class Markov::Chain(LinkType)

• Markov::Chain(LinkType)
• Reference
• Object

Overview

A Chain is a vehicle for generating probable sequences of type LinkType

Defined in:

Constructors

• .new(transition_table : TransitionTable(LinkType), seed : LinkType | Nil = nil)

  For larger processes, you'll want to externally train a TransitionTable then pass it in as an argument.

• .new(sample : Array(LinkType), seed : LinkType = (sample.sample(1)).first)

  If you have a small (Array-sized) data set, you can pass it as sample and a TransitionTable will be constructed for you with the sample data.

• .new(pull : JSON::PullParser)

  Makes it possible to use #to_json and #from_json (see Crystal docs)

Instance Method Summary

• #generate(count : Int32)

  Generates a probable, sequential Array of LinkType elements of count length

• #generated

  Returns an ordered Array(LinkType) of all LinkType elements generated

• #next : LinkType

  Generates the next probable LinkType element

• #on_dead_end(&block : Proc(TransitionTable(LinkType), Chain(LinkType), Exception, LinkType)) : Proc(TransitionTable(LinkType), Chain(LinkType), Exception, LinkType)

  Sets an exception handler for EmptyTransitionMatrixException when Chain instance reaches a dead end while using Chain#generate or Chain#next.

• #seed

  Returns #seed element.

• #transition_table

  Returns the trained instance of TransitionTable

Constructor Detail

Instance Method Detail

c = Markov::Chain(String).new sample: ["Koala", "Kangaroo"] of String, seed: "Kangaroo"
c.on_dead_end do |transition_table, chain, exception|
  "Koala"
end
c.next() #=> "Koala"
c.next() #=> "Kangaroo"
c.next() #=> "Koala"