@stdlib/random-strided-geometric
v0.1.1
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Fill a strided array with pseudorandom numbers drawn from a geometric distribution.
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Geometric Random Numbers
Fill a strided array with pseudorandom numbers drawn from a geometric distribution.
Installation
npm install @stdlib/random-strided-geometric
Usage
var geometric = require( '@stdlib/random-strided-geometric' );
geometric( N, p, sp, out, so )
Fills a strided array with pseudorandom numbers drawn from a geometric distribution.
var Float64Array = require( '@stdlib/array-float64' );
// Create an array:
var out = new Float64Array( 10 );
// Fill the array with pseudorandom numbers:
geometric( out.length, [ 0.01 ], 0, out, 1 );
The function has the following parameters:
- N: number of indexed elements.
- p: rate parameter.
- sp: index increment for
p
. - 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 ];
geometric( 3, [ 0.01 ], 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 p0 = new Float64Array( [ 0.01, 0.01, 0.01, 0.01, 0.01, 0.01 ] );
// Create offset view:
var p1 = new Float64Array( p0.buffer, p0.BYTES_PER_ELEMENT*3 ); // start at 4th element
// Create an output array:
var out = new Float64Array( 3 );
// Fill the output array:
geometric( out.length, p1, -1, out, 1 );
geometric.ndarray( N, p, sp, op, out, so, oo )
Fills a strided array with pseudorandom numbers drawn from a geometric 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:
geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 );
The function has the following additional parameters:
- op: starting index for
p
. - 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 ];
geometric.ndarray( 3, [ 0.01 ], 0, 0, out, 2, 1 );
geometric.factory( [options] )
Returns a function for filling strided arrays with pseudorandom numbers drawn from a geometric distribution.
var Float64Array = require( '@stdlib/array-float64' );
var random = geometric.factory();
// returns <Function>
// Create an array:
var out = new Float64Array( 10 );
// Fill the array with pseudorandom numbers:
random( out.length, [ 0.01 ], 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 thestate
andseed
options. In order to seed the underlying 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 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 = geometric.factory( opts );
var out = new Float64Array( 10 );
random( out.length, [ 0.01 ], 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 = geometric.factory( opts );
var out = new Float64Array( 10 );
random( out.length, [ 0.01 ], 0, out, 1 );
random.PRNG
The underlying pseudorandom number generator.
var prng = geometric.PRNG;
// returns <Function>
geometric.seed
The value used to seed the underlying pseudorandom number generator.
var seed = geometric.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 = geometric.factory({
'prng': minstd
});
// returns <Function>
var seed = random.seed;
// returns null
geometric.seedLength
Length of underlying pseudorandom number generator seed.
var len = geometric.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 = geometric.factory({
'prng': minstd
});
// returns <Function>
var len = random.seedLength;
// returns null
geometric.state
Writable property for getting and setting the underlying pseudorandom number generator state.
var state = geometric.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 = geometric.factory({
'prng': minstd
});
// returns <Function>
var state = random.state;
// returns null
geometric.stateLength
Length of underlying pseudorandom number generator state.
var len = geometric.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 = geometric.factory({
'prng': minstd
});
// returns <Function>
var len = random.stateLength;
// returns null
geometric.byteLength
Size (in bytes) of underlying pseudorandom number generator state.
var sz = geometric.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 = geometric.factory({
'prng': minstd
});
// returns <Function>
var sz = random.byteLength;
// returns null
Notes
- If
N <= 0
, bothgeometric
andgeometric.ndarray
leave the output array unchanged. - Both
geometric
andgeometric.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 geometric = require( '@stdlib/random-strided-geometric' );
// Specify a PRNG seed:
var opts = {
'seed': 1234
};
// Create a seeded PRNG:
var rand1 = geometric.factory( opts );
// Create an array:
var x1 = zeros( 10, 'float64' );
// Fill the array with pseudorandom numbers:
rand1( x1.length, [ 0.01 ], 0, x1, 1 );
// Create another function for filling strided arrays:
var rand2 = geometric.factory( opts );
// returns <Function>
// Create a second array:
var x2 = zeros( 10, 'generic' );
// Fill the array with the same pseudorandom numbers:
rand2( x2.length, [ 0.01 ], 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/geometric
: geometric distributed pseudorandom numbers.@stdlib/random-array/geometric
: create an array containing pseudorandom numbers drawn from a geometric 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.