3.1.1 • Published 4 years ago

implausible v3.1.1

Weekly downloads
198
License
MIT
Repository
github
Last release
4 years ago

implausible

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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:

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

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

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.

parameterinput type(s)defaultdescription
nameStringarc4Refer to the list of PRNG names for values.
seedNumber, Stringundefined (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.

parameterinput type(s)defaultdescription
collection (required)Array or Object of {String:Number} pairsArray: 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.
nameStringarc4Refer to the list of PRNG names for values.
seedNumber, Stringundefined (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.

parameterinput type(s)defaultdescription
collection (required)Array or Object of {String:Number} pairsArray: 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.
countNumber1Sample size that determines output Array length.
nameStringarc4Refer to the list of PRNG names for values.
seedNumber, Stringundefined (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.

deterministicprngprobabilitypseudorandomrandomsampleseedseedableseededstochasticuniformweighted
ramdaseedrandom
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