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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!

Exponential Random Numbers

NPM versionBuild StatusCoverage Status

Create an iterator for generating pseudorandom numbers drawn from an exponential distribution.

Installation

npm install @stdlib/random-iter-exponential

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

variterator=require('@stdlib/random-iter-exponential');

iterator( lambda[, options] )

Returns an iterator for generating pseudorandom numbers drawn from an exponential distribution with rate parameter lambda.

varit=iterator(2.5);// returns <Object>varr=it.next().value;// returns <number>r=it.next().value;// returns <number>r=it.next().value;// returns <number>// ...

If lambda <= 0, the function throws an error.

varit=iterator(-0.5);// throws <TypeError>

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 the state and seed options. In order to seed the returned iterator, 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. Setting this option to true ensures that a returned iterator has exclusive control over its internal pseudorandom number generator state. Default: true.
  • iter: number of iterations.

To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng option.

varminstd=require('@stdlib/random-base-minstd');varit=iterator(2.0,{'prng': minstd.normalized});varr=it.next().value;// returns <number>

To return an iterator having a specific initial state, set the iterator state option.

varbool;varit1;varit2;varr;vari;it1=iterator(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,{'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 option.

varit1=iterator(2.0,{'seed': 12345});varr1=it1.next().value;// returns <number>varit2=iterator(2.0,{'seed': 12345});varr2=it2.next().value;// returns <number>varbool=(r1===r2);// returns true

To limit the number of iterations, set the iter option.

varit=iterator(2.0,{'iter': 2});varr=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:

  • next: function which returns an iterator protocol-compliant object containing the next iterated value (if one exists) assigned to a value property and a done property having a boolean value indicating whether the iterator is finished.
  • return: function which closes an iterator and returns a single (optional) argument in an iterator protocol-compliant object.
  • seed: pseudorandom number generator seed. If provided a prng option, the property value is null.
  • seedLength: length of generator seed. If provided a prng option, the property value is null.
  • state: writable property for getting and setting the generator state. If provided a prng option, the property value is null.
  • stateLength: length of generator state. If provided a prng option, the property value is null.
  • byteLength: size (in bytes) of generator state. If provided a prng option, the property value is null.
  • PRNG: underlying pseudorandom number generator.

Notes

  • If an environment supports Symbol.iterator, the returned iterator is iterable.
  • If PRNG state is "shared" (meaning a state array was provided during iterator creation and not copied) and one sets the underlying generator state to a state array having a different length, the iterator 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 iterator 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 iterator and/or PRNGs sharing the PRNG's state array).

Examples

variterator=require('@stdlib/random-iter-exponential');varit;varr;// Create a seeded iterator for generating pseudorandom numbers:it=iterator(2.0,{'seed': 1234,'iter': 10});// Perform manual iteration...while(true){r=it.next();if(r.done){break;}console.log(r.value);}

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.

Community

Chat


License

See LICENSE.

Copyright

Copyright © 2016-2026. The Stdlib Authors.

About

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GitHub - stdlib-js/random-iter-exponential: Create an iterator for generating pseudorandom numbers drawn from an exponential distribution. · GitHub
Skip to content
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!

Exponential Random Numbers

NPM versionBuild StatusCoverage Status

Create an iterator for generating pseudorandom numbers drawn from an exponential distribution.

Installation

npm install @stdlib/random-iter-exponential

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

variterator=require('@stdlib/random-iter-exponential');

iterator( lambda[, options] )

Returns an iterator for generating pseudorandom numbers drawn from an exponential distribution with rate parameter lambda.

varit=iterator(2.5);// returns <Object>varr=it.next().value;// returns <number>r=it.next().value;// returns <number>r=it.next().value;// returns <number>// ...

If lambda <= 0, the function throws an error.

varit=iterator(-0.5);// throws <TypeError>

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 the state and seed options. In order to seed the returned iterator, 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. Setting this option to true ensures that a returned iterator has exclusive control over its internal pseudorandom number generator state. Default: true.
  • iter: number of iterations.

To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng option.

varminstd=require('@stdlib/random-base-minstd');varit=iterator(2.0,{'prng': minstd.normalized});varr=it.next().value;// returns <number>

To return an iterator having a specific initial state, set the iterator state option.

varbool;varit1;varit2;varr;vari;it1=iterator(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,{'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 option.

varit1=iterator(2.0,{'seed': 12345});varr1=it1.next().value;// returns <number>varit2=iterator(2.0,{'seed': 12345});varr2=it2.next().value;// returns <number>varbool=(r1===r2);// returns true

To limit the number of iterations, set the iter option.

varit=iterator(2.0,{'iter': 2});varr=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:

  • next: function which returns an iterator protocol-compliant object containing the next iterated value (if one exists) assigned to a value property and a done property having a boolean value indicating whether the iterator is finished.
  • return: function which closes an iterator and returns a single (optional) argument in an iterator protocol-compliant object.
  • seed: pseudorandom number generator seed. If provided a prng option, the property value is null.
  • seedLength: length of generator seed. If provided a prng option, the property value is null.
  • state: writable property for getting and setting the generator state. If provided a prng option, the property value is null.
  • stateLength: length of generator state. If provided a prng option, the property value is null.
  • byteLength: size (in bytes) of generator state. If provided a prng option, the property value is null.
  • PRNG: underlying pseudorandom number generator.

Notes

  • If an environment supports Symbol.iterator, the returned iterator is iterable.
  • If PRNG state is "shared" (meaning a state array was provided during iterator creation and not copied) and one sets the underlying generator state to a state array having a different length, the iterator 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 iterator 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 iterator and/or PRNGs sharing the PRNG's state array).

Examples

variterator=require('@stdlib/random-iter-exponential');varit;varr;// Create a seeded iterator for generating pseudorandom numbers:it=iterator(2.0,{'seed': 1234,'iter': 10});// Perform manual iteration...while(true){r=it.next();if(r.done){break;}console.log(r.value);}

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.

Community

Chat


License

See LICENSE.

Copyright

Copyright © 2016-2026. The Stdlib Authors.

About

Create an iterator for generating pseudorandom numbers drawn from an exponential distribution.

Topics

Resources

Code of conduct

Contributing

Security policy

Stars

2 stars

Watchers

2 watching

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Sponsor this project

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Force GitHub README to respect dark mode (function() { var style = document.createElement('style'); style.textContent = ' .markdown-body { color-scheme: dark light; } .markdown-body pre { background: #161b22 !important; } .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; } .markdown-body table th, .markdown-body table td { border-color: #30363d !important; } .markdown-body img { background: #0d1117; } .markdown-body blockquote { border-left-color: #8b949e; } .markdown-body hr { border-color: #30363d; } '; document.head.appendChild(style); })(); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - stdlib-js/random-iter-exponential: Create an iterator for generating pseudorandom numbers drawn from an exponential distribution. · GitHub
Skip to content
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!

Exponential Random Numbers

NPM versionBuild StatusCoverage Status

Create an iterator for generating pseudorandom numbers drawn from an exponential distribution.

Installation

npm install @stdlib/random-iter-exponential

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

variterator=require('@stdlib/random-iter-exponential');

iterator( lambda[, options] )

Returns an iterator for generating pseudorandom numbers drawn from an exponential distribution with rate parameter lambda.

varit=iterator(2.5);// returns <Object>varr=it.next().value;// returns <number>r=it.next().value;// returns <number>r=it.next().value;// returns <number>// ...

If lambda <= 0, the function throws an error.

varit=iterator(-0.5);// throws <TypeError>

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 the state and seed options. In order to seed the returned iterator, 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. Setting this option to true ensures that a returned iterator has exclusive control over its internal pseudorandom number generator state. Default: true.
  • iter: number of iterations.

To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng option.

varminstd=require('@stdlib/random-base-minstd');varit=iterator(2.0,{'prng': minstd.normalized});varr=it.next().value;// returns <number>

To return an iterator having a specific initial state, set the iterator state option.

varbool;varit1;varit2;varr;vari;it1=iterator(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,{'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 option.

varit1=iterator(2.0,{'seed': 12345});varr1=it1.next().value;// returns <number>varit2=iterator(2.0,{'seed': 12345});varr2=it2.next().value;// returns <number>varbool=(r1===r2);// returns true

To limit the number of iterations, set the iter option.

varit=iterator(2.0,{'iter': 2});varr=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:

  • next: function which returns an iterator protocol-compliant object containing the next iterated value (if one exists) assigned to a value property and a done property having a boolean value indicating whether the iterator is finished.
  • return: function which closes an iterator and returns a single (optional) argument in an iterator protocol-compliant object.
  • seed: pseudorandom number generator seed. If provided a prng option, the property value is null.
  • seedLength: length of generator seed. If provided a prng option, the property value is null.
  • state: writable property for getting and setting the generator state. If provided a prng option, the property value is null.
  • stateLength: length of generator state. If provided a prng option, the property value is null.
  • byteLength: size (in bytes) of generator state. If provided a prng option, the property value is null.
  • PRNG: underlying pseudorandom number generator.

Notes

  • If an environment supports Symbol.iterator, the returned iterator is iterable.
  • If PRNG state is "shared" (meaning a state array was provided during iterator creation and not copied) and one sets the underlying generator state to a state array having a different length, the iterator 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 iterator 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 iterator and/or PRNGs sharing the PRNG's state array).

Examples

variterator=require('@stdlib/random-iter-exponential');varit;varr;// Create a seeded iterator for generating pseudorandom numbers:it=iterator(2.0,{'seed': 1234,'iter': 10});// Perform manual iteration...while(true){r=it.next();if(r.done){break;}console.log(r.value);}

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.

Community

Chat


License

See LICENSE.

Copyright

Copyright © 2016-2026. The Stdlib Authors.

About

Create an iterator for generating pseudorandom numbers drawn from an exponential distribution.

Topics

Resources

Code of conduct

Contributing

Security policy

Stars

2 stars

Watchers

2 watching

Forks

Releases

Sponsor this project

Packages

Used by

Contributors

Languages

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Skip to content
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!

Exponential Random Numbers

NPM versionBuild StatusCoverage Status

Create an iterator for generating pseudorandom numbers drawn from an exponential distribution.

Installation

npm install @stdlib/random-iter-exponential

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

variterator=require('@stdlib/random-iter-exponential');

iterator( lambda[, options] )

Returns an iterator for generating pseudorandom numbers drawn from an exponential distribution with rate parameter lambda.

varit=iterator(2.5);// returns <Object>varr=it.next().value;// returns <number>r=it.next().value;// returns <number>r=it.next().value;// returns <number>// ...

If lambda <= 0, the function throws an error.

varit=iterator(-0.5);// throws <TypeError>

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 the state and seed options. In order to seed the returned iterator, 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. Setting this option to true ensures that a returned iterator has exclusive control over its internal pseudorandom number generator state. Default: true.
  • iter: number of iterations.

To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng option.

varminstd=require('@stdlib/random-base-minstd');varit=iterator(2.0,{'prng': minstd.normalized});varr=it.next().value;// returns <number>

To return an iterator having a specific initial state, set the iterator state option.

varbool;varit1;varit2;varr;vari;it1=iterator(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,{'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 option.

varit1=iterator(2.0,{'seed': 12345});varr1=it1.next().value;// returns <number>varit2=iterator(2.0,{'seed': 12345});varr2=it2.next().value;// returns <number>varbool=(r1===r2);// returns true

To limit the number of iterations, set the iter option.

varit=iterator(2.0,{'iter': 2});varr=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:

  • next: function which returns an iterator protocol-compliant object containing the next iterated value (if one exists) assigned to a value property and a done property having a boolean value indicating whether the iterator is finished.
  • return: function which closes an iterator and returns a single (optional) argument in an iterator protocol-compliant object.
  • seed: pseudorandom number generator seed. If provided a prng option, the property value is null.
  • seedLength: length of generator seed. If provided a prng option, the property value is null.
  • state: writable property for getting and setting the generator state. If provided a prng option, the property value is null.
  • stateLength: length of generator state. If provided a prng option, the property value is null.
  • byteLength: size (in bytes) of generator state. If provided a prng option, the property value is null.
  • PRNG: underlying pseudorandom number generator.

Notes

  • If an environment supports Symbol.iterator, the returned iterator is iterable.
  • If PRNG state is "shared" (meaning a state array was provided during iterator creation and not copied) and one sets the underlying generator state to a state array having a different length, the iterator 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 iterator 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 iterator and/or PRNGs sharing the PRNG's state array).

Examples

variterator=require('@stdlib/random-iter-exponential');varit;varr;// Create a seeded iterator for generating pseudorandom numbers:it=iterator(2.0,{'seed': 1234,'iter': 10});// Perform manual iteration...while(true){r=it.next();if(r.done){break;}console.log(r.value);}

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.

Community

Chat


License

See LICENSE.

Copyright

Copyright © 2016-2026. The Stdlib Authors.

About

Create an iterator for generating pseudorandom numbers drawn from an exponential distribution.

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Resources

Code of conduct

Contributing

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2 stars

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Strip utm_, fbclid, gclid, etc. from all links on page (function() { var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content', 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid', 'ref', 'ref_src', 'source', 'medium', 'campaign']; function cleanUrl(url) { try { var u = new URL(url, window.location.origin); var changed = false; trackingParams.forEach(function(p) { if (u.searchParams.has(p)) { u.searchParams.delete(p); changed = true; } }); return changed ? u.toString() : url; } catch (e) { return url; } } function cleanLinks() { document.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } cleanLinks(); var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1) { if (node.tagName === 'A') cleanLinks(); node.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + ' GitHub - stdlib-js/random-iter-exponential: Create an iterator for generating pseudorandom numbers drawn from an exponential distribution. · GitHub
Skip to content
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!

Exponential Random Numbers

NPM versionBuild StatusCoverage Status

Create an iterator for generating pseudorandom numbers drawn from an exponential distribution.

Installation

npm install @stdlib/random-iter-exponential

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

variterator=require('@stdlib/random-iter-exponential');

iterator( lambda[, options] )

Returns an iterator for generating pseudorandom numbers drawn from an exponential distribution with rate parameter lambda.

varit=iterator(2.5);// returns <Object>varr=it.next().value;// returns <number>r=it.next().value;// returns <number>r=it.next().value;// returns <number>// ...

If lambda <= 0, the function throws an error.

varit=iterator(-0.5);// throws <TypeError>

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 the state and seed options. In order to seed the returned iterator, 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. Setting this option to true ensures that a returned iterator has exclusive control over its internal pseudorandom number generator state. Default: true.
  • iter: number of iterations.

To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng option.

varminstd=require('@stdlib/random-base-minstd');varit=iterator(2.0,{'prng': minstd.normalized});varr=it.next().value;// returns <number>

To return an iterator having a specific initial state, set the iterator state option.

varbool;varit1;varit2;varr;vari;it1=iterator(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,{'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 option.

varit1=iterator(2.0,{'seed': 12345});varr1=it1.next().value;// returns <number>varit2=iterator(2.0,{'seed': 12345});varr2=it2.next().value;// returns <number>varbool=(r1===r2);// returns true

To limit the number of iterations, set the iter option.

varit=iterator(2.0,{'iter': 2});varr=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:

  • next: function which returns an iterator protocol-compliant object containing the next iterated value (if one exists) assigned to a value property and a done property having a boolean value indicating whether the iterator is finished.
  • return: function which closes an iterator and returns a single (optional) argument in an iterator protocol-compliant object.
  • seed: pseudorandom number generator seed. If provided a prng option, the property value is null.
  • seedLength: length of generator seed. If provided a prng option, the property value is null.
  • state: writable property for getting and setting the generator state. If provided a prng option, the property value is null.
  • stateLength: length of generator state. If provided a prng option, the property value is null.
  • byteLength: size (in bytes) of generator state. If provided a prng option, the property value is null.
  • PRNG: underlying pseudorandom number generator.

Notes

  • If an environment supports Symbol.iterator, the returned iterator is iterable.
  • If PRNG state is "shared" (meaning a state array was provided during iterator creation and not copied) and one sets the underlying generator state to a state array having a different length, the iterator 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 iterator 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 iterator and/or PRNGs sharing the PRNG's state array).

Examples

variterator=require('@stdlib/random-iter-exponential');varit;varr;// Create a seeded iterator for generating pseudorandom numbers:it=iterator(2.0,{'seed': 1234,'iter': 10});// Perform manual iteration...while(true){r=it.next();if(r.done){break;}console.log(r.value);}

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.

Community

Chat


License

See LICENSE.

Copyright

Copyright © 2016-2026. The Stdlib Authors.

About

Create an iterator for generating pseudorandom numbers drawn from an exponential distribution.

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Resources

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Contributing

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Watchers

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Auto-enable theater mode on YouTube (function() { function tryTheater() { var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]'); if (btn && !btn.classList.contains('activated')) { btn.click(); } } // Try immediately tryTheater(); // Try after navigation (SPA) var lastUrl = location.href; setInterval(function() { if (location.href !== lastUrl) { lastUrl = location.href; setTimeout(tryTheater, 500); } }, 1000); // Also try on player load var observer = new MutationObserver(tryTheater); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - stdlib-js/random-iter-exponential: Create an iterator for generating pseudorandom numbers drawn from an exponential distribution. · GitHub
Skip to content
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!

Exponential Random Numbers

NPM versionBuild StatusCoverage Status

Create an iterator for generating pseudorandom numbers drawn from an exponential distribution.

Installation

npm install @stdlib/random-iter-exponential

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

variterator=require('@stdlib/random-iter-exponential');

iterator( lambda[, options] )

Returns an iterator for generating pseudorandom numbers drawn from an exponential distribution with rate parameter lambda.

varit=iterator(2.5);// returns <Object>varr=it.next().value;// returns <number>r=it.next().value;// returns <number>r=it.next().value;// returns <number>// ...

If lambda <= 0, the function throws an error.

varit=iterator(-0.5);// throws <TypeError>

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 the state and seed options. In order to seed the returned iterator, 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. Setting this option to true ensures that a returned iterator has exclusive control over its internal pseudorandom number generator state. Default: true.
  • iter: number of iterations.

To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng option.

varminstd=require('@stdlib/random-base-minstd');varit=iterator(2.0,{'prng': minstd.normalized});varr=it.next().value;// returns <number>

To return an iterator having a specific initial state, set the iterator state option.

varbool;varit1;varit2;varr;vari;it1=iterator(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,{'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 option.

varit1=iterator(2.0,{'seed': 12345});varr1=it1.next().value;// returns <number>varit2=iterator(2.0,{'seed': 12345});varr2=it2.next().value;// returns <number>varbool=(r1===r2);// returns true

To limit the number of iterations, set the iter option.

varit=iterator(2.0,{'iter': 2});varr=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:

  • next: function which returns an iterator protocol-compliant object containing the next iterated value (if one exists) assigned to a value property and a done property having a boolean value indicating whether the iterator is finished.
  • return: function which closes an iterator and returns a single (optional) argument in an iterator protocol-compliant object.
  • seed: pseudorandom number generator seed. If provided a prng option, the property value is null.
  • seedLength: length of generator seed. If provided a prng option, the property value is null.
  • state: writable property for getting and setting the generator state. If provided a prng option, the property value is null.
  • stateLength: length of generator state. If provided a prng option, the property value is null.
  • byteLength: size (in bytes) of generator state. If provided a prng option, the property value is null.
  • PRNG: underlying pseudorandom number generator.

Notes

  • If an environment supports Symbol.iterator, the returned iterator is iterable.
  • If PRNG state is "shared" (meaning a state array was provided during iterator creation and not copied) and one sets the underlying generator state to a state array having a different length, the iterator 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 iterator 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 iterator and/or PRNGs sharing the PRNG's state array).

Examples

variterator=require('@stdlib/random-iter-exponential');varit;varr;// Create a seeded iterator for generating pseudorandom numbers:it=iterator(2.0,{'seed': 1234,'iter': 10});// Perform manual iteration...while(true){r=it.next();if(r.done){break;}console.log(r.value);}

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.

Community

Chat


License

See LICENSE.

Copyright

Copyright © 2016-2026. The Stdlib Authors.

About

Create an iterator for generating pseudorandom numbers drawn from an exponential distribution.

Topics

Resources

Code of conduct

Contributing

Security policy

Stars

2 stars

Watchers

2 watching

Forks

Releases

Sponsor this project

Packages

Used by

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Remove or un-stick sticky/fixed headers that block content (function() { function unstick() { document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) { if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') { el.style.position = 'static'; el.style.top = 'auto'; el.style.zIndex = 'auto'; } }); } unstick(); var observer = new MutationObserver(unstick); observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] }); })(); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' GitHub - stdlib-js/random-iter-exponential: Create an iterator for generating pseudorandom numbers drawn from an exponential distribution. · GitHub
Skip to content
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!

Exponential Random Numbers

NPM versionBuild StatusCoverage Status

Create an iterator for generating pseudorandom numbers drawn from an exponential distribution.

Installation

npm install @stdlib/random-iter-exponential

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

variterator=require('@stdlib/random-iter-exponential');

iterator( lambda[, options] )

Returns an iterator for generating pseudorandom numbers drawn from an exponential distribution with rate parameter lambda.

varit=iterator(2.5);// returns <Object>varr=it.next().value;// returns <number>r=it.next().value;// returns <number>r=it.next().value;// returns <number>// ...

If lambda <= 0, the function throws an error.

varit=iterator(-0.5);// throws <TypeError>

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 the state and seed options. In order to seed the returned iterator, 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. Setting this option to true ensures that a returned iterator has exclusive control over its internal pseudorandom number generator state. Default: true.
  • iter: number of iterations.

To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng option.

varminstd=require('@stdlib/random-base-minstd');varit=iterator(2.0,{'prng': minstd.normalized});varr=it.next().value;// returns <number>

To return an iterator having a specific initial state, set the iterator state option.

varbool;varit1;varit2;varr;vari;it1=iterator(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,{'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 option.

varit1=iterator(2.0,{'seed': 12345});varr1=it1.next().value;// returns <number>varit2=iterator(2.0,{'seed': 12345});varr2=it2.next().value;// returns <number>varbool=(r1===r2);// returns true

To limit the number of iterations, set the iter option.

varit=iterator(2.0,{'iter': 2});varr=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:

  • next: function which returns an iterator protocol-compliant object containing the next iterated value (if one exists) assigned to a value property and a done property having a boolean value indicating whether the iterator is finished.
  • return: function which closes an iterator and returns a single (optional) argument in an iterator protocol-compliant object.
  • seed: pseudorandom number generator seed. If provided a prng option, the property value is null.
  • seedLength: length of generator seed. If provided a prng option, the property value is null.
  • state: writable property for getting and setting the generator state. If provided a prng option, the property value is null.
  • stateLength: length of generator state. If provided a prng option, the property value is null.
  • byteLength: size (in bytes) of generator state. If provided a prng option, the property value is null.
  • PRNG: underlying pseudorandom number generator.

Notes

  • If an environment supports Symbol.iterator, the returned iterator is iterable.
  • If PRNG state is "shared" (meaning a state array was provided during iterator creation and not copied) and one sets the underlying generator state to a state array having a different length, the iterator 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 iterator 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 iterator and/or PRNGs sharing the PRNG's state array).

Examples

variterator=require('@stdlib/random-iter-exponential');varit;varr;// Create a seeded iterator for generating pseudorandom numbers:it=iterator(2.0,{'seed': 1234,'iter': 10});// Perform manual iteration...while(true){r=it.next();if(r.done){break;}console.log(r.value);}

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.

Community

Chat


License

See LICENSE.

Copyright

Copyright © 2016-2026. The Stdlib Authors.

About

Create an iterator for generating pseudorandom numbers drawn from an exponential distribution.

Topics

Resources

Code of conduct

Contributing

Security policy

Stars

2 stars

Watchers

2 watching

Forks

Releases

Sponsor this project

Packages

Used by

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Universal Dark Mode - works on any site (function() { var enabled = true; function applyDarkMode() { if (!enabled) return; // Create style element if it doesn't exist var style = document.getElementById('universal-dark-mode-style'); if (!style) { style = document.createElement('style'); style.id = 'universal-dark-mode-style'; document.head.appendChild(style); } // Dark mode CSS - inverts colors but preserves images/video style.textContent = ' /* Invert everything except media */ html { filter: invert(1) hue-rotate(180deg) !important; background: #1a1a2e !important; } /* Restore images, videos, iframes, canvas */ img, video, iframe, canvas, svg, picture, [style*="background-image"] { filter: invert(1) hue-rotate(180deg) !important; } /* Preserve specific elements that should not be inverted */ .no-dark-mode, .no-dark-mode *, [data-theme="light"], [data-theme="light"], .ace_editor, .ace_editor *, .CodeMirror, .CodeMirror *, .monaco-editor, .monaco-editor *, .markdown-body pre, .markdown-body pre *, .highlight, .highlight *, pre code, pre code * { filter: none !important; } /* Fix common UI elements */ .modal, .popup, .dropdown-menu, .tooltip, .popover { filter: invert(1) hue-rotate(180deg) !important; background: #2d2d44 !important; border-color: #444 !important; } /* Scrollbars */ ::-webkit-scrollbar { background: #1a1a2e !important; } ::-webkit-scrollbar-thumb { background: #444 !important; } ::-webkit-scrollbar-thumb:hover { background: #555 !important; } /* Selection */ ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; } ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; } '; } function removeDarkMode() { var style = document.getElementById('universal-dark-mode-style'); if (style) style.remove(); } // Toggle with Alt+Shift+D document.addEventListener('keydown', function(e) { if (e.altKey && e.shiftKey && e.key === 'D') { e.preventDefault(); enabled = !enabled; if (enabled) { applyDarkMode(); console.log('[Universal Dark Mode] Enabled'); } else { removeDarkMode(); console.log('[Universal Dark Mode] Disabled'); } } }); // Apply on load applyDarkMode(); // Re-apply on dynamic content var observer = new MutationObserver(function(mutations) { if (enabled && !document.getElementById('universal-dark-mode-style')) { applyDarkMode(); } }); observer.observe(document.head, { childList: true }); console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle'); })(); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })(); GitHub - stdlib-js/random-iter-exponential: Create an iterator for generating pseudorandom numbers drawn from an exponential distribution. · GitHub
Skip to content
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!

Exponential Random Numbers

NPM versionBuild StatusCoverage Status

Create an iterator for generating pseudorandom numbers drawn from an exponential distribution.

Installation

npm install @stdlib/random-iter-exponential

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

variterator=require('@stdlib/random-iter-exponential');

iterator( lambda[, options] )

Returns an iterator for generating pseudorandom numbers drawn from an exponential distribution with rate parameter lambda.

varit=iterator(2.5);// returns <Object>varr=it.next().value;// returns <number>r=it.next().value;// returns <number>r=it.next().value;// returns <number>// ...

If lambda <= 0, the function throws an error.

varit=iterator(-0.5);// throws <TypeError>

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 the state and seed options. In order to seed the returned iterator, 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. Setting this option to true ensures that a returned iterator has exclusive control over its internal pseudorandom number generator state. Default: true.
  • iter: number of iterations.

To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng option.

varminstd=require('@stdlib/random-base-minstd');varit=iterator(2.0,{'prng': minstd.normalized});varr=it.next().value;// returns <number>

To return an iterator having a specific initial state, set the iterator state option.

varbool;varit1;varit2;varr;vari;it1=iterator(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,{'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 option.

varit1=iterator(2.0,{'seed': 12345});varr1=it1.next().value;// returns <number>varit2=iterator(2.0,{'seed': 12345});varr2=it2.next().value;// returns <number>varbool=(r1===r2);// returns true

To limit the number of iterations, set the iter option.

varit=iterator(2.0,{'iter': 2});varr=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:

  • next: function which returns an iterator protocol-compliant object containing the next iterated value (if one exists) assigned to a value property and a done property having a boolean value indicating whether the iterator is finished.
  • return: function which closes an iterator and returns a single (optional) argument in an iterator protocol-compliant object.
  • seed: pseudorandom number generator seed. If provided a prng option, the property value is null.
  • seedLength: length of generator seed. If provided a prng option, the property value is null.
  • state: writable property for getting and setting the generator state. If provided a prng option, the property value is null.
  • stateLength: length of generator state. If provided a prng option, the property value is null.
  • byteLength: size (in bytes) of generator state. If provided a prng option, the property value is null.
  • PRNG: underlying pseudorandom number generator.

Notes

  • If an environment supports Symbol.iterator, the returned iterator is iterable.
  • If PRNG state is "shared" (meaning a state array was provided during iterator creation and not copied) and one sets the underlying generator state to a state array having a different length, the iterator 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 iterator 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 iterator and/or PRNGs sharing the PRNG's state array).

Examples

variterator=require('@stdlib/random-iter-exponential');varit;varr;// Create a seeded iterator for generating pseudorandom numbers:it=iterator(2.0,{'seed': 1234,'iter': 10});// Perform manual iteration...while(true){r=it.next();if(r.done){break;}console.log(r.value);}

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

See LICENSE.

Copyright

Copyright © 2016-2026. The Stdlib Authors.

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Create an iterator for generating pseudorandom numbers drawn from an exponential distribution.

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