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@stdlib/random-streams-box-muller

v0.2.1

Published

Create a readable stream for generating pseudorandom numbers drawn from a standard normal distribution using the Box-Muller transform.

Downloads

85

Readme

Standard Normal Random Numbers

NPM version Build Status Coverage Status

Create a readable stream for generating pseudorandom numbers drawn from a standard normal distribution using the Box-Muller transform.

Installation

npm install @stdlib/random-streams-box-muller

Usage

var randomStream = require( '@stdlib/random-streams-box-muller' );

randomStream( [options] )

Returns a readable stream for generating pseudorandom numbers drawn from a standard normal distribution using the Box-Muller transform.

var inspectStream = require( '@stdlib/streams-node-inspect-sink' );

var iStream;
var stream;

function log( chunk, idx ) {
    console.log( chunk.toString() );
    if ( idx === 10 ) {
        stream.destroy();
    }
}

stream = randomStream();
iStream = inspectStream( log );

stream.pipe( iStream );

The function accepts the following options:

  • objectMode: specifies whether a stream should operate in objectMode. Default: false.
  • encoding: specifies how Buffer objects should be decoded to strings. Default: null.
  • highWaterMark: specifies the maximum number of bytes to store in an internal buffer before ceasing to generate additional pseudorandom numbers.
  • sep: separator used to join streamed data. This option is only applicable when a stream is not in objectMode. Default: '\n'.
  • iter: number of iterations.
  • 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 returned pseudorandom number generator stream, 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 and/or streams. Setting this option to true ensures that a stream generator has exclusive control over its internal state. Default: true.
  • siter: number of iterations after which to emit the pseudorandom number generator state. This option is useful when wanting to deterministically capture a stream's underlying PRNG state. Default: 1e308.

To set stream options,

var opts = {
    'objectMode': true,
    'encoding': 'utf8',
    'highWaterMark': 64
};

var stream = randomStream( opts );

By default, the function returns a stream which can generate an infinite number of values (i.e., the stream will never end). To limit the number of generated pseudorandom numbers, set the iter option.

var inspectStream = require( '@stdlib/streams-node-inspect-sink' );

function log( chunk ) {
    console.log( chunk.toString() );
}

var opts = {
    'iter': 10
};

var stream = randomStream( opts );
var iStream = inspectStream( log );

stream.pipe( iStream );

By default, when not operating in objectMode, a returned stream delineates generated pseudorandom numbers using a newline character. To specify an alternative separator, set the sep option.

var inspectStream = require( '@stdlib/streams-node-inspect-sink' );

function log( chunk ) {
    console.log( chunk.toString() );
}

var opts = {
    'iter': 10,
    'sep': ','
};

var stream = randomStream( opts );
var iStream = inspectStream( log );

stream.pipe( iStream );

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

var inspectStream = require( '@stdlib/streams-node-inspect-sink' );

function log( v ) {
    console.log( v );
}

var opts = {
    'objectMode': true,
    'iter': 10,
    'seed': 1234
};

var stream = randomStream( opts );

opts = {
    'objectMode': true
};
var iStream = inspectStream( opts, log );

stream.pipe( iStream );

To return a readable stream with an underlying pseudorandom number generator having a specific initial state, set the state option.

var inspectStream = require( '@stdlib/streams-node-inspect-sink' );

function log( v ) {
    console.log( v );
}

var opts1 = {
    'objectMode': true,
    'iter': 10
};

var stream = randomStream( opts1 );

var opts2 = {
    'objectMode': true
};
var iStream = inspectStream( opts2, log );

// Stream pseudorandom numbers, thus progressing the underlying generator state:
stream.pipe( iStream );

// Create a new PRNG stream initialized to the last state of the previous stream:
var opts3 = {
    'objectMode': true,
    'iter': 10,
    'state': stream.state
};

stream = randomStream( opts3 );
iStream = inspectStream( opts2, log );

// Stream pseudorandom numbers starting from the last state of the previous stream:
stream.pipe( iStream );
stream.PRNG

The underlying pseudorandom number generator.

var stream = randomStream();

var prng = stream.PRNG;
// returns <Function>
stream.seed

The value used to seed the underlying pseudorandom number generator.

var stream = randomStream();

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

If provided a PRNG for uniformly distributed numbers, this value is null.

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

var stream = randomStream({
    'prng': minstd
});

var seed = stream.seed;
// returns null
stream.seedLength

Length of underlying pseudorandom number generator seed.

var stream = randomStream();

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

If provided a PRNG for uniformly distributed numbers, this value is null.

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

var stream = randomStream({
    'prng': minstd
});

var len = stream.seedLength;
// returns null
stream.state

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

var stream = randomStream();

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

If provided a PRNG for uniformly distributed numbers, this value is null.

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

var stream = randomStream({
    'prng': minstd
});

var state = stream.state;
// returns null
stream.stateLength

Length of underlying pseudorandom number generator state.

var stream = randomStream();

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

If provided a PRNG for uniformly distributed numbers, this value is null.

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

var stream = randomStream({
    'prng': minstd
});

var len = stream.stateLength;
// returns null
stream.byteLength

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

var stream = randomStream();

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

If provided a PRNG for uniformly distributed numbers, this value is null.

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

var stream = randomStream({
    'prng': minstd
});

var sz = stream.byteLength;
// returns null

randomStream.factory( [options] )

Returns a function for creating readable streams which generate pseudorandom numbers drawn from a standard normal distribution using the Box-Muller transform.

var opts = {
    'objectMode': true,
    'encoding': 'utf8',
    'highWaterMark': 64
};

var createStream = randomStream.factory( opts );

The method accepts the same options as randomStream().


randomStream.objectMode( [options] )

This method is a convenience function to create streams which always operate in objectMode.

var inspectStream = require( '@stdlib/streams-node-inspect-sink' );

function log( v ) {
    console.log( v );
}

var opts = {
    'iter': 10
};
var stream = randomStream.objectMode( opts );

opts = {
    'objectMode': true
};
var iStream = inspectStream( opts, log );

stream.pipe( iStream );

This method accepts the same options as randomStream(); however, the method will always override the objectMode option in options.


Events

In addition to the standard readable stream events, the following events are supported...

'state'

Emitted after internally generating siter pseudorandom numbers.

var opts = {
    'siter': 10 // emit the PRNG state every 10 pseudorandom numbers
};

var stream = randomStream( opts );

stream.on( 'state', onState );

function onState( state ) {
    // Do something with the emitted state, such as save to file...
}

Notes

  • If PRNG state is "shared" (meaning a state array was provided during stream creation and not copied) and one sets the generator state to a state array having a different length, the underlying 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).
  • In order to capture the PRNG state after a specific number of generated pseudorandom numbers, regardless of internal stream buffering, use the siter option in conjunction with a state event listener. Attempting to capture the underlying PRNG state after reading generated numbers is not likely to give expected results, as internal stream buffering will mean more values have been generated than have been read. Thus, the state returned by the state property will likely reflect a future PRNG state from the perspective of downstream consumers.

Examples

var inspectStream = require( '@stdlib/streams-node-inspect-sink' );
var randomStream = require( '@stdlib/random-streams-box-muller' );

function log( v ) {
    console.log( v.toString() );
}

var opts = {
    'objectMode': true,
    'iter': 10
};

var stream = randomStream( opts );

opts = {
    'objectMode': true
};
var iStream = inspectStream( opts, log );

stream.pipe( iStream );

References

  • Box, G. E. P., and Mervin E. Muller. 1958. "A Note on the Generation of Random Normal Deviates." The Annals of Mathematical Statistics 29 (2). The Institute of Mathematical Statistics: 610–11. doi:10.1214/aoms/1177706645.
  • Bell, James R. 1968. "Algorithm 334: Normal Random Deviates." Communications of the ACM 11 (7). New York, NY, USA: ACM: 498. doi:10.1145/363397.363547.
  • Knop, R. 1969. "Remark on Algorithm 334 [G5]: Normal Random Deviates." Communications of the ACM 12 (5). New York, NY, USA: ACM: 281. doi:10.1145/362946.362996.
  • Marsaglia, G., and T. A. Bray. 1964. "A Convenient Method for Generating Normal Variables." SIAM Review 6 (3). Society for Industrial; Applied Mathematics: 260–64. doi:10.1137/1006063.
  • Thomas, David B., Wayne Luk, Philip H.W. Leong, and John D. Villasenor. 2007. "Gaussian Random Number Generators." ACM Computing Surveys 39 (4). New York, NY, USA: ACM. doi:10.1145/1287620.1287622.

See Also


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.

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License

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Copyright

Copyright © 2016-2024. The Stdlib Authors.