About stdlib...
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 uniformly distributed pseudorandom numbers between
0
and1
.
npm install @stdlib/random-strided-randu
Alternatively,
- To load the package in a website via a
script
tag without installation and bundlers, use the ES Module available on theesm
branch (see README). - If you are using Deno, visit the
deno
branch (see README for usage intructions). - For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the
umd
branch (see README).
The branches.md 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.
var randu = require( '@stdlib/random-strided-randu' );
Fills a strided array with uniformly distributed pseudorandom numbers between 0
and 1
.
var Float64Array = require( '@stdlib/array-float64' );
// Create an array:
var out = new Float64Array( 10 );
// Fill the array with pseudorandom numbers:
randu( out.length, out, 1 );
The function has the following parameters:
- N: number of indexed elements.
- out: output array.
- so: index increment for
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 ];
randu( 3, 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 array:
var out0 = new Float64Array( 6 );
// Create offset views:
var out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
// Fill the output array:
randu( out1.length, out1, 1 );
The function accepts the following options
:
-
name: name of a supported pseudorandom number generator (PRNG), which will serve as the underlying source of pseudorandom numbers. The following generators are supported:
mt19937
: 32-bit Mersenne Twister.minstd
: linear congruential pseudorandom number generator (LCG) based on Park and Miller.minstd-shuffle
: linear congruential pseudorandom number generator (LCG) whose output is shuffled.
Default:
'mt19937'
. -
seed: pseudorandom number generator seed. Valid seed values vary according to the underlying PRNG.
-
state: pseudorandom number generator state. Valid state values vary according to the underlying PRNG. If provided, the function ignores the
seed
option. -
copy:
boolean
indicating whether to copy a provided pseudorandom number generator state. Setting this option tofalse
allows sharing state between two or more pseudorandom number generators. Setting this option totrue
ensures that a returned generator has exclusive control over its internal state. Default:true
.
By default, the underlying pseudorandom number generator is mt19937
. To use a different PRNG, set the name
option.
var Float64Array = require( '@stdlib/array-float64' );
var opts = {
'name': 'minstd-shuffle'
};
var out = new Float64Array( 10 );
randu( out.length, 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 );
randu( out.length, out, 1, opts );
Fills a strided array with uniformly distributed pseudorandom numbers between 0
and 1
using alternative indexing semantics.
var Float64Array = require( '@stdlib/array-float64' );
// Create an array:
var out = new Float64Array( 10 );
// Fill the array with pseudorandom numbers:
randu.ndarray( out.length, out, 1, 0 );
The function has the following additional parameters:
- oo: starting index for
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 ];
randu.ndarray( 3, out, 2, 1 );
The function accepts the same options
as documented above for randu()
.
- If
N <= 0
, both functions leave the output array unchanged. - Both functions support array-like objects having getter and setter accessors for array element access.
var zeros = require( '@stdlib/array-zeros' );
var zeroTo = require( '@stdlib/array-base-zero-to' );
var logEach = require( '@stdlib/console-log-each' );
var randu = require( '@stdlib/random-strided-randu' );
// 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:
randu( x1.length, x1, 1, opts );
// Create a second array:
var x2 = zeros( 10, 'generic' );
// Fill the array with the same pseudorandom numbers:
randu( x2.length, x2, 1, opts );
// Print the array contents:
logEach( 'x1[%d] = %.2f; x2[%d] = %.2f', idx, x1, idx, x2 );
@stdlib/random-base/randu
: uniformly distributed pseudorandom numbers between 0 and 1.@stdlib/random-array/randu
: create an array containing uniformly distributed pseudorandom numbers between 0 and 1.@stdlib/random-strided/uniform
: fill a strided array with pseudorandom numbers drawn from a continuous 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 © 2016-2024. The Stdlib Authors.