Poisson Random Numbers

Fill a strided array with pseudorandom numbers drawn from a Poisson distribution.

Installation

npm install @stdlib/random-strided-poisson

Usage

var poisson = require( '@stdlib/random-strided-poisson' );

poisson( N, lambda, sl, out, so )

Fills a strided array with pseudorandom numbers drawn from a Poisson distribution.

var Float64Array = require( '@stdlib/array-float64' );

// Create an array:
var out = new Float64Array( 10 );

// Fill the array with pseudorandom numbers:
poisson( out.length, [ 2.0 ], 0, out, 1 );

The function has the following parameters:

• N: number of indexed elements.
• lambda: rate parameter.
• sl: index increment for lambda.
• out: output array.
• so: index increment for out.

The N and stride parameters determine which strided array elements are accessed at runtime. For example, to access every other value in out,

var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];

poisson( 3, [ 2.0 ], 0, out, 2 );

Note that indexing is relative to the first index. To introduce an offset, use typed array views.

var Float64Array = require( '@stdlib/array-float64' );

// Initial array:
var lambda0 = new Float64Array( [ 2.0, 2.0, 2.0, 2.0, 2.0, 2.0 ] );

// Create offset view:
var lambda1 = new Float64Array( lambda0.buffer, lambda0.BYTES_PER_ELEMENT*3 ); // start at 4th element

// Create an output array:
var out = new Float64Array( 3 );

// Fill the output array:
poisson( out.length, lambda1, -1, out, 1 );

poisson.ndarray( N, lambda, sl, ol, out, so, oo )

Fills a strided array with pseudorandom numbers drawn from a Poisson distribution using alternative indexing semantics.

var Float64Array = require( '@stdlib/array-float64' );

// Create an array:
var out = new Float64Array( 10 );

// Fill the array with pseudorandom numbers:
poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 );

The function has the following additional parameters:

• ol: starting index for lambda.
• oo: starting index for out.

While typed array views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to access every other value in out starting from the second value,

var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];

poisson.ndarray( 3, [ 2.0 ], 0, 0, out, 2, 1 );

poisson.factory( [options] )

Returns a function for filling strided arrays with pseudorandom numbers drawn from a Poisson distribution.

var Float64Array = require( '@stdlib/array-float64' );

var random = poisson.factory();
// returns <Function>

// Create an array:
var out = new Float64Array( 10 );

// Fill the array with pseudorandom numbers:
random( out.length, [ 2.0 ], 0, out, 1 );

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 the state and seed options. In order to seed the underlying pseudorandom number generator, one must seed the provided prng (assuming the provided prng is seedable).
• seed: pseudorandom number generator seed.
• state: a Uint32Array containing pseudorandom number generator state. If provided, the function ignores the seed option.
• copy: 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 an underlying 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 Float64Array = require( '@stdlib/array-float64' );
var minstd = require( '@stdlib/random-base-minstd' );

var opts = {
    'prng': minstd.normalized
};
var random = poisson.factory( opts );

var out = new Float64Array( 10 );
random( out.length, [ 2.0 ], 0, out, 1 );

To seed the underlying pseudorandom number generator, set the seed option.

var Float64Array = require( '@stdlib/array-float64' );

var opts = {
    'seed': 12345
};
var random = poisson.factory( opts );

var out = new Float64Array( 10 );
random( out.length, [ 2.0 ], 0, out, 1 );

random.PRNG

The underlying pseudorandom number generator.

var prng = poisson.PRNG;
// returns <Function>

poisson.seed

The value used to seed the underlying pseudorandom number generator.

var seed = poisson.seed;
// returns <Uint32Array>

If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.

var minstd = require( '@stdlib/random-base-minstd-shuffle' ).normalized;

var random = poisson.factory({
    'prng': minstd
});
// returns <Function>

var seed = random.seed;
// returns null

poisson.seedLength

Length of underlying pseudorandom number generator seed.

var len = poisson.seedLength;
// returns <number>

If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.

var minstd = require( '@stdlib/random-base-minstd-shuffle' ).normalized;

var random = poisson.factory({
    'prng': minstd
});
// returns <Function>

var len = random.seedLength;
// returns null

poisson.state

Writable property for getting and setting the underlying pseudorandom number generator state.

var state = poisson.state;
// returns <Uint32Array>

If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.

var minstd = require( '@stdlib/random-base-minstd-shuffle' ).normalized;

var random = poisson.factory({
    'prng': minstd
});
// returns <Function>

var state = random.state;
// returns null

poisson.stateLength

Length of underlying pseudorandom number generator state.

var len = poisson.stateLength;
// returns <number>

If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.

var minstd = require( '@stdlib/random-base-minstd-shuffle' ).normalized;

var random = poisson.factory({
    'prng': minstd
});
// returns <Function>

var len = random.stateLength;
// returns null

poisson.byteLength

Size (in bytes) of underlying pseudorandom number generator state.

var sz = poisson.byteLength;
// returns <number>

If the factory method is provided a PRNG for uniformly distributed numbers, the associated property value on the returned function is null.

var minstd = require( '@stdlib/random-base-minstd-shuffle' ).normalized;

var random = poisson.factory({
    'prng': minstd
});
// returns <Function>

var sz = random.byteLength;
// returns null

Notes

• If N <= 0, both poisson and poisson.ndarray leave the output array unchanged.
• Both poisson and poisson.ndarray support array-like objects having getter and setter accessors for array element access.

Examples

var zeros = require( '@stdlib/array-zeros' );
var zeroTo = require( '@stdlib/array-zero-to' );
var logEach = require( '@stdlib/console-log-each' );
var poisson = require( '@stdlib/random-strided-poisson' );

// Specify a PRNG seed:
var opts = {
    'seed': 1234
};

// Create a seeded PRNG:
var rand1 = poisson.factory( opts );

// Create an array:
var x1 = zeros( 10, 'float64' );

// Fill the array with pseudorandom numbers:
rand1( x1.length, [ 2.0 ], 0, x1, 1 );

// Create another function for filling strided arrays:
var rand2 = poisson.factory( opts );
// returns <Function>

// Create a second array:
var x2 = zeros( 10, 'generic' );

// Fill the array with the same pseudorandom numbers:
rand2( x2.length, [ 2.0 ], 0, x2, 1 );

// Create a list of indices:
var idx = zeroTo( x1.length, 'generic' );

// Print the array contents:
logEach( 'x1[%d] = %.2f; x2[%d] = %.2f', idx, x1, idx, x2 );

See Also

• @stdlib/random-base/poisson: Poisson distributed random numbers.
• @stdlib/random-array/poisson: create an array containing 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.