https://github.com/stdlib-js/random-base-mt19937
A 32-bit Mersenne Twister pseudorandom number generator.
https://github.com/stdlib-js/random-base-mt19937
generator javascript math mathematics mersenne mt19937 node node-js nodejs prng pseudorandom rand randint random randu statistics stats stdlib twister uniform
Last synced: about 1 month ago
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A 32-bit Mersenne Twister pseudorandom number generator.
- Host: GitHub
- URL: https://github.com/stdlib-js/random-base-mt19937
- Owner: stdlib-js
- License: apache-2.0
- Created: 2021-06-15T18:12:26.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2025-03-10T02:10:31.000Z (about 1 month ago)
- Last Synced: 2025-03-10T02:46:11.158Z (about 1 month ago)
- Topics: generator, javascript, math, mathematics, mersenne, mt19937, node, node-js, nodejs, prng, pseudorandom, rand, randint, random, randu, statistics, stats, stdlib, twister, uniform
- Language: JavaScript
- Homepage: https://github.com/stdlib-js/stdlib
- Size: 1.94 MB
- Stars: 7
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff
- Security: SECURITY.md
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README
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# Mersenne Twister
[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url]
> A 32-bit [Mersenne Twister][mersenne-twister] pseudorandom number generator.
## Installation
```bash
npm install @stdlib/random-base-mt19937
```
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 mt19937 = require( '@stdlib/random-base-mt19937' );
```
#### mt19937()
Returns a pseudorandom integer on the interval `[0, 4294967295]`.
```javascript
var r = mt19937();
// returns
```
#### mt19937.normalized()
Returns a pseudorandom number on the interval `[0, 1)` with 53-bit precision.
```javascript
var r = mt19937.normalized();
// returns
```
#### mt19937.factory( \[options] )
Returns a 32-bit [Mersenne Twister][mersenne-twister] pseudorandom number generator.
```javascript
var rand = mt19937.factory();
```
The function accepts the following `options`:
- **seed**: pseudorandom number generator seed.
- **state**: a [`Uint32Array`][@stdlib/array/uint32] containing pseudorandom number generator state. If provided, the function ignores the `seed` option.
- **copy**: 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 a returned generator has exclusive control over its internal state. Default: `true`.
By default, a random integer is used to seed the returned generator. To seed the generator, provide either a nonzero integer on the interval `[1, 4294967295]`
```javascript
var rand = mt19937.factory({
'seed': 1234
});
var r = rand();
// returns 822569775
```
or, for arbitrary length seeds, an array-like object containing unsigned 32-bit integers
```javascript
var Uint32Array = require( '@stdlib/array-uint32' );
var rand = mt19937.factory({
'seed': new Uint32Array( [ 291, 564, 837, 1110 ] )
});
var r = rand();
// returns 1067595299
```
To return a generator having a specific initial state, set the generator `state` option.
```javascript
// Generate pseudorandom numbers, thus progressing the generator state:
var r;
var i;
for ( i = 0; i < 1000; i++ ) {
r = mt19937();
}
// Create a new MT19937 PRNG initialized to the current state of `mt19937`:
var rand = mt19937.factory({
'state': mt19937.state
});
// Test that the generated pseudorandom numbers are the same:
var bool = ( rand() === mt19937() );
// returns true
```
#### mt19937.NAME
The generator name.
```javascript
var str = mt19937.NAME;
// returns 'mt19937'
```
#### mt19937.MIN
Minimum possible value.
```javascript
var min = mt19937.MIN;
// returns 0
```
#### mt19937.MAX
Maximum possible value.
```javascript
var max = mt19937.MAX;
// returns 4294967295
```
#### mt19937.seed
The value used to seed `mt19937()`.
```javascript
// Generate pseudorandom values...
var r;
var i;
for ( i = 0; i < 100; i++ ) {
r = mt19937();
}
// Generate the same pseudorandom values...
var rand = mt19937.factory({
'seed': mt19937.seed
});
for ( i = 0; i < 100; i++ ) {
r = rand();
}
```
#### mt19937.seedLength
Length of generator seed.
```javascript
var len = mt19937.seedLength;
// returns
```
#### mt19937.state
Writable property for getting and setting the generator state.
```javascript
var r = mt19937();
// returns
r = mt19937();
// returns
// ...
// Get a copy of the current state:
var state = mt19937.state;
// returns
r = mt19937();
// returns
r = mt19937();
// returns
// Reset the state:
mt19937.state = state;
// Replay the last two pseudorandom numbers:
r = mt19937();
// returns
r = mt19937();
// returns
// ...
```
#### mt19937.stateLength
Length of generator state.
```javascript
var len = mt19937.stateLength;
// returns
```
#### mt19937.byteLength
Size (in bytes) of generator state.
```javascript
var sz = mt19937.byteLength;
// returns
```
#### mt19937.toJSON()
Serializes the pseudorandom number generator as a JSON object.
```javascript
var o = mt19937.toJSON();
// returns { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }
```
## Notes
- [Mersenne Twister][mersenne-twister] is **not** a cryptographically secure PRNG, as the PRNG is based on a linear recursion. Any pseudorandom number sequence generated by a linear recursion is **insecure**, due to the fact that one can predict future generated outputs by observing a sufficiently long subsequence of generated values.
- Compared to other PRNGs, [Mersenne Twister][mersenne-twister] has a large state size (`~2.5kB`). Because of the large state size, beware of increased memory consumption when using the `factory()` method to create many [Mersenne Twister][mersenne-twister] PRNGs. When appropriate (e.g., when external state mutation is not a concern), consider sharing PRNG state.
- A seed array of length `1` is considered **equivalent** to an integer seed equal to the lone seed array element and vice versa.
- If PRNG state is "shared" (meaning a state array was provided during PRNG creation and **not** copied) and one sets the generator state to a state array having a different length, the PRNG does **not** update the existing shared state and, instead, points to the newly provided state array. In order to synchronize PRNG output according to the new shared state array, the state array for **each** relevant PRNG must be **explicitly** set.
- If PRNG state is "shared" and one sets the generator state to a state array of the same length, the PRNG state is updated (along with the state of all other PRNGs sharing the PRNG's state array).
- The PRNG has a period of `2^19937 - 1`.
## Examples
```javascript
var mt19937 = require( '@stdlib/random-base-mt19937' );
// Generate pseudorandom numbers...
var i;
for ( i = 0; i < 100; i++ ) {
console.log( mt19937() );
}
// Create a new pseudorandom number generator...
var seed = 1234;
var rand = mt19937.factory({
'seed': seed
});
for ( i = 0; i < 100; i++ ) {
console.log( rand() );
}
// Create another pseudorandom number generator using a previous seed...
rand = mt19937.factory({
'seed': mt19937.seed
});
for ( i = 0; i < 100; i++ ) {
console.log( rand() );
}
```
* * *
## References
- Matsumoto, Makoto, and Takuji Nishimura. 1998. "Mersenne Twister: A 623-dimensionally Equidistributed Uniform Pseudo-random Number Generator." _ACM Transactions on Modeling and Computer Simulation_ 8 (1). New York, NY, USA: ACM: 3–30. doi:[10.1145/272991.272995][@matsumoto:1998a].
- Harase, Shin. 2017. "Conversion of Mersenne Twister to double-precision floating-point numbers." _ArXiv_ abs/1708.06018 (September). .
* * *
## See Also
- [`@stdlib/random-array/mt19937`][@stdlib/random/array/mt19937]: create an array containing pseudorandom numbers generated using a 32-bit Mersenne Twister pseudorandom number generator.
- [`@stdlib/random-iter/mt19937`][@stdlib/random/iter/mt19937]: create an iterator for a 32-bit Mersenne Twister pseudorandom number generator.
- [`@stdlib/random-streams/mt19937`][@stdlib/random/streams/mt19937]: create a readable stream for a 32-bit Mersenne Twister pseudorandom number generator.
- [`@stdlib/random-base/minstd`][@stdlib/random/base/minstd]: A linear congruential pseudorandom number generator (LCG) based on Park and Miller.
- [`@stdlib/random-base/randi`][@stdlib/random/base/randi]: pseudorandom numbers having integer values.
* * *
## 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]
---
## Copyright
Copyright © 2016-2025. The Stdlib [Authors][stdlib-authors].
[npm-image]: http://img.shields.io/npm/v/@stdlib/random-base-mt19937.svg
[npm-url]: https://npmjs.org/package/@stdlib/random-base-mt19937
[test-image]: https://github.com/stdlib-js/random-base-mt19937/actions/workflows/test.yml/badge.svg?branch=main
[test-url]: https://github.com/stdlib-js/random-base-mt19937/actions/workflows/test.yml?query=branch:main
[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/random-base-mt19937/main.svg
[coverage-url]: https://codecov.io/github/stdlib-js/random-base-mt19937?branch=main
[chat-image]: https://img.shields.io/gitter/room/stdlib-js/stdlib.svg
[chat-url]: https://app.gitter.im/#/room/#stdlib-js_stdlib:gitter.im
[stdlib]: https://github.com/stdlib-js/stdlib
[stdlib-authors]: https://github.com/stdlib-js/stdlib/graphs/contributors
[umd]: https://github.com/umdjs/umd
[es-module]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules
[deno-url]: https://github.com/stdlib-js/random-base-mt19937/tree/deno
[deno-readme]: https://github.com/stdlib-js/random-base-mt19937/blob/deno/README.md
[umd-url]: https://github.com/stdlib-js/random-base-mt19937/tree/umd
[umd-readme]: https://github.com/stdlib-js/random-base-mt19937/blob/umd/README.md
[esm-url]: https://github.com/stdlib-js/random-base-mt19937/tree/esm
[esm-readme]: https://github.com/stdlib-js/random-base-mt19937/blob/esm/README.md
[branches-url]: https://github.com/stdlib-js/random-base-mt19937/blob/main/branches.md
[mersenne-twister]: https://en.wikipedia.org/wiki/Mersenne_Twister
[@matsumoto:1998a]: https://doi.org/10.1145/272991.272995
[@stdlib/array/uint32]: https://github.com/stdlib-js/array-uint32
[@stdlib/random/array/mt19937]: https://github.com/stdlib-js/random-array-mt19937
[@stdlib/random/iter/mt19937]: https://github.com/stdlib-js/random-iter-mt19937
[@stdlib/random/streams/mt19937]: https://github.com/stdlib-js/random-streams-mt19937
[@stdlib/random/base/minstd]: https://github.com/stdlib-js/random-base-minstd
[@stdlib/random/base/randi]: https://github.com/stdlib-js/random-base-randi