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Ipsumizer

Ipsumizer generates random sentences based on the sample text it is initialized with.

Synopsis

require 'ipsumizer'

# sample text -- the Aeneid (only first lines shown)
text = <<-END
Arma virumque cano, Troiae qui primus ab oris
Italiam, fato profugus, Laviniaque venit
litora, multum ille et terris iactatus et alto
vi superum saevae memorem Iunonis ob iram;
multa quoque et bello passus, dum conderet urbem,
inferretque deos Latio, genus unde Latinum,
Albanique patres, atque altae moenia Romae.

Musa, mihi causas memora, quo numine laeso,
quidve dolens, regina deum tot volvere casus
insignem pietate virum, tot adire labores
impulerit. Tantaene animis caelestibus irae?

...

END

ip = Ipsumizer.new text

ip.speak                 # "Illi ingere glaebae; faciat tempora magno miserae lustri non data dum excutitur, dona Cupido Tyrius artit, et prodimus urbine Byrsam, neque, Troesque corpora mortalis, foret Troiaque qui taliam rabili portuna viros inhumati unda dextra, donis?"
ip.speak                 # "'Rex erat pectore pontus, nostrata pelago pectore tot captas epulis Achates et patres, haere duce reconderat, ut supplexu Aeneas, Tyria fluctus antiquentem tum excidio Libyae: sic ore cadis agminem." 
ip.speak                 # "Adsit lacrimisque matrem arrectisque ruunt et alas et placidam Iunonis?"

ip = Ipsumizer.new text, prefix: 2

ip.speak                 # "Hissalia ma cubem gerefix, Iuripsilis ocubvolut ciantensii, iturue perbata gerecurore Iulcelacriscenthomasumin lo.]"

Description

Ipsumizer builds a "character language model" based on the sample sentences you give it. This means it discovers the probability that a particular letter follows particular sequences of preceding letters within a sentence. "Letters" in this case include the beginning of the sentence and the end. Given this information it can build a new sentence like so:

  1. Pick the starting character based on the frequence of starting letters in the sample sentences
  2. Pick the next character based on the frequency of second characters given the first
  3. Pick the third character based on the frequency of the preceding two
  4. etc.

Once it reaches its "prefix" limit, it trims the preceding sequence to this length. The longer the sequence, the less creative Ipsumizer will be and the more the generated text will resemble the sample. At some length it will stop generating any novel sentences and will simply return some random sentence from the sample it ingested.

Sentencing

If you give Ipsumizer an array as the first argument to its initializer it will assume these are the sample sentences. Alternatively, if you give it a String it will use a regular expression to splits this string into sample sentences. As is generally the case with regular expression parsing, this won't always be as sophisticated as you might like. You can either do the sentencing yourself beforehand or provide your own sentencing regexp, like so:

ip = Ipsumizer.new text, sentencer: /([.?!])/

Note the capturing group around the expression. Ipsumizer assumes sentencing expressions capture their separators. It will look for the these in the split output, therefore, and glue them back onto their sentences.

Normalization

The only normalization Ipsumizer provides by default is the stripping of whitespace and the conversion of all internal whitespace into ' '. If you want to remove macrons, for example, you need to do it to the text yourself.

Methods

initialize(text, sentencer: DEFAULT_SENTENCER, prefix: DEFAULT_PREFIX)

The text parameter is either a string or an array of strings. In the former case, the string will be split into sentences using the sentencer pattern. The prefix parameter is a non-negative integer. The bigger the prefix, the more faithful generated sentences will be to the original.

speak

Generate a random sentence.

sentence(text)

Split the text parameter into sentences using the Ipsumizer's sentence boundary pattern.

sentencer

Accessor for the sentencer pattern.

prefix

Accessor for the prefix length.

Defaults and Constants

  DEFAULT_SENTENCER = Regexp.new %r{([.!?][.!?\p{Final_Punctuation}\p{Close_Punctuation}"\s]*)}

  DEFAULT_PREFIX = 4

Installation

Add this line to your application's Gemfile:

gem 'ipsumizer'

And then execute:

$ bundle

Or install it yourself as:

$ gem install ipsumizer

Development

After checking out the repo, run bin/setup to install dependencies. Then, run rake test 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.

Contributing

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

License

The gem is available as open source under the terms of the MIT License.

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generates text mimicking a sample

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