
Research
/Security News
Coruna Respawned: Compromised art-template npm Package Leads to iOS Browser Exploit Kit
Compromised npm package art-template delivered a Coruna-like iOS Safari exploit framework through a watering-hole attack.
@stdlib/random-strided-uniform
Advanced tools
Fill a strided array with pseudorandom numbers drawn from a continuous uniform distribution.
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!
Fill a strided array with pseudorandom numbers drawn from a continuous uniform distribution.
npm install @stdlib/random-strided-uniform
var uniform = require( '@stdlib/random-strided-uniform' );
Fills a strided array with pseudorandom numbers drawn from a continuous uniform distribution.
var Float64Array = require( '@stdlib/array-float64' );
// Create an array:
var out = new Float64Array( 10 );
// Fill the array with pseudorandom numbers:
uniform( out.length, [ 2.0 ], 0, [ 5.0 ], 0, out, 1 );
The function has the following parameters:
a.b.out.The N and stride parameters determine which strided array elements are accessed at runtime. For example, to access every other value in out,
var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
uniform( 3, [ 2.0 ], 0, [ 5.0 ], 0, out, 2 );
Note that indexing is relative to the first index. To introduce an offset, use typed array views.
var Float64Array = require( '@stdlib/array-float64' );
// Initial arrays...
var a0 = new Float64Array( [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ] );
var b0 = new Float64Array( [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] );
// Create offset views...
var a1 = new Float64Array( a0.buffer, a0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var b1 = new Float64Array( b0.buffer, b0.BYTES_PER_ELEMENT*3 ); // start at 4th element
// Create an output array:
var out = new Float64Array( 3 );
// Fill the output array:
uniform( out.length, a1, -2, b1, 1, out, 1 );
The function accepts the following options:
[0,1). If provided, the function ignores both the state and seed options. In order to seed the underlying pseudorandom number generator, one must seed the provided prng (assuming the provided prng is seedable).Uint32Array containing pseudorandom number generator state. If provided, the function ignores the seed option.boolean indicating whether to copy a provided pseudorandom number generator state. Setting this option to false allows sharing state between two or more pseudorandom number generators. Setting this option to true ensures that an underlying generator has exclusive control over its internal state. Default: true.To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng option.
var Float64Array = require( '@stdlib/array-float64' );
var minstd = require( '@stdlib/random-base-minstd' );
var opts = {
'prng': minstd.normalized
};
var out = new Float64Array( 10 );
uniform( out.length, [ 2.0 ], 0, [ 5.0 ], 0, out, 1, opts );
To seed the underlying pseudorandom number generator, set the seed option.
var Float64Array = require( '@stdlib/array-float64' );
var opts = {
'seed': 12345
};
var out = new Float64Array( 10 );
uniform( out.length, [ 2.0 ], 0, [ 5.0 ], 0, out, 1, opts );
Fills a strided array with pseudorandom numbers drawn from a continuous uniform distribution using alternative indexing semantics.
var Float64Array = require( '@stdlib/array-float64' );
// Create an array:
var out = new Float64Array( 10 );
// Fill the array with pseudorandom numbers:
uniform.ndarray( out.length, [ 2.0 ], 0, 0, [ 5.0 ], 0, 0, out, 1, 0 );
The function has the following additional parameters:
a.b.out.While typed array views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to access every other value in out starting from the second value,
var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
uniform.ndarray( 3, [ 2.0 ], 0, 0, [ 5.0 ], 0, 0, out, 2, 1 );
The function accepts the same options as documented above for uniform().
N <= 0, both functions leave the output array unchanged.var zeros = require( '@stdlib/array-zeros' );
var zeroTo = require( '@stdlib/array-base-zero-to' );
var logEach = require( '@stdlib/console-log-each' );
var uniform = require( '@stdlib/random-strided-uniform' );
// Specify a PRNG seed:
var opts = {
'seed': 1234
};
// Create an array:
var x1 = zeros( 10, 'float64' );
// Create a list of indices:
var idx = zeroTo( x1.length );
// Fill the array with pseudorandom numbers:
uniform( x1.length, [ 2.0 ], 0, [ 5.0 ], 0, x1, 1, opts );
// Create a second array:
var x2 = zeros( 10, 'generic' );
// Fill the array with the same pseudorandom numbers:
uniform( x2.length, [ 2.0 ], 0, [ 5.0 ], 0, x2, 1, opts );
// Print the array contents:
logEach( 'x1[%d] = %.2f; x2[%d] = %.2f', idx, x1, idx, x2 );
@stdlib/random-base/uniform: uniformly distributed pseudorandom numbers.@stdlib/random-array/uniform: create an array containing pseudorandom numbers drawn from a continuous uniform distribution.@stdlib/random-strided/discrete-uniform: fill a strided array with pseudorandom numbers drawn from a discrete uniform distribution.This package is part of 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, see the main project repository.
See LICENSE.
Copyright © 2016-2026. The Stdlib Authors.
FAQs
Fill a strided array with pseudorandom numbers drawn from a continuous uniform distribution.
The npm package @stdlib/random-strided-uniform receives a total of 11 weekly downloads. As such, @stdlib/random-strided-uniform popularity was classified as not popular.
We found that @stdlib/random-strided-uniform demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 4 open source maintainers collaborating on the project.
Did you know?

Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.

Research
/Security News
Compromised npm package art-template delivered a Coruna-like iOS Safari exploit framework through a watering-hole attack.

Company News
As AI accelerates how code is written and shipped, Socket is scaling to protect the software supply chain from the growing wave of attacks targeting open source dependencies.

Company News
Socket is scaling to defend open source against supply chain attacks as AI accelerates software development.