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@stdlib/random-iter-kumaraswamy
Advanced tools
Create an iterator for generating pseudorandom numbers drawn from a Kumaraswamy's double bounded distribution.
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Create an iterator for generating pseudorandom numbers drawn from a Kumaraswamy's double bounded distribution.
npm install @stdlib/random-iter-kumaraswamy
var iterator = require( '@stdlib/random-iter-kumaraswamy' );
Returns an iterator for generating pseudorandom numbers drawn from a Kumaraswamy's double bounded distribution with parameters a (first shape parameter) and b (second shape parameter).
var it = iterator( 2.0, 1.0 );
// returns <Object>
var r = it.next().value;
// returns <number>
r = it.next().value;
// returns <number>
r = it.next().value;
// returns <number>
// ...
If a <= 0 or b <= 0, the function throws an error.
var it = iterator( -1.0, 1.0 );
// throws <TypeError>
The function accepts the following options:
[0,1). If provided, the function ignores both the state and seed options. In order to seed the returned iterator, one must seed the provided prng (assuming the provided prng is seedable).Uint32Array containing pseudorandom number generator state. If provided, the function ignores the seed option.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 iterator has exclusive control over its internal pseudorandom number generator state. Default: true.To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng option.
var minstd = require( '@stdlib/random-base-minstd' );
var it = iterator( 2.0, 2.0, {
'prng': minstd.normalized
});
var r = it.next().value;
// returns <number>
To return an iterator having a specific initial state, set the iterator state option.
var bool;
var it1;
var it2;
var r;
var i;
it1 = iterator( 2.0, 2.0 );
// Generate pseudorandom numbers, thus progressing the generator state:
for ( i = 0; i < 1000; i++ ) {
r = it1.next().value;
}
// Create a new iterator initialized to the current state of `it1`:
it2 = iterator( 2.0, 2.0, {
'state': it1.state
});
// Test that the generated pseudorandom numbers are the same:
bool = ( it1.next().value === it2.next().value );
// returns true
To seed the iterator, set the seed To seed the iterator, set the seed option.
var it1 = iterator( 2.0, 2.0, {
'seed': 12345
});
var r1 = it1.next().value;
// returns <number>
var it2 = iterator( 2.0, 2.0, {
'seed': 12345
});
var r2 = it2.next().value;
// returns <number>
var bool = ( r1 === r2 );
// returns true
To limit the number of iterations, set the iter option.
var it = iterator( 2.0, 2.0, {
'iter': 2
});
var r = it.next().value;
// returns <number>
r = it.next().value;
// returns <number>
r = it.next().done;
// returns true
The returned iterator protocol-compliant object has the following properties:
value property and a done property having a boolean value indicating whether the iterator is finished.prng option, the property value is null.prng option, the property value is null.prng option, the property value is null.prng option, the property value is null.prng option, the property value is null.Symbol.iterator, the returned iterator is iterable.var iterator = require( '@stdlib/random-iter-kumaraswamy' );
var it;
var r;
// Create a seeded iterator for generating pseudorandom numbers:
it = iterator( 2.0, 5.0, {
'seed': 1234,
'iter': 10
});
// Perform manual iteration...
while ( true ) {
r = it.next();
if ( r.done ) {
break;
}
console.log( r.value );
}
@stdlib/random-base/kumaraswamy: Kumaraswamy's double bounded distributed pseudorandom numbers.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.
See LICENSE.
Copyright © 2016-2026. The Stdlib Authors.
FAQs
Create an iterator for generating pseudorandom numbers drawn from a Kumaraswamy's double bounded distribution.
We found that @stdlib/random-iter-kumaraswamy demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 4 open source maintainers collaborating on the project.
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