Entropic

Entropic trains and predicts entropy of strings based on character n-gram models. For example:

require 'entropic'
>> m = Entropic::Model.read(open('https://raw.githubusercontent.com/willf/entropy/master/data/google_books_2.tsv')); true
=> true
>> m.entropy("entropy")
=> 10.15243685946792
>> m.entropy("yportne")
=> 11.048928592721346

The string 'yportne' is much less likely than the string 'entropy'.

You can also train a model, using strings one per line.

>> n = Entropic::Model.new(2); true
=> true
>> File.open('/tmp/training.txt') {|f| n.train(f)}; true
=> true
>> n.entropy('love')
=> 5.132072254636385

You can also train a model, using strings and a count of the number of times it appers, tab separated.

>> o = Entropic::Model.new(2); true
=> true
>> File.open('/tmp/training_with_counts.txt') {|f| o.train_with_multiplier(f)}; true
=> true
>> o.entropy('love')
=> 5.132072254636385

You can also dump a model, to be read later.

>> File.open('/tmp/save.tsv','w') {|f| o.dump(f)}; true
=> true

Add this line to your application's Gemfile:

gem 'entropic'

And then execute:

$ bundle

Or install it yourself as:

$ gem install entropic

After checking out the repo, run bin/setup to install dependencies. Then, run rake spec to run the tests. You can also run bin/console for an interactive prompt that will allow you to experiment.

To install this gem onto your local machine, run bundle exec rake install. To release a new version, update the version number in version.rb, and then run bundle exec rake release, which will create a git tag for the version, push git commits and tags, and push the .gem file to rubygems.org.

Bug reports and pull requests are welcome on GitHub at https://github.com/willf/entropic.