You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: indexes.rb
    path of file: ./repos/picky/server/lib/picky/query
    
    the code of the file until where you have to start completion: module Picky

  module Query

    # The query indexes class bundles indexes given to a query.
    #
    # Example:
    #   # If you call
    #   Search.new dvd_index, mp3_index, video_index
    #
    #   # What it does is take the three given (API-) indexes and
    #   # bundle them in an index bundle.
    #
    class Indexes
      
      forward :size, :first, :to => :@indexes
      
      attr_reader :indexes,
                  :ignored_categories,
                  :ignored_allocations,
                  :exclusive_allocations

      # Creates a new Query::Indexes.
      #
      # Its job is to generate all possible combinations.
      # Note: We cannot mix memory and redis indexes just 
    
      def ignore_allocations *qualifier_arrays
        @ignored_allocations ||= []
        @ignored_allocations += qualifier_arrays #.map do |qualifier_array|
          # qualifier_array.map { |qualifier| @qualifier_mapper.map qualifier }
        # end.compact
        @ignored_allocations.uniq!
      end
      
      # Exclusively keep the allocations with the given qualifiers.
      #
      def keep_allocations *qualifier_arrays
        @exclusive_allocations ||= []
        @exclusive_allocations += qualifier_arrays #.map do |qualifier_array|
          # qualifier_array.map { |qualifier| @qualifier_mapper.map qualifier }
        # end.compact
        @exclusive_allocations.uniq!
      end

      # Returns a number of prepared (sorted, reduced etc.) allocations for the given tokens.
      #
      def prepared_allocations_for tokens, boosts = {}, amount = nil
        allocations = allocations_for tokens

        # Score the allocations using weights as bias.
        #
        # Note: Before we can sort them we need to score them.
        #
        allocations.calculate_score boosts

        # Filter the allocations â€“ ignore/only.
        #
        allocations.keep_allocations exclusive_allocations if exclusive_allocations
        allocations.remove_allocations ignored_allocations if ignored_allocations

        # Sort the allocations.
        # (allocations are sorted according to score, highest to lowest)
        #
        # Before we can chop off unimportant allocations, we need to sort them.
        #
        allocations.sort!
        
        # allocations.remove_allocations ignored_allocations if ignored_allocations
        
        # Reduce the amount of allocations.
        #
        # Before we remove categories, we should reduce the amount of allocations.
        #
        allocations.reduce_to amount if amount

        # Remove categories from allocations.
        #
        allocations.remove_categories ignored_categories if ignored_categories

        allocations
      end
      # Returns a number of possible allocations for the given tokens.
      #
      def allocations_for tokens
        Allocations.new allocations_ary_for(tokens)
      end
      def allocations_ary_for tokens
        indexes.inject([]) do |allocations, index|
          allocations + allocation_for(tokens, index)
        end
      end
      def allocation_for tokens, index
        # Expand the combinations.
        #
        possible_combinations = tokens.possible_combinations_in index.categories

        # Generate all possible combinations.
        #
        all_possible_combinations = expand_combinations_from possible_combinations

        # Add the wrapped possible allocations to the ones we already have.
        #
        all_possible_combinations.map! do |expanded_combinations|
          Allocation.new index, Query::Combinations.new(expanded_combinations)
        end
      end

      # This is the core of the search engine. No kidding.
      #
      # Gets an array of
      # [
      #  [<combinations for token1>],
      #  [<combinations for token2>],
      #  [<combinations for token3>]
      # ]
      #
      # Generates all possible allocations of combinations.
      # [
      #  [first combination of token1, first c of t2, first c of t3],
      #  [first combination of token1, first c of t2, second c of t3]
      #  ...
      # ]
      #
      # Generates all possible combinations of array elements:
      # [1,2,3] x [a,b,c] x [k,l,m] => [[1,a,k], [1,a,l], [1,a,m], [1,b,k], [1,b,l], [1,b,m], [1,c,k], ..., [3,c,m]]
      # Note: Also calculates the weights and sorts them accordingly.
      #
      # Note: This is a heavily optimized ruby version.
      #
      # Works like this:
      # [1,2,3], [a,b,c], [k,l,m] are expanded to
      #  group mult: 1
      #  <- single mult ->
      # [1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3] = 27 elements
      #  group mult: 3
      #  <- -> s/m
      # [a,a,a,b,b,b,c,c,c,a,a,a,b,b,b,c,c,c,a,a,a,b,b,b,c,c,c] = 27 elements
      #  group mult: 9
      #  <> s/m
      # [k,l,m,k,l,m,k,l,m,k,l,m,k,l,m,k,l,m,k,l,m,k,l,m,k,l,m] = 27 elements
      #
      # It is then recombined, where
      # [
      #  [a,a,b,b,c,c]
      #  [d,e,d,e,d,e]
      # ]
      # becomes
      # [
      #  [a,d],
      #  [a,e],
      #  [b,d],
      #  [b,e],
      #  [c,d],
      #  [c,e]
      # ]
      #
      # Note: Not using transpose as it is slower.
      #
      # Returns nil if there are no combinations.
      #
      # Note: Of course I could split this method up into smaller
      #       ones, but I guess I am a bit sentimental.
      #
      def expand_combinations_from possible_combinations
        # If an element has size 0, this means one of the
        # tokens could not be allocated.
        #
        return [] if possible_combinations.any? { |possible_combination| possible_combination.empty? }

        # Generate the first multiplicator "with which" (well, not quite) to multiply the smallest amount of combinations.
        #
        single_mult = possible_combinations.inject(1) { |total, combinations| total * combinations.size }

        # Initialize a group multiplicator.
        #
        group_mult = 1

        # The expanding part to line up the combinations
        # for later combination in allocations.
        #
        possible_combinations.collect! do |combinations|

          # Get the size of the combinations of the first token.
          #
          combinations_size = combinations.size

          # Special case: If there is no combination for one of the tokens.
          #               In that case, we just use the same single mult for
          #               the next iteration.
          #               If there are combinations, we divide the single mult
          #               by the number of combinations.
          #
          single_mult /= combinations_size unless combinations_size.zero?

          # Expand each combination by the single mult:
          # [a,b,c]
          # [a,a,a,  b,b,b,  c,c,c]
          # Then, expand the result by the group mult:
          # [a,a,a,b,b,b,c,c,c,  a,a,a,b,b,b,c,c,c,  a,a,a,b,b,b,c,c,c]
          #
          combinations = combinations.inject([]) do |total, combination|
            total + Array.new(single_mult, combination)
          end * group_mult

          # Multiply the group mult by the combinations size,
          # since the next combinations' single mult is smaller
          # and we need to adjust for that.
          #
          group_mult = group_mult * combinations_size

          # Return the combinations.
          #
          combinations
        end

        return [] if possible_combinations.empty?

        possible_combinations.shift.zip *possible_combinations
      end

    end

  end

end