@stdlib/math-tools-unary

Multiple dispatch for unary mathematical functions.

https://github.com/stdlib-js/math-tools-unary

Science Score: 44.0%

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dispatch javascript math mathematics multimethod multimethods multiple ndarray node node-js nodejs stdlib tools unary

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Repository

Multiple dispatch for unary mathematical functions.

Basic Info

Host: GitHub
Owner: stdlib-js
License: apache-2.0
Language: JavaScript
Default Branch: main
Homepage: https://github.com/stdlib-js/stdlib
Size: 3.54 MB

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dispatch javascript math mathematics multimethod multimethods multiple ndarray node node-js nodejs stdlib tools unary

Created over 4 years ago · Last pushed 11 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!

Unary

$NPM version$ $Build Status$ $Coverage Status$

Multiple dispatch for unary mathematical functions.

## Installation ```bash npm install @stdlib/math-tools-unary ``` 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 dispatch = require( '@stdlib/math-tools-unary' ); ``` #### dispatch( table ) Returns a function which dispatches to specified functions based on input argument types. ```javascript var nabs = require( '@stdlib/math-base-special-abs' ); var dabs = require( '@stdlib/math-strided-special-dabs' ); var sabs = require( '@stdlib/math-strided-special-sabs' ); var gabs = require( '@stdlib/math-strided-special-abs' ); var table = { 'scalar': [ 'number', nabs ], 'array': [ 'float64', dabs, 'float32', sabs, 'generic', gabs ], 'ndarray': [ 'float64', dabs.ndarray, 'float32', sabs.ndarray, 'generic', gabs.ndarray ] }; var abs = dispatch( table ); ``` The function accepts the following arguments: - **table**: resolution table object which maps input argument types to corresponding implementations. A `table` resolution object may contain one or more of the following fields: - **scalar**: strided look-up table for scalar arguments. Implementation functions must accept a single input argument: a scalar value. Supported data types: `'number'` and `'complex'`. - **array**: strided look-up table for array-like object arguments. Implementation functions must follow strided array interface argument conventions: ```text fcn( N, x, strideX, y, strideY ) ``` where - **N**: number of indexed elements. - **x**: input strided array. - **strideX**: index increment for `x`. - **y**: destination strided array. - **strideY**: index increment for `y`. Supported array data types consist of all supported [ndarray][@stdlib/ndarray/dtypes] data types. - **ndarray**: strided look-up table for [`ndarray`][@stdlib/ndarray/ctor] arguments. Implementation functions must follow strided array ndarray interface argument conventions: ```text fcn( N, x, strideX, offsetX, y, strideY, offsetY ) ``` where - **N**: number of indexed elements. - **x**: input strided array (i.e., underlying input [`ndarray`][@stdlib/ndarray/ctor] buffer). - **strideX**: index increment for `x`. - **offsetX**: starting index for `x`. - **y**: destination strided array (i.e., underlying output [`ndarray`][@stdlib/ndarray/ctor] buffer). - **strideY**: index increment for `y`. - **offsetY**: starting index for `y`. Supported data types consist of all supported [ndarray][@stdlib/ndarray/dtypes] data types. Each strided look-up table should be comprised as follows: ```text [ , , , , ... ] ``` If an argument's data type is **not** found in the argument's corresponding look-up table and if a `'generic'` data type is present in that same table, the returned dispatch function will resolve the "generic" implementation. In other words, an implementation associated with a `'generic'` data type will be treated as the default implementation. If unable to resolve an implementation for a provided argument data type, the returned function throws an error. * * * #### dispatcher( x ) Dispatches to an underlying implementation based the data type of `x`. ```javascript var nabs = require( '@stdlib/math-base-special-abs' ); var dabs = require( '@stdlib/math-strided-special-dabs' ); var sabs = require( '@stdlib/math-strided-special-sabs' ); var gabs = require( '@stdlib/math-strided-special-abs' ); var table = { 'scalar': [ 'number', nabs ], 'array': [ 'float64', dabs, 'float32', sabs, 'generic', gabs ], 'ndarray': [ 'float64', dabs.ndarray, 'float32', sabs.ndarray, 'generic', gabs.ndarray ] }; var abs = dispatch( table ); var y = abs( -1.0 ); // returns 1.0 ``` The returned dispatch function accepts the following arguments: - **x**: input [`ndarray`][@stdlib/ndarray/ctor], array-like object, or number. If provided an [`ndarray`][@stdlib/ndarray/ctor] or array-like object, the function performs element-wise computation. If provided an [`ndarray`][@stdlib/ndarray/ctor], the function returns an [`ndarray`][@stdlib/ndarray/ctor] having the same shape and data type as `x`. ```javascript var dabs = require( '@stdlib/math-strided-special-dabs' ); var sabs = require( '@stdlib/math-strided-special-sabs' ); var gabs = require( '@stdlib/math-strided-special-abs' ); var array = require( '@stdlib/ndarray-array' ); var table = { 'ndarray': [ 'float64', dabs.ndarray, 'float32', sabs.ndarray, 'generic', gabs.ndarray ] }; var abs = dispatch( table ); var x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] ); // 2x2 var y = abs( x ); // returns var v = y.get( 0, 1 ); // returns 2.0 ``` If provided an array-like object, the function returns an array-like object having the same length and data type as `x`. ```javascript var dabs = require( '@stdlib/math-strided-special-dabs' ); var sabs = require( '@stdlib/math-strided-special-sabs' ); var gabs = require( '@stdlib/math-strided-special-abs' ); var Float64Array = require( '@stdlib/array-float64' ); var table = { 'array': [ 'float64', dabs, 'float32', sabs, 'generic', gabs ] }; var abs = dispatch( table ); var x = new Float64Array( [ -1.0, -2.0 ] ); var y = abs( x ); // returns [ 1.0, 2.0 ] ```

## Examples ```javascript var nabs = require( '@stdlib/math-base-special-abs' ); var dabs = require( '@stdlib/math-strided-special-dabs' ); var sabs = require( '@stdlib/math-strided-special-sabs' ); var gabs = require( '@stdlib/math-strided-special-abs' ); var Float64Array = require( '@stdlib/array-float64' ); var array = require( '@stdlib/ndarray-array' ); var ind2sub = require( '@stdlib/ndarray-ind2sub' ); var dispatch = require( '@stdlib/math-tools-unary' ); var table; var sub; var abs; var sh; var x; var y; var i; // Define a table for resolving unary functions based on argument data types: table = { 'scalar': [ 'number', nabs ], 'array': [ 'float64', dabs, 'float32', sabs, 'generic', gabs ], 'ndarray': [ 'float64', dabs.ndarray, 'float32', sabs.ndarray, 'generic', gabs.ndarray ] }; // Create a function which dispatches based on argument data types: abs = dispatch( table ); // Provide a number... y = abs( -1.0 ); console.log( 'x = %d => abs(x) = %d', -1.0, y ); // Provide an array-like object... x = new Float64Array( [ -1.0, -2.0, -3.0 ] ); y = abs( x ); for ( i = 0; i < x.length; i++ ) { console.log( 'x_%d = %d => abs(x_%d) = %d', i, x[ i ], i, y[ i ] ); } // Provide an ndarray... x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] ); sh = x.shape; y = abs( x ); for ( i = 0; i < x.length; i++ ) { sub = ind2sub( sh, i ); console.log( 'x_%d%d = %d => abs(x_%d%d) = %d', sub[ 0 ], sub[ 1 ], x.iget( i ), sub[ 0 ], sub[ 1 ], y.iget( i ) ); } ```

* * * ## 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
  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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npmjs.org: @stdlib/math-tools-unary

Multiple dispatch for unary mathematical functions.

Homepage: https://stdlib.io
License: Apache-2.0
Latest release: 0.2.2
published over 1 year ago

Versions: 10
Dependent Packages: 5
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Downloads: 26 Last month

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@stdlib/math-tools-unary

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