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minstd

Fill a strided array with pseudorandom numbers generated using a linear congruential pseudorandom number generator (LCG).

Installation

npm install @stdlib/random-strided-minstd

Alternatively,

• To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
• If you are using Deno, visit the deno branch (see README for usage intructions).
• For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).

The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.

To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

Usage

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

minstd( N, out, so[, options] )

Fills a strided array with pseudorandom integers between 1 and 2147483646.

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

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

// Fill the array with pseudorandom numbers:
minstd( out.length, out, 1 );

The function has the following parameters:

• N: number of indexed elements.
• 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 ];

minstd( 3, 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 out0 = new Float64Array( 6 );

// Create offset views:
var out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

// Fill the output array:
minstd( out1.length, out1, 1 );

The function accepts the following options:

• seed: pseudorandom number generator seed.
• state: an Int32Array 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 a returned generator has exclusive control over its internal state. Default: true.

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

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

var opts = {
    'seed': 12345
};

var out = new Float64Array( 10 );
minstd( out.length, out, 1, opts );

minstd.ndarray( N, out, so, oo[, options] )

Fills a strided array with pseudorandom integers between 1 and 2147483646 using alternative indexing semantics.

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

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

// Fill the array with pseudorandom numbers:
minstd.ndarray( out.length, out, 1, 0 );

The function has the following additional parameters:

• 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 ];

minstd.ndarray( 3, out, 2, 1 );

The function accepts the same options as documented above for minstd().

minstd.normalized( N, out, so[, options] )

Fills a strided array with pseudorandom numbers between 0 and 1.

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

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

// Fill the array with pseudorandom numbers:
minstd.normalized( out.length, out, 1 );

The function has the following parameters:

• N: number of indexed elements.
• out: output array.
• so: index increment for out.

The function accepts the same options as documented above for minstd().

minstd.normalized.ndarray( N, out, so, oo[, options] )

Fills a strided array with pseudorandom numbers between 0 and 1 using alternative indexing semantics.

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

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

// Fill the array with pseudorandom numbers:
minstd.normalized.ndarray( out.length, out, 1, 0 );

The function has the following additional parameters:

• oo: starting index for out.

The function accepts the same options as documented above for minstd().

Notes

• If N <= 0, all functions leave the output array unchanged.
• All functions 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-base-zero-to' );
var logEach = require( '@stdlib/console-log-each' );
var minstd = require( '@stdlib/random-strided-minstd' );

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

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

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

// Fill the array with pseudorandom numbers:
minstd.normalized( x1.length, x1, 1, opts );

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

// Fill the array with the same pseudorandom numbers:
minstd.normalized( x2.length, x2, 1, opts );

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

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See Also

• @stdlib/random-base/minstd: A linear congruential pseudorandom number generator (LCG) based on Park and Miller.
• @stdlib/random-array/minstd: create an array containing pseudorandom numbers generated using a linear congruential pseudorandom number generator (LCG).
• @stdlib/random-strided/minstd-shuffle: fill a strided array with pseudorandom numbers generated using a linear congruential pseudorandom number generator (LCG) whose output is shuffled.
• @stdlib/random-strided/randu: fill a strided array with uniformly distributed pseudorandom numbers between 0 and 1.

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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

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License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.