aiparking_api/node_modules/random/readme.md
2020-02-02 15:24:30 +07:00

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# random
> Seedable random number generator supporting many common distributions.
[![NPM](https://img.shields.io/npm/v/random.svg)](https://www.npmjs.com/package/random) [![Build Status](https://travis-ci.com/transitive-bullshit/random.svg?branch=master)](https://travis-ci.com/transitive-bullshit/random) [![JavaScript Style Guide](https://img.shields.io/badge/code_style-standard-brightgreen.svg)](https://standardjs.com)
Welcome to the most **random** module on npm! 😜
## Highlights
- Simple API (_make easy things easy and hard things possible_)
- Seedable based on entropy or user input
- Plugin support for different pseudo random number generators (PRNGs)
- Sample from many common distributions
- uniform, normal, poisson, bernoulli, etc
- Validates all user input via [ow](https://github.com/sindresorhus/ow)
- Integrates with [seedrandom](https://github.com/davidbau/seedrandom)
- Supports node >= 6 and browser
## Install
```bash
npm install --save random
```
## Usage
```js
const random = require('random')
// quick uniform shortcuts
random.float(min = 0, max = 1) // uniform float in [ min, max )
random.int(min = 0, max = 1) // uniform integer in [ min, max ]
random.boolean() // true or false
// uniform
random.uniform(min = 0, max = 1) // () => [ min, max )
random.uniformInt(min = 0, max = 1) // () => [ min, max ]
random.uniformBoolean() // () => [ false, true ]
// normal
random.normal(mu = 0, sigma = 1)
random.logNormal(mu = 0, sigma = 1)
// bernoulli
random.bernoulli(p = 0.5)
random.binomial(n = 1, p = 0.5)
random.geometric(p = 0.5)
// poisson
random.poisson(lambda = 1)
random.exponential(lambda = 1)
// misc
random.irwinHall(n)
random.bates(n)
random.pareto(alpha)
```
For convenience, several common uniform samplers are exposed directly:
```js
random.float() // 0.2149383367670885
random.int(0, 100) // 72
random.boolean() // true
```
**All distribution methods return a thunk** (function with no params), which will return
a series of independent, identically distributed random variables from the specified distribution.
```js
// create a normal distribution with default params (mu=1 and sigma=0)
const normal = random.normal()
normal() // 0.4855465422678824
normal() // -0.06696771815439678
normal() // 0.7350852689834705
// create a poisson distribution with default params (lambda=1)
const poisson = random.poisson()
poisson() // 0
poisson() // 4
poisson() // 1
```
Note that returning a thunk here is more efficient when generating multiple
samples from the same distribution.
You can change the underlying PRNG or its seed as follows:
```js
const seedrandom = require('seedrandom')
// change the underlying pseudo random number generator
// by default, Math.random is used as the underlying PRNG
random.use(seedrandom('foobar'))
// create a new independent random number generator (uses seedrandom under the hood)
const rng = random.clone('my-new-seed')
// create a second independent random number generator and use a seeded PRNG
const rng2 = random.clone(seedrandom('kittyfoo'))
// replace Math.random with rng.uniform
rng.patch()
// restore original Math.random
rng.unpatch()
```
## API
<!-- Generated by documentation.js. Update this documentation by updating the source code. -->
#### Table of Contents
- [Random](#random)
- [rng](#rng)
- [clone](#clone)
- [use](#use)
- [patch](#patch)
- [unpatch](#unpatch)
- [next](#next)
- [float](#float)
- [int](#int)
- [integer](#integer)
- [bool](#bool)
- [boolean](#boolean)
- [uniform](#uniform)
- [uniformInt](#uniformint)
- [uniformBoolean](#uniformboolean)
- [normal](#normal)
- [logNormal](#lognormal)
- [bernoulli](#bernoulli)
- [binomial](#binomial)
- [geometric](#geometric)
- [poisson](#poisson)
- [exponential](#exponential)
- [irwinHall](#irwinhall)
- [bates](#bates)
- [pareto](#pareto)
### [Random](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L36-L382)
Seedable random number generator supporting many common distributions.
Defaults to Math.random as its underlying pseudorandom number generator.
Type: `function (rng)`
- `rng` **(RNG | [function](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Statements/function))** Underlying pseudorandom number generator. (optional, default `Math.random`)
* * *
#### [rng](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L47-L49)
Type: `function ()`
* * *
#### [clone](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L61-L67)
- **See: RNG.clone**
Creates a new `Random` instance, optionally specifying parameters to
set a new seed.
Type: `function (args, seed, opts): Random`
- `args` **...any**
- `seed` **[string](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/String)?** Optional seed for new RNG.
- `opts` **[object](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Object)?** Optional config for new RNG options.
* * *
#### [use](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L87-L89)
Sets the underlying pseudorandom number generator used via
either an instance of `seedrandom`, a custom instance of RNG
(for PRNG plugins), or a string specifying the PRNG to use
along with an optional `seed` and `opts` to initialize the
RNG.
Type: `function (args)`
- `args` **...any**
Example:
```javascript
const random = require('random')
random.use('example_seedrandom_string')
// or
random.use(seedrandom('kittens'))
// or
random.use(Math.random)
```
* * *
#### [patch](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L94-L101)
Patches `Math.random` with this Random instance's PRNG.
Type: `function ()`
* * *
#### [unpatch](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L106-L111)
Restores a previously patched `Math.random` to its original value.
Type: `function ()`
* * *
#### [next](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L124-L126)
Convenience wrapper around `this.rng.next()`
Returns a floating point number in \[0, 1).
Type: `function (): number`
* * *
#### [float](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L138-L140)
Samples a uniform random floating point number, optionally specifying
lower and upper bounds.
Convence wrapper around `random.uniform()`
Type: `function (min, max): number`
- `min` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Lower bound (float, inclusive) (optional, default `0`)
- `max` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Upper bound (float, exclusive) (optional, default `1`)
* * *
#### [int](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L152-L154)
Samples a uniform random integer, optionally specifying lower and upper
bounds.
Convence wrapper around `random.uniformInt()`
Type: `function (min, max): number`
- `min` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Lower bound (integer, inclusive) (optional, default `0`)
- `max` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Upper bound (integer, inclusive) (optional, default `1`)
* * *
#### [integer](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L168-L170)
Samples a uniform random integer, optionally specifying lower and upper
bounds.
Convence wrapper around `random.uniformInt()`
Type: `function (min, max): number`
- `min` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Lower bound (integer, inclusive) (optional, default `0`)
- `max` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Upper bound (integer, inclusive) (optional, default `1`)
* * *
#### [bool](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L181-L183)
Samples a uniform random boolean value.
Convence wrapper around `random.uniformBoolean()`
Type: `function (): boolean`
* * *
#### [boolean](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L192-L194)
Samples a uniform random boolean value.
Convence wrapper around `random.uniformBoolean()`
Type: `function (): boolean`
* * *
#### [uniform](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L207-L209)
Generates a [Continuous uniform distribution](https://en.wikipedia.org/wiki/Uniform_distribution_(continuous)).
Type: `function (min, max): function`
- `min` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Lower bound (float, inclusive) (optional, default `0`)
- `max` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Upper bound (float, exclusive) (optional, default `1`)
* * *
#### [uniformInt](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L218-L220)
Generates a [Discrete uniform distribution](https://en.wikipedia.org/wiki/Discrete_uniform_distribution).
Type: `function (min, max): function`
- `min` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Lower bound (integer, inclusive) (optional, default `0`)
- `max` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Upper bound (integer, inclusive) (optional, default `1`)
* * *
#### [uniformBoolean](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L230-L232)
Generates a [Discrete uniform distribution](https://en.wikipedia.org/wiki/Discrete_uniform_distribution),
with two possible outcomes, `true` or \`false.
This method is analogous to flipping a coin.
Type: `function (): function`
* * *
#### [normal](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L245-L247)
Generates a [Normal distribution](https://en.wikipedia.org/wiki/Normal_distribution).
Type: `function (mu, sigma): function`
- `mu` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Mean (optional, default `0`)
- `sigma` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Standard deviation (optional, default `1`)
* * *
#### [logNormal](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L256-L258)
Generates a [Log-normal distribution](https://en.wikipedia.org/wiki/Log-normal_distribution).
Type: `function (mu, sigma): function`
- `mu` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Mean of underlying normal distribution (optional, default `0`)
- `sigma` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Standard deviation of underlying normal distribution (optional, default `1`)
* * *
#### [bernoulli](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L270-L272)
Generates a [Bernoulli distribution](https://en.wikipedia.org/wiki/Bernoulli_distribution).
Type: `function (p): function`
- `p` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Success probability of each trial. (optional, default `0.5`)
* * *
#### [binomial](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L281-L283)
Generates a [Binomial distribution](https://en.wikipedia.org/wiki/Binomial_distribution).
Type: `function (n, p): function`
- `n` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Number of trials. (optional, default `1`)
- `p` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Success probability of each trial. (optional, default `0.5`)
* * *
#### [geometric](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L291-L293)
Generates a [Geometric distribution](https://en.wikipedia.org/wiki/Geometric_distribution).
Type: `function (p): function`
- `p` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Success probability of each trial. (optional, default `0.5`)
* * *
#### [poisson](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L305-L307)
Generates a [Poisson distribution](https://en.wikipedia.org/wiki/Poisson_distribution).
Type: `function (lambda): function`
- `lambda` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Mean (lambda > 0) (optional, default `1`)
* * *
#### [exponential](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L315-L317)
Generates an [Exponential distribution](https://en.wikipedia.org/wiki/Exponential_distribution).
Type: `function (lambda): function`
- `lambda` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Inverse mean (lambda > 0) (optional, default `1`)
* * *
#### [irwinHall](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L329-L331)
Generates an [Irwin Hall distribution](https://en.wikipedia.org/wiki/Irwin%E2%80%93Hall_distribution).
Type: `function (n): function`
- `n` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Number of uniform samples to sum (n >= 0) (optional, default `1`)
* * *
#### [bates](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L339-L341)
Generates a [Bates distribution](https://en.wikipedia.org/wiki/Bates_distribution).
Type: `function (n): function`
- `n` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Number of uniform samples to average (n >= 1) (optional, default `1`)
* * *
#### [pareto](https://github.com/transitive-bullshit/random/blob/e11a840a1cfe0f5bd9c43640f9645a0b28f61406/src/random.js#L349-L351)
Generates a [Pareto distribution](https://en.wikipedia.org/wiki/Pareto_distribution).
Type: `function (alpha): function`
- `alpha` **[number](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number)** Alpha (optional, default `1`)
* * *
## Todo
- Distributions
- [x] uniform
- [x] uniformInt
- [x] uniformBoolean
- [x] normal
- [x] logNormal
- [ ] chiSquared
- [ ] cauchy
- [ ] fischerF
- [ ] studentT
- [x] bernoulli
- [x] binomial
- [ ] negativeBinomial
- [x] geometric
- [x] poisson
- [x] exponential
- [ ] gamma
- [ ] hyperExponential
- [ ] weibull
- [ ] beta
- [ ] laplace
- [x] irwinHall
- [x] bates
- [x] pareto
- Generators
- [x] pluggable prng
- [ ] port more prng from boost
- [ ] custom entropy
- Misc
- [x] browser support via rollup
- [x] basic docs
- [x] basic tests
- [x] test suite
- [x] initial release!
## Related
- [d3-random](https://github.com/d3/d3-random) - D3's excellent random number generation library.
- [seedrandom](https://github.com/davidbau/seedrandom) - Seedable pseudo random number generator.
- [random-int](https://github.com/sindresorhus/random-int) - For the common use case of generating uniform random ints.
- [random-float](https://github.com/sindresorhus/random-float) - For the common use case of generating uniform random floats.
- [randombytes](https://github.com/crypto-browserify/randombytes) - Random crypto bytes for Node.js and the browser.
## Credit
Huge shoutout to [Roger Combs](https://github.com/rcombs) for donating the `random` npm package for this project!
Lots of inspiration from [d3-random](https://github.com/d3/d3-random) ([@mbostock](https://github.com/mbostock) and [@svanschooten](https://github.com/svanschooten)).
Some distributions and PRNGs are ported from C++ [boost::random](https://www.boost.org/doc/libs/1_66_0/doc/html/boost_random/reference.html#boost_random.reference.distributions).
## License
MIT © [Travis Fischer](https://github.com/transitive-bullshit)