random-tools-unary

Constructor for creating ndarrays filled with pseudorandom numbers drawn from a single-parameter probability distribution.

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

Science Score: 44.0%

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Low similarity (16.3%) to scientific vocabulary

Keywords

array javascript math mathematics ndarray node node-js nodejs prng pseudorandom rand random rng statistics stats stdlib tools

Last synced: 6 months ago · JSON representation ·

Repository

Constructor for creating ndarrays filled with pseudorandom numbers drawn from a single-parameter probability distribution.

Basic Info

Host: GitHub
Owner: stdlib-js
License: apache-2.0
Language: JavaScript
Default Branch: main
Homepage: https://github.com/stdlib-js/stdlib
Size: 716 KB

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Stars: 0
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Topics

array javascript math mathematics ndarray node node-js nodejs prng pseudorandom rand random rng statistics stats stdlib tools

Created 10 months ago · Last pushed 9 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!

Random

Constructor for creating ndarrays filled with pseudorandom values drawn from a unary PRNG.

## Installation ```bash npm install @stdlib/random-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 Random = require( '@stdlib/random-tools-unary' ); ``` #### Random( prng, idtypes, odtypes, policies\[, options] ) Returns an interface for creating ndarrays filled with pseudorandom values drawn from a unary PRNG. ```javascript var dtypes = require( '@stdlib/ndarray-dtypes' ); var exponential = require( '@stdlib/random-base-exponential' ); var idt = dtypes( 'real_and_generic' ); var odt = dtypes( 'real_floating_point_and_generic' ); var policies = { 'output': 'real_floating_point_and_generic' }; var options = { 'order': 'row-major' }; var rand = new Random( exponential, idt, odt, policies, options ); ``` The constructor has the following parameters: - **prng**: unary pseudorandom value generator. - **idtypes**: list of supported input data types. - **odtypes**: list of supported output data types. - **policies**: interface policies. Must have the following properties: - **output**: output data type [policy][@stdlib/ndarray/policies]. - **options**: function options (_optional_). The constructor supports the following options: - **order**: default [memory layout][@stdlib/ndarray/orders]. #### Random.prototype.generate( shape, param1\[, options] ) Returns an ndarray filled with pseudorandom values drawn from a unary PRNG. ```javascript var dtypes = require( '@stdlib/ndarray-dtypes' ); var exponential = require( '@stdlib/random-base-exponential' ); var idt = dtypes( 'real_and_generic' ); var odt = dtypes( 'real_floating_point_and_generic' ); var policies = { 'output': 'real_floating_point_and_generic' }; var options = { 'order': 'row-major' }; var rand = new Random( exponential, idt, odt, policies, options ); var v = rand.generate( [ 2, 2 ], 2.0 ); // returns ``` The method has the following parameters: - **shape**: output ndarray shape. - **param1**: PRNG parameter. May be either a scalar or an ndarray. If an ndarray, must be [broadcast compatible][@stdlib/ndarray/base/broadcast-shapes] with the specified output ndarray shape. - **options**: function options (_optional_). The method accepts the following options: - **dtype**: output ndarray data type. Setting this option overrides the output data type policy. - **order**: memory layout. Setting this option overrides the default memory layout. - **mode**: specifies how to handle indices which exceed ndarray dimensions. - **submode**: specifies how to handle subscripts which exceed ndarray dimensions on a per dimension basis. - **readonly**: boolean indicating whether an ndarray should be read-only. By default, the method returns an ndarray having a data type determined by the output data type policy. To override the default behavior, set the `dtype` option. ```javascript var dtypes = require( '@stdlib/ndarray-dtypes' ); var getDType = require( '@stdlib/ndarray-dtype' ); var exponential = require( '@stdlib/random-base-exponential' ); var idt = dtypes( 'real_and_generic' ); var odt = dtypes( 'real_floating_point_and_generic' ); var policies = { 'output': 'real_floating_point_and_generic' }; var options = { 'order': 'row-major' }; var rand = new Random( exponential, idt, odt, policies, options ); var v = rand.generate( [ 2, 2 ], 2.0, { 'dtype': 'generic' }); // returns var dt = getDType( v ); // returns 'generic' ``` #### Random.prototype.assign( param1, out ) Fills an ndarray with pseudorandom values drawn from a unary PRNG. ```javascript var dtypes = require( '@stdlib/ndarray-dtypes' ); var ndzeros = require( '@stdlib/ndarray-zeros' ); var exponential = require( '@stdlib/random-base-exponential' ); var idt = dtypes( 'real_and_generic' ); var odt = dtypes( 'real_floating_point_and_generic' ); var policies = { 'output': 'real_floating_point_and_generic' }; var options = { 'order': 'row-major' }; var rand = new Random( exponential, idt, odt, policies, options ); var out = ndzeros( [ 2, 2 ] ); var v = rand.assign( 2.0, out ); // returns var bool = ( v === out ); // returns true ``` The method has the following parameters: - **param1**: PRNG parameter. May be either a scalar or an ndarray. If an ndarray, must be [broadcast compatible][@stdlib/ndarray/base/broadcast-shapes] with the output ndarray. - **out**: output ndarray.

## Notes - The output data type policy only applies to the `generate` method. For the `assign` method, the output ndarray is allowed to have any supported output data type.

## Examples ```javascript var exponential = require( '@stdlib/random-base-exponential' ); var dtypes = require( '@stdlib/ndarray-dtypes' ); var ndarray = require( '@stdlib/ndarray-ctor' ); var ndarray2array = require( '@stdlib/ndarray-to-array' ); var Random = require( '@stdlib/random-tools-unary' ); // Create a new PRNG instance... var idt = dtypes( 'real_and_generic' ); var odt = dtypes( 'real_floating_point_and_generic' ); var policies = { 'output': 'real_floating_point_and_generic' }; var random = new Random( exponential, idt, odt, policies ); // Generate a 3x3 matrix of pseudorandom numbers: var x = random.generate( [ 3, 3 ], 2.0 ); console.log( ndarray2array( x ) ); // Generate another matrix with a specified data type: x = random.generate( [ 3, 3 ], 2.0, { 'dtype': 'float32' }); console.log( ndarray2array( x ) ); // Define an array of distribution parameters: var param = new ndarray( 'generic', [ 2.0, 20.0, 200.0 ], [ 3, 1 ], [ 1, 1 ], 0, 'row-major' ); // Broadcast the parameters to generate another 3x3 matrix of pseudorandom numbers: x = random.generate( [ 3, 3 ], param ); console.log( ndarray2array( x ) ); ```

* * * ## 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
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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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