf, 'shape': shape, 'strides': sx, 'offset': ox, 'order': 'row-major' }; var y = { 'dtype': 'float64', 'data': ybuf, 'shape': shape, 'strides': sy, 'offset': oy, 'order': 'row-major' }; // Apply the unary function: unaryBy( [ x, y ], scale, accessor ); console.log( y.data ); // => [ 40.0, 60.0, 120.0, 140.0, 200.0, 220.0 ] ``` The function accepts the following arguments: - **arrays**: array-like object containing one input ndarray and one output ndarray. - **fcn**: unary function to apply. 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). The invoked callback function is provided four arguments: - **value**: input array element. - **idx**: iteration index (zero-based). - **indices**: input and output ndarray data buffer indices `[ix, iy]`. - **arrays**: input and output ndarrays `[x, y]`. To set the callback execution context, provide a `thisArg`. ```javascript var Float64Array = require( '@stdlib/array-float64' ); function scale( x ) { return x * 10.0; } function accessor( v ) { this.count += 1; return v * 2.0; } // Create data buffers: var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); var ybuf = new Float64Array( 6 ); // Define the shape of the input and output arrays: var shape = [ 3, 1, 2 ]; // Define the array strides: var sx = [ 4, 4, 1 ]; var sy = [ 2, 2, 1 ]; // Define the index offsets: var ox = 1; var oy = 0; // Create the input and output ndarray-like objects: var x = { 'dtype': 'float64', 'data': xbuf, 'shape': shape, 'strides': sx, 'offset': ox, 'order': 'row-major' }; var y = { 'dtype': 'float64', 'data': ybuf, 'shape': shape, 'strides': sy, 'offset': oy, 'order': 'row-major' }; // Apply the unary function: var context = { 'count': 0 }; unaryBy( [ x, y ], scale, accessor, context ); var cnt = context.count; // returns 6 ```

## Notes - For very high-dimensional ndarrays which are non-contiguous, one should consider copying the underlying data to contiguous memory before applying a unary function in order to achieve better performance. - If a provided callback function does not return any value (or equivalently, explicitly returns `undefined`), the value is **ignored**. ```javascript var Float64Array = require( '@stdlib/array-float64' ); function scale( x ) { return x * 10.0; } function accessor() { // No-op... } // Create data buffers: var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); var ybuf = new Float64Array( 6 ); // Define the shape of the input and output arrays: var shape = [ 3, 1, 2 ]; // Define the array strides: var sx = [ 4, 4, 1 ]; var sy = [ 2, 2, 1 ]; // Define the index offsets: var ox = 1; var oy = 0; // Create the input and output ndarray-like objects: var x = { 'dtype': 'float64', 'data': xbuf, 'shape': shape, 'strides': sx, 'offset': ox, 'order': 'row-major' }; var y = { 'dtype': 'float64', 'data': ybuf, 'shape': shape, 'strides': sy, 'offset': oy, 'order': 'row-major' }; // Apply the unary function: unaryBy( [ x, y ], scale, accessor ); console.log( y.data ); // => [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ```

## Examples ```javascript var discreteUniform = require( '@stdlib/random-base-discrete-uniform' ).factory; var filledarray = require( '@stdlib/array-filled' ); var filledarrayBy = require( '@stdlib/array-filled-by' ); var abs = require( '@stdlib/math-base-special-abs' ); var sqrt = require( '@stdlib/math-base-special-sqrt' ); var naryFunction = require( '@stdlib/utils-nary-function' ); var shape2strides = require( '@stdlib/ndarray-base-shape2strides' ); var ndarray2array = require( '@stdlib/ndarray-base-to-array' ); var unaryBy = require( '@stdlib/ndarray-base-unary-by' ); var N = 10; var x = { 'dtype': 'generic', 'data': filledarrayBy( N, 'generic', discreteUniform( -100, 100 ) ), 'shape': [ 5, 2 ], 'strides': [ 2, 1 ], 'offset': 0, 'order': 'row-major' }; var y = { 'dtype': 'generic', 'data': filledarray( 0, N, 'generic' ), 'shape': x.shape.slice(), 'strides': shape2strides( x.shape, 'column-major' ), 'offset': 0, 'order': 'column-major' }; unaryBy( [ x, y ], sqrt, naryFunction( abs, 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] --- ## License See [LICENSE][stdlib-license]. ## Copyright Copyright © 2016-2025. The Stdlib [Authors][stdlib-authors].

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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
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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
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  - TypeScript
  - standard library
  - scientific computing
  - numerical computing
  - statistical computing

license: Apache-2.0 AND BSL-1.0

date-released: 2016

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npmjs.org: @stdlib/ndarray-base-unary-by

Apply a unary function to each element retrieved from a input ndarray according to a callback function and assign results to elements in an output ndarray.

Homepage: https://stdlib.io
License: Apache-2.0
Latest release: 0.2.1
published almost 2 years ago

Versions: 4
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Downloads: 15 Last month

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planeshifter rreusser stdlib-bot kgryte

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@stdlib/array-filled ^0.0.x development
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@stdlib/array-typed-complex-ctors ^0.0.x development
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@stdlib/ndarray-base-numel ^0.0.x
@stdlib/ndarray-base-unary-loop-interchange-order ^0.0.x
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@stdlib/ndarray-base-vind2bind ^0.0.x
@stdlib/types ^0.0.x

@stdlib/ndarray-base-unary-by

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