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@keystonehq/alias-sampling
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A Node.js module for efficient sampling from a discrete probability distribution using the alias method.
Readme
A JavaScript library for efficient sampling of random values from a discrete probability distribution using the Walker-Vose alias method, provided by KeystoneHQ.
Install the library using yarn:
yarn add @keystonehq/alias-sampling
Or npm:
npm install @keystonehq/alias-sampling
To use the library, first import the sample
function and then create a sampler with a given probability distribution and optionally an array of outcomes. You can then generate random samples using the .next()
method.
import sample from '@keystonehq/alias-sampling';
// Create a sampler with specified probabilities and outcomes
var s = sample([0.5, 0.25, 0.25], ['A', 'B', 'C']);
// Generate a single random outcome
console.log(s.next()); // => 'A', 'B', or 'C' according to specified probabilities
import sample from '@keystonehq/alias-sampling';
// Create a sampler with specified probabilities
var s = sample([0.5, 0.25, 0.25], [10, 20, 30]);
// Generate multiple random samples
console.log(s.next(1000)); // => an array of 1000 random samples
import sample from '@keystonehq/alias-sampling';
// Create a sampler without specifying outcomes (defaults to indices)
var s = sample([0.5, 0.25, 0.25]);
// Generate a single random index
console.log(s.next()); // => 0, 1, or 2 with the specified probabilities
import sample from '@keystonehq/alias-sampling';
// Custom random generator function
var rand = Math.random;
// Create a sampler with specified probabilities and custom random generator
var s = sample([0.5, 0.25, 0.25], null, rand);
// Generate a random index using the custom random generator
console.log(s.next()); // => 0, 1, or 2 with the specified probabilities
FAQs
A Node.js module for efficient sampling from a discrete probability distribution using the alias method.
We found that @keystonehq/alias-sampling demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 5 open source maintainers collaborating on the project.
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