# Author::    Sergio Fierens (Implementation only)
# License::   MPL 1.1
# Project::   ai4r
# Url::       http://www.ai4r.org/
#
# You can redistribute it and/or modify it under the terms of 
# the Mozilla Public License version 1.1  as published by the 
# Mozilla Foundation at http://www.mozilla.org/MPL/MPL-1.1.txt

require 'set'
require File.dirname(__FILE__) + '/../data/data_set'
require File.dirname(__FILE__) + '/../classifiers/classifier'

module Ai4r
  module Classifiers

    include Ai4r::Data
    
    # = Introduction
    # 
    # A fast classifier algorithm, created by Lucio de Souza Coelho 
    # and Len Trigg.
    class Hyperpipes < Classifier
      
      attr_reader :data_set, :pipes

      # Build a new Hyperpipes classifier. You must provide a DataSet instance
      # as parameter. The last attribute of each item is considered as 
      # the item class.
      def build(data_set)
        data_set.check_not_empty
        @data_set = data_set
        @domains = data_set.build_domains
        
        @pipes = {}
        @domains.last.each {|cat| @pipes[cat] = build_pipe(@data_set)}
        @data_set.data_items.each {|item| update_pipe(@pipes[item.last], item) }
        
        return self
      end
      
      # You can evaluate new data, predicting its class.
      # e.g.
      #   classifier.eval(['New York',  '<30', 'F'])  # => 'Y'      
      def eval(data)
        votes = Hash.new {0}
        @pipes.each do |category, pipe|
          pipe.each_with_index do |bounds, i|
            if data[i].is_a? Numeric
              votes[category]+=1 if data[i]>=bounds[:min] && data[i]<=bounds[:max]
            else
              votes[category]+=1 if bounds[data[i]]
            end
          end
        end
        return votes.to_a.max {|x, y| x.last <=> y.last}.first
      end
      
      # This method returns the generated rules in ruby code.
      # e.g.
      #   
      #   classifier.get_rules
      #     # =>  if age_range == '<30' then marketing_target = 'Y'
      #           elsif age_range == '[30-50)' then marketing_target = 'N'
      #           elsif age_range == '[50-80]' then marketing_target = 'N'
      #           end
      #
      # It is a nice way to inspect induction results, and also to execute them:  
      #     marketing_target = nil
      #     eval classifier.get_rules   
      #     puts marketing_target
      #       # =>  'Y'
      def get_rules
        rules = []
        rules << "votes = Hash.new {0}"
        data = @data_set.data_items.first
        labels = @data_set.data_labels.collect {|l| l.to_s}
        @pipes.each do |category, pipe|
          pipe.each_with_index do |bounds, i|
            rule = "votes['#{category}'] += 1 "
            if data[i].is_a? Numeric
              rule += "if #{labels[i]} >= #{bounds[:min]} && #{labels[i]} <= #{bounds[:max]}"
            else
              rule += "if #{bounds.inspect}[#{labels[i]}]"
            end
            rules << rule
          end
        end
        rules << "#{labels.last} = votes.to_a.max {|x, y| x.last <=> y.last}.first"
        return rules.join("\n")
      end
      
      protected

      def build_pipe(data_set)
        data_set.data_items.first[0...-1].collect do |att|
          if att.is_a? Numeric
            {:min=>1.0/0, :max=>-1.0/0}
          else
            Hash.new(false)
          end
        end
      end
      
      def update_pipe(pipe, data_item)
        data_item[0...-1].each_with_index do |att, i|
          if att.is_a? Numeric
            pipe[i][:min] = att if att < pipe[i][:min]
            pipe[i][:max] = att if att > pipe[i][:max]
          else
            pipe[i][att] = true
          end  
        end
      end
      
    end
  end
end