About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

minstd

Create an array containing pseudorandom numbers generated using a linear congruential pseudorandom number generator (LCG).

Installation

npm install @stdlib/random-array-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-array-minstd' );

minstd( len[, options] )

Returns an array containing pseudorandom integers on the interval [1, 2147483646].

var out = minstd( 10 );
// returns <Float64Array>

The function has the following parameters:

• len: output array length.
• options: function options.

The function accepts the following options:

• dtype: output array data type. Must be a real-valued data type or "generic". Default: 'float64'.

By default, the function returns a Float64Array. To return an array having a different data type, set the dtype option.

var opts = {
    'dtype': 'generic'
};

var out = minstd( 10, opts );
// returns [...]

minstd.normalized( len[, options] )

Returns an array containing pseudorandom numbers on the interval [0, 1).

var out = minstd.normalized( 10 );
// returns <Float64Array>

The function has the following parameters:

• len: output array length.
• options: function options.

The function accepts the following options:

• dtype: output array data type. Must be a real-valued floating-point data type or "generic". Default: 'float64'.

By default, the function returns a Float64Array. To return an array having a different data type, set the dtype option.

var opts = {
    'dtype': 'generic'
};

var out = minstd.normalized( 10, opts );
// returns [...]

minstd.factory( [options] )

Returns a function for creating arrays containing pseudorandom numbers generated using a linear congruential pseudorandom number generator (LCG).

var random = minstd.factory();

var out = random( 10 );
// returns <Float64Array>

var len = out.length;
// returns 10

out = random.normalized( 10 );
// returns <Float64Array>

len = out.length;
// returns 10

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.
• idtype: default output array data type when generating integers. Must be a real-valued data type or "generic". Default: 'float64'.
• ndtype: default output array data type when generating normalized numbers. Must be a real-valued floating-point data type or "generic". Default: 'float64'.

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

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

var out = random( 10, opts );
// returns <Float64Array>

The returned function accepts the following options:

• dtype: output array data type. Must be a real-valued data type or "generic". This overrides the default output array data type.

The returned function has a normalized method which accepts the following options:

• dtype: output array data type. Must be a real-valued floating-point data type or "generic". This overrides the default output array data type.

To override the default output array data type, set the dtype option.

var random = minstd.factory();

var out = random( 10 );
// returns <Float64Array>

var opts = {
    'dtype': 'generic'
};
out = random( 10, opts );
// returns [...]

minstd.PRNG

The underlying pseudorandom number generator.

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

minstd.seed

The value used to seed the underlying pseudorandom number generator.

var seed = minstd.seed;
// returns <Int32Array>

minstd.seedLength

Length of underlying pseudorandom number generator seed.

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

minstd.state

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

var state = minstd.state;
// returns <Int32Array>

minstd.stateLength

Length of underlying pseudorandom number generator state.

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

minstd.byteLength

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

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

Notes

• An LCG is fast and uses little memory. On the other hand, because the generator is a simple linear congruential generator, the generator has recognized shortcomings. By today's PRNG standards, the generator's period is relatively short. More importantly, the "randomness quality" of the generator's output is lacking. These defects make the generator unsuitable, for example, in Monte Carlo simulations and in cryptographic applications.
• If PRNG state is "shared" (meaning a state array was provided during function creation and not copied) and one sets the underlying generator state to a state array having a different length, the function returned by the factory method does not update the existing shared state and, instead, points to the newly provided state array. In order to synchronize the output of the underlying generator according to the new shared state array, the state array for each relevant creation function and/or PRNG must be explicitly set.
• If PRNG state is "shared" and one sets the underlying generator state to a state array of the same length, the PRNG state is updated (along with the state of all other creation functions and/or PRNGs sharing the PRNG's state array).

Examples

var logEach = require( '@stdlib/console-log-each' );
var minstd = require( '@stdlib/random-array-minstd' );

// Create a function for generating random arrays originating from the same state:
var random = minstd.factory({
    'state': minstd.state,
    'copy': true
});

// Generate 3 arrays:
var x1 = random.normalized( 5 );
var x2 = random.normalized( 5 );
var x3 = random.normalized( 5 );

// Print the contents:
logEach( '%f, %f, %f', x1, x2, x3 );

// Create another function for generating random arrays with the original state:
random = minstd.factory({
    'state': minstd.state,
    'copy': true
});

// Generate a single array which replicates the above pseudorandom number generation sequence:
var x4 = random.normalized( 15 );

// Print the contents:
logEach( '%f', x4 );

---

See Also

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

---

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.