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Generate pseudorandom numbers with optional seed and choice of algorithm.

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implausible

implausible is a collection of pseudorandom number generators (PRNGs) and utilities powered by seedrandom.

Quick start

RunKit

RunKit provides one of the most direct ways to get started:

test with RunKit

CodePen

Declare imports and global binding in the JS section to get started:

import { prng } from 'https://unpkg.com/implausible@latest?module';
window.prng = prng;

Run commands in the Console section:

prng();
// example output: 0.3722007770466942

test with CodePen

Browsers

Insert the following element within the <head> tag of an HTML document:

<script src="https://unpkg.com/implausible@latest"></script>

After the script is loaded, the implausible browser global is exposed:

implausible.prng();
// example output: 0.6736552471595748

Node.js

With npm installed, run terminal command:

npm i implausible

npm package

Once installed, declare method imports at the top of each JavaScript file they will be used.

ES2015

Recommended

import {
  prng,
  sample,
  samples,
} from 'implausible';

CommonJS

const {
  prng,
  sample,
  samples,
} = require('implausible');

Usage

Generate stochastic number

prng();
// example output: 0.4471833625387327

prng();
// example output: 0.18700348375416123

...with a specific algorithm

Refer to the list of PRNG names for valid parameter { name } values.

prng({ name: 'xor4096' });
// example output: 0.7105067998636514

Generate deterministic number

prng({ seed: 'hello.' });
// output: 0.9282578795792454

prng({ seed: 'hello.' });
// output: 0.9282578795792454

...with a specific algorithm

Refer to the list of PRNG names for valid parameter { name } values.

prng({
  name: 'xor4096',
  seed: 'hello.',
});
// output: 0.9798525865189731

Stochastic uniform sample

sample({
  collection: [
    'heads',
    'tails',
  ],
});
// example output: 'tails'

...with a specific algorithm

Refer to the list of PRNG names for valid parameter { name } values.

sample({
  collection: [
    'heads',
    'tails',
  ],
  name: 'alea',
});
// example output: 'heads'

Stochastic weighted sample

sample({
  collection: {
    'A-': 6.3,
    'A+': 35.7,
    'AB-': 0.6,
    'AB+': 3.4,
    'B-': 1.5,
    'B+': 8.5,
    'O-': 6.6,
    'O+': 37.4,
  },
});
// example output: 'A+'

...with a specific algorithm

Refer to the list of PRNG names for valid parameter { name } values.

sample({
  collection: {
    'A-': 6.3,
    'A+': 35.7,
    'AB-': 0.6,
    'AB+': 3.4,
    'B-': 1.5,
    'B+': 8.5,
    'O-': 6.6,
    'O+': 37.4,
  },
  name: 'alea',
});
// example output: 'O+'

Deterministic uniform sample

sample({
  collection: [
    'heads',
    'tails',
  ],
  seed: 'hello.',
});
// output: 'tails'

...with a specific algorithm

Refer to the list of PRNG names for valid parameter { name } values.

sample({
  collection: [
    'heads',
    'tails',
  ],
  name: 'tychei',
  seed: 'hello.',
});
// output: 'heads'

Deterministic weighted sample

sample({
  collection: {
    'A-': 6.3,
    'A+': 35.7,
    'AB-': 0.6,
    'AB+': 3.4,
    'B-': 1.5,
    'B+': 8.5,
    'O-': 6.6,
    'O+': 37.4,
  },
  seed: 'hello.',
});
// output: 'A-'

...with a specific algorithm

Refer to the list of PRNG names for valid parameter { name } values.

sample({
  collection: {
    'A-': 6.3,
    'A+': 35.7,
    'AB-': 0.6,
    'AB+': 3.4,
    'B-': 1.5,
    'B+': 8.5,
    'O-': 6.6,
    'O+': 37.4,
  },
  name: 'tychei',
  seed: 'hello.',
});
// output: 'A+'

API

List of PRNG names

The following names of pseudorandom number generators (PRNGs) are valid String inputs for the optional { name } parameter:

alea
arc4 (default)
tychei
xor128
xor4096
xorshift7
xorwow

All undefined seed are automatically generated by arc4 before being piped to other generators in stochastic mode. Visit seedrandom documentation for comparative statistics on period and performance.

`prng() || prng({ [name][, seed] })`

Input

All parameters are optional properties of an optional Object.

parameter	input type(s)	default	description
`name`	`String`	`arc4`	Refer to the list of PRNG names for values.
`seed`	`Number`, `String`	`undefined` (stochastic)	Deterministic when provided, or stochastic when undefined.

Output

Generates a Number within range: [0, 1) (including 0 and excluding 1).

`sample({ collection[, name][, seed] })`

See also: samples

Input

All parameters are properties of an Object.

parameter	input type(s)	default	description
`collection` (required)	`Array` or `Object` of `{String:Number}` pairs		`Array`: collection of outcomes with uniform (equally likely) probability distribution (i.e.: coin, dice). `Object`: histogram where the relative probability of sampling a key is determined by its `Number` value.
`name`	`String`	`arc4`	Refer to the list of PRNG names for values.
`seed`	`Number`, `String`	`undefined` (stochastic)	Deterministic when provided, or stochastic when undefined.

Output

Generates a String weighted random sample from a collection member or key.

`samples({ collection[, count][, name][, seed] })`

See also: sample

Input

All parameters are properties of an Object.

parameter	input type(s)	default	description
`collection` (required)	`Array` or `Object` of `{String:Number}` pairs		`Array`: collection of outcomes with uniform (equally likely) probability distribution (i.e.: coin, dice). `Object`: histogram where the relative probability of sampling a key is determined by its `Number` value.
`count`	`Number`	`1`	Sample size that determines output `Array` length.
`name`	`String`	`arc4`	Refer to the list of PRNG names for values.
`seed`	`Number`, `String`	`undefined` (stochastic)	Deterministic when provided, or stochastic when undefined.

Output

Generates an Array of weighted random sample String from a collection member or key, similar to calling sample multiple times.

Credits

Thanks to David Bau and additional authors for distributing parent package seedrandom under the MIT license.