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@stdlib/random-base-improved-ziggurat
Advanced tools
Normally distributed pseudorandom numbers using the improved Ziggurat method.
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Standard normally distributed pseudorandom numbers using the Improved Ziggurat method.
npm install @stdlib/random-base-improved-ziggurat
var randn = require( '@stdlib/random-base-improved-ziggurat' );
Returns a standard normally distributed pseudorandom number.
var r = randn();
// returns <number>
Returns a pseudorandom number generator (PRNG) for generating standard normally distributed pseudorandom numbers.
var rand = randn.factory();
The function accepts the following options
:
[0,1)
. If provided, the function ignores both the state
and seed
options. In order to seed the returned pseudorandom number generator, one must seed the provided prng
(assuming the provided prng
is seedable).Uint32Array
containing pseudorandom number generator state. If provided, the function ignores the seed
option.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
.To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng
option.
var minstd = require( '@stdlib/random-base-minstd' );
var rand = randn.factory({
'prng': minstd.normalized
});
var r = rand();
// returns <number>
To seed a pseudorandom number generator, set the seed
option.
var rand1 = randn.factory({
'seed': 12345
});
var r1 = rand1();
// returns <number>
var rand2 = randn.factory({
'seed': 12345
});
var r2 = rand2();
// returns <number>
var bool = ( r1 === r2 );
// returns true
To return a generator having a specific initial state, set the generator state
option.
var rand;
var bool;
var r;
var i;
// Generate pseudorandom numbers, thus progressing the generator state:
for ( i = 0; i < 1000; i++ ) {
r = randn();
}
// Create a new PRNG initialized to the current state of `randn`:
rand = randn.factory({
'state': randn.state
});
// Test that the generated pseudorandom numbers are the same:
bool = ( rand() === randn() );
// returns true
The generator name.
var str = randn.NAME;
// returns 'improved-ziggurat'
The underlying pseudorandom number generator for uniformly distributed numbers on the interval [0,1)
.
var prng = randn.PRNG;
// returns <Function>
The value used to seed randn()
.
var rand;
var r;
var i;
// Generate pseudorandom values...
for ( i = 0; i < 100; i++ ) {
r = randn();
}
// Generate the same pseudorandom values...
rand = randn.factory({
'seed': randn.seed
});
for ( i = 0; i < 100; i++ ) {
r = rand();
}
If provided a PRNG for uniformly distributed numbers, this value is null
.
var rand = randn.factory({
'prng': Math.random
});
var seed = rand.seed;
// returns null
Length of generator seed.
var len = randn.seedLength;
// returns <number>
If provided a PRNG for uniformly distributed numbers, this value is null
.
var rand = randn.factory({
'prng': Math.random
});
var len = rand.seedLength;
// returns null
Writable property for getting and setting the generator state.
var r = randn();
// returns <number>
r = randn();
// returns <number>
// ...
// Get a copy of the current state:
var state = randn.state;
// returns <Uint32Array>
r = randn();
// returns <number>
r = randn();
// returns <number>
// Reset the state:
randn.state = state;
// Replay the last two pseudorandom numbers:
r = randn();
// returns <number>
r = randn();
// returns <number>
// ...
If provided a PRNG for uniformly distributed numbers, this value is null
.
var rand = randn.factory({
'prng': Math.random
});
var state = rand.state;
// returns null
Length of generator state.
var len = randn.stateLength;
// returns <number>
If provided a PRNG for uniformly distributed numbers, this value is null
.
var rand = randn.factory({
'prng': Math.random
});
var len = rand.stateLength;
// returns null
Size (in bytes) of generator state.
var sz = randn.byteLength;
// returns <number>
If provided a PRNG for uniformly distributed numbers, this value is null
.
var rand = randn.factory({
'prng': Math.random
});
var sz = rand.byteLength;
// returns null
Serializes the pseudorandom number generator as a JSON object.
var o = randn.toJSON();
// returns { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }
If provided a PRNG for uniformly distributed numbers, this method returns null
.
var rand = randn.factory({
'prng': Math.random
});
var o = rand.toJSON();
// returns null
var randn = require( '@stdlib/random-base-improved-ziggurat' );
var seed;
var rand;
var i;
// Generate pseudorandom numbers...
for ( i = 0; i < 100; i++ ) {
console.log( randn() );
}
// Create a new pseudorandom number generator...
seed = 1234;
rand = randn.factory({
'seed': seed
});
for ( i = 0; i < 100; i++ ) {
console.log( rand() );
}
// Create another pseudorandom number generator using a previous seed...
rand = randn.factory({
'seed': randn.seed
});
for ( i = 0; i < 100; i++ ) {
console.log( rand() );
}
@stdlib/random-iter/improved-ziggurat
: create an iterator for generating pseudorandom numbers drawn from a standard normal distribution using the Improved Ziggurat algorithm.@stdlib/random-streams/improved-ziggurat
: create a readable stream for generating pseudorandom numbers drawn from a standard normal distribution using the Improved Ziggurat algorithm.This package is part of 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, see the main project repository.
See LICENSE.
Copyright © 2016-2024. The Stdlib Authors.
FAQs
Normally distributed pseudorandom numbers using the improved Ziggurat method.
We found that @stdlib/random-base-improved-ziggurat demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 4 open source maintainers collaborating on the project.
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