Seedable random number generator supporting many common distributions.
Welcome to the most random module on npm! 😜
npm install --save random
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:
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.
// 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:
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()
Seedable random number generator supporting many common distributions.
Defaults to Math.random as its underlying pseudorandom number generator.
Type: function (rng)
rng (RNG | function) Underlying pseudorandom number generator. (optional, default Math.random)Type: function ()
Creates a new Random instance, optionally specifying parameters to
set a new seed.
Type: function (args, seed, opts): Random
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 ...anyExample:
const random = require('random')
random.use('example_seedrandom_string')
// or
random.use(seedrandom('kittens'))
// or
random.use(Math.random)
Patches Math.random with this Random instance's PRNG.
Type: function ()
Restores a previously patched Math.random to its original value.
Type: function ()
Convenience wrapper around this.rng.next()
Returns a floating point number in [0, 1).
Type: function (): number
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 Lower bound (float, inclusive) (optional, default 0)max number Upper bound (float, exclusive) (optional, default 1)Samples a uniform random integer, optionally specifying lower and upper bounds.
Convence wrapper around random.uniformInt()
Type: function (min, max): number
min number Lower bound (integer, inclusive) (optional, default 0)max number Upper bound (integer, inclusive) (optional, default 1)Samples a uniform random integer, optionally specifying lower and upper bounds.
Convence wrapper around random.uniformInt()
Type: function (min, max): number
min number Lower bound (integer, inclusive) (optional, default 0)max number Upper bound (integer, inclusive) (optional, default 1)Samples a uniform random boolean value.
Convence wrapper around random.uniformBoolean()
Type: function (): boolean
Samples a uniform random boolean value.
Convence wrapper around random.uniformBoolean()
Type: function (): boolean
Generates a Continuous uniform distribution.
Type: function (min, max): function
min number Lower bound (float, inclusive) (optional, default 0)max number Upper bound (float, exclusive) (optional, default 1)Generates a Discrete uniform distribution.
Type: function (min, max): function
min number Lower bound (integer, inclusive) (optional, default 0)max number Upper bound (integer, inclusive) (optional, default 1)Generates a Discrete uniform distribution,
with two possible outcomes, true or `false.
This method is analogous to flipping a coin.
Type: function (): function
Generates a Normal distribution.
Type: function (mu, sigma): function
Generates a Log-normal distribution.
Type: function (mu, sigma): function
mu number Mean of underlying normal distribution (optional, default 0)sigma number Standard deviation of underlying normal distribution (optional, default 1)Generates a Bernoulli distribution.
Type: function (p): function
p number Success probability of each trial. (optional, default 0.5)Generates a Binomial distribution.
Type: function (n, p): function
n number Number of trials. (optional, default 1)p number Success probability of each trial. (optional, default 0.5)Generates a Geometric distribution.
Type: function (p): function
p number Success probability of each trial. (optional, default 0.5)Generates a Poisson distribution.
Type: function (lambda): function
lambda number Mean (lambda > 0) (optional, default 1)Generates an Exponential distribution.
Type: function (lambda): function
lambda number Inverse mean (lambda > 0) (optional, default 1)Generates an Irwin Hall distribution.
Type: function (n): function
n number Number of uniform samples to sum (n >= 0) (optional, default 1)Generates a Bates distribution.
Type: function (n): function
n number Number of uniform samples to average (n >= 1) (optional, default 1)Generates a Pareto distribution.
Type: function (alpha): function
alpha number Alpha (optional, default 1)Distributions
Generators
Misc
Huge shoutout to Roger Combs for donating the random npm package for this project!
Lots of inspiration from d3-random (@mbostock and @svanschooten).
Some distributions and PRNGs are ported from C++ boost::random.
MIT © Travis Fischer
FAQs
Seedable random number generator supporting many common distributions.
The npm package random receives a total of 48,447 weekly downloads. As such, random popularity was classified as popular.
We found that random demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 0 open source maintainers collaborating on the project.
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