https://github.com/cantino/walker_method

A Ruby implementation of Walker's Alias Method for quickly sampling from an array with a given probability distribution
https://github.com/cantino/walker_method

Last synced: 17 days ago
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A Ruby implementation of Walker's Alias Method for quickly sampling from an array with a given probability distribution

• Host: GitHub
• URL: https://github.com/cantino/walker_method
• Owner: cantino
• License: mit
• Created: 2013-03-05T06:02:11.000Z (over 11 years ago)
• Default Branch: master
• Last Pushed: 2013-03-16T20:10:53.000Z (over 11 years ago)
• Last Synced: 2024-10-14T20:34:46.120Z (30 days ago)
• Language: Ruby
• Homepage:
• Size: 109 KB
• Stars: 71
• Watchers: 5
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt

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README

        
# WalkerMethod

Walker's Alias Method is an O(1) algorithm for selecting elements from an array given a weighted distribution.

For example, let's say you want to return `:win` 60% of the time, `:lose` 20% of the time, and `:tie` 20% of the time.  You could fill an array with

6 examples of `:win` and 2 examples each of `:lose` and `:tie`, then pick a random element.  You could also use ranges, picking a random number

between 0.0 and 1.0 and returning `:win` when the number is below 0.6, `:lose` if the number is below 0.8, and `:tie` otherwise.  But, these algorithms are still O(n).

You can do better by using a heap or binary search tree, but Walker's Alias Method is better still, with a constant runtime once an O(n)

pre-computation phase has completed.  For this example, you could do:

    selector = WalkerMethod.new([:win, :lose, :tie], [60, 20, 20])

    selector.random

This implementation is a port of http://code.activestate.com/recipes/576564-walkers-alias-method-for-random-objects-with-diffe/ from Python to Ruby.  There is also a [Node.js implementation](https://github.com/ThoughtLeadr/Walker-Random-Node).

## Speed

It's FAST and simple.  It samples from a 50,000 word frequency dictionary 10,000 times in 1.2 milliseconds.

## Installation

Add this line to your application's Gemfile:

    gem 'walker_method'

And then execute:

    $ bundle

Or install it yourself as:

    $ gem install walker_method

## Usage

    # Sampling from an English word frequency dictionary care of http://invokeit.wordpress.com/frequency-word-lists

    words = ["you", "the", "i", "to", "a", "and", "it", "of", "that", "in", "is", "me", "what", "this", "for", "my", "on", "your", "we", "have", "do", "no", "don't", "are", "be"]

    freqs = [4621939, 3957465, 3476773, 2873389, 2551033, 1775393, 1693042, 1531878, 1323823, 1295198, 1242191, 1208959, 1071825, 961194, 898671, 877684, 867296, 834953, 819499, 812625, 799991, 788200, 764177, 743194, 743014]

    selector = WalkerMethod.new(words, weights)

    selector.random

    # => "and"

## Contributing

1. Fork it

2. Create your feature branch (`git checkout -b my-new-feature`)

3. Commit your changes (`git commit -am 'Add some feature'`)

4. Push to the branch (`git push origin my-new-feature`)

5. Create new Pull Request