@stdlib/random-base-poisson
v0.2.1
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Poisson distributed random numbers.
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Poisson Random Numbers
Poisson distributed pseudorandom numbers.
Installation
npm install @stdlib/random-base-poisson
Usage
var poisson = require( '@stdlib/random-base-poisson' );
poisson( lambda )
Returns a pseudorandom number drawn from a Poisson distribution with mean parameter lambda
.
var r = poisson( 7.9 );
// returns <number>
If lambda <= 0
or lambda
is NaN
, the function returns NaN
.
var r = poisson( -2.0 );
// returns NaN
r = poisson( NaN );
// returns NaN
poisson.factory( [lambda, ][options] )
Returns a pseudorandom number generator (PRNG) for generating pseudorandom numbers drawn from a Poisson distribution.
var rand = poisson.factory();
var r = rand( 15.0 );
// returns <number>
If provided lambda
, the returned generator returns random variates from the specified distribution.
var rand = poisson.factory( 10.0 );
var r = rand();
// returns <number>
r = rand();
// returns <number>
If not provided lambda
, the returned generator requires that lambda
be provided at each invocation.
var rand = poisson.factory();
var r = rand( 4.0 );
// returns <number>
r = rand( 3.14 );
// returns <number>
The function accepts the following options
:
- prng: pseudorandom number generator for generating uniformly distributed pseudorandom numbers on the interval
[0,1)
. If provided, the function ignores both thestate
andseed
options. In order to seed the returned pseudorandom number generator, one must seed the providedprng
(assuming the providedprng
is seedable). - seed: pseudorandom number generator seed.
- state: a
Uint32Array
containing pseudorandom number generator state. If provided, the function ignores theseed
option. - copy:
boolean
indicating whether to copy a provided pseudorandom number generator state. Setting this option tofalse
allows sharing state between two or more pseudorandom number generators. Setting this option totrue
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 = poisson.factory({
'prng': minstd.normalized
});
var r = rand( 3.0 );
// returns <number>
To seed a pseudorandom number generator, set the seed
option.
var rand1 = poisson.factory({
'seed': 12345
});
var r1 = rand1( 3.0 );
// returns <number>
var rand2 = poisson.factory( 3.0, {
'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 = poisson( 10.0 );
}
// Create a new PRNG initialized to the current state of `poisson`:
rand = poisson.factory({
'state': poisson.state
});
// Test that the generated pseudorandom numbers are the same:
bool = ( rand( 10.0 ) === poisson( 10.0 ) );
// returns true
poisson.NAME
The generator name.
var str = poisson.NAME;
// returns 'poisson'
poisson.PRNG
The underlying pseudorandom number generator.
var prng = poisson.PRNG;
// returns <Function>
poisson.seed
The value used to seed poisson()
.
var rand;
var r;
var i;
// Generate pseudorandom values...
for ( i = 0; i < 100; i++ ) {
r = poisson( 2.0 );
}
// Generate the same pseudorandom values...
rand = poisson.factory( 2.0, {
'seed': poisson.seed
});
for ( i = 0; i < 100; i++ ) {
r = rand();
}
If provided a PRNG for uniformly distributed numbers, this value is null
.
var rand = poisson.factory({
'prng': Math.random
});
var seed = rand.seed;
// returns null
poisson.seedLength
Length of generator seed.
var len = poisson.seedLength;
// returns <number>
If provided a PRNG for uniformly distributed numbers, this value is null
.
var rand = poisson.factory({
'prng': Math.random
});
var len = rand.seedLength;
// returns null
poisson.state
Writable property for getting and setting the generator state.
var r = poisson( 10.0 );
// returns <number>
r = poisson( 10.0 );
// returns <number>
// ...
// Get a copy of the current state:
var state = poisson.state;
// returns <Uint32Array>
r = poisson( 10.0 );
// returns <number>
r = poisson( 10.0 );
// returns <number>
// Reset the state:
poisson.state = state;
// Replay the last two pseudorandom numbers:
r = poisson( 10.0 );
// returns <number>
r = poisson( 10.0 );
// returns <number>
// ...
If provided a PRNG for uniformly distributed numbers, this value is null
.
var rand = poisson.factory({
'prng': Math.random
});
var state = rand.state;
// returns null
poisson.stateLength
Length of generator state.
var len = poisson.stateLength;
// returns <number>
If provided a PRNG for uniformly distributed numbers, this value is null
.
var rand = poisson.factory({
'prng': Math.random
});
var len = rand.stateLength;
// returns null
poisson.byteLength
Size (in bytes) of generator state.
var sz = poisson.byteLength;
// returns <number>
If provided a PRNG for uniformly distributed numbers, this value is null
.
var rand = poisson.factory({
'prng': Math.random
});
var sz = rand.byteLength;
// returns null
poisson.toJSON()
Serializes the pseudorandom number generator as a JSON object.
var o = poisson.toJSON();
// returns { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }
If provided a PRNG for uniformly distributed numbers, this method returns null
.
var rand = poisson.factory({
'prng': Math.random
});
var o = rand.toJSON();
// returns null
Notes
- If PRNG state is "shared" (meaning a state array was provided during PRNG creation and not copied) and one sets the generator state to a state array having a different length, the PRNG does not update the existing shared state and, instead, points to the newly provided state array. In order to synchronize PRNG output according to the new shared state array, the state array for each relevant PRNG must be explicitly set.
- If PRNG state is "shared" and one sets the generator state to a state array of the same length, the PRNG state is updated (along with the state of all other PRNGs sharing the PRNG's state array).
Examples
var poisson = require( '@stdlib/random-base-poisson' );
var seed;
var rand;
var i;
// Generate pseudorandom numbers...
for ( i = 0; i < 100; i++ ) {
console.log( poisson( 8.0 ) );
}
// Create a new pseudorandom number generator...
seed = 1234;
rand = poisson.factory( 0.8, {
'seed': seed
});
for ( i = 0; i < 100; i++ ) {
console.log( rand() );
}
// Create another pseudorandom number generator using a previous seed...
rand = poisson.factory( 8.0, {
'seed': poisson.seed
});
for ( i = 0; i < 100; i++ ) {
console.log( rand() );
}
References
- Knuth, Donald E. 1997. The Art of Computer Programming, Volume 2 (3rd Ed.): Seminumerical Algorithms. Boston, MA, USA: Addison-Wesley Longman Publishing Co., Inc.
- Hörmann, W. 1993. "The transformed rejection method for generating Poisson random variables." Insurance: Mathematics and Economics 12 (1): 39–45. doi:10.1016/0167-6687(93)90997-4.
See Also
@stdlib/random-array/poisson
: create an array containing pseudorandom numbers drawn from a Poisson distribution.@stdlib/random-iter/poisson
: create an iterator for generating pseudorandom numbers drawn from a Poisson distribution.@stdlib/random-streams/poisson
: create a readable stream for generating pseudorandom numbers drawn from a Poisson distribution.
Notice
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.
Community
License
See LICENSE.
Copyright
Copyright © 2016-2024. The Stdlib Authors.