#!/usr/bin/env ruby
#--
# tsort.rb - provides a module for topological sorting and strongly connected components.
#++
#

#
# TSort implements topological sorting using Tarjan's algorithm for
# strongly connected components.
#
# TSort is designed to be able to be used with any object which can be interpreted
# as a directed graph.
# TSort requires two methods to interpret an object as a graph:
# tsort_each_node and tsort_each_child:
#
# * tsort_each_node is used to iterate for all nodes over a graph.
# * tsort_each_child is used to iterate for child nodes of a given node.
#
# The equality of nodes are defined by eql? and hash since
# TSort uses Hash internally.
#
# == A Simple Example
#
# The following example demonstrates how to mix the TSort module into an
# existing class (in this case, Hash). Here, we're treating each key in
# the hash as a node in the graph, and so we simply alias the required
# #tsort_each_node method to Hash's #each_key method. For each key in the
# hash, the associated value is an array of the node's child nodes. This
# choice in turn leads to our implementation of the required #tsort_each_child
# method, which fetches the array of child nodes and then iterates over that
# array using the user-supplied block.
#
#  require 'tsort'
#
#  class Hash
#    include TSort
#    alias tsort_each_node each_key
#    def tsort_each_child(node, &block)
#      fetch(node).each(&block)
#    end
#  end
#
#  {1=>[2, 3], 2=>[3], 3=>[], 4=>[]}.tsort
#  #=> [3, 2, 1, 4]
#
#  {1=>[2], 2=>[3, 4], 3=>[2], 4=>[]}.strongly_connected_components
#  #=> [[4], [2, 3], [1]]
#
# == A More Realistic Example
#
# A very simple `make' like tool can be implemented as follows:
#
#  require 'tsort'
#
#  class Make
#    def initialize
#      @dep = {}
#      @dep.default = []
#    end
#
#    def rule(outputs, inputs=[], &block)
#      triple = [outputs, inputs, block]
#      outputs.each {|f| @dep[f] = [triple]}
#      @dep[triple] = inputs
#    end
#
#    def build(target)
#      each_strongly_connected_component_from(target) {|ns|
#        if ns.length != 1
#          fs = ns.delete_if {|n| Array === n}
#          raise TSort::Cyclic.new("cyclic dependencies: #{fs.join ', '}")
#        end
#        n = ns.first
#        if Array === n
#          outputs, inputs, block = n
#          inputs_time = inputs.map {|f| File.mtime f}.max
#          begin
#            outputs_time = outputs.map {|f| File.mtime f}.min
#          rescue Errno::ENOENT
#            outputs_time = nil
#          end
#          if outputs_time == nil ||
#             inputs_time != nil && outputs_time <= inputs_time
#            sleep 1 if inputs_time != nil && inputs_time.to_i == Time.now.to_i
#            block.call
#          end
#        end
#      }
#    end
#
#    def tsort_each_child(node, &block)
#      @dep[node].each(&block)
#    end
#    include TSort
#  end
#
#  def command(arg)
#    print arg, "\n"
#    system arg
#  end
#
#  m = Make.new
#  m.rule(%w[t1]) { command 'date > t1' }
#  m.rule(%w[t2]) { command 'date > t2' }
#  m.rule(%w[t3]) { command 'date > t3' }
#  m.rule(%w[t4], %w[t1 t3]) { command 'cat t1 t3 > t4' }
#  m.rule(%w[t5], %w[t4 t2]) { command 'cat t4 t2 > t5' }
#  m.build('t5')
#
# == Bugs
#
# * 'tsort.rb' is wrong name because this library uses
#   Tarjan's algorithm for strongly connected components.
#   Although 'strongly_connected_components.rb' is correct but too long.
#
# == References
#
# R. E. Tarjan, "Depth First Search and Linear Graph Algorithms",
# <em>SIAM Journal on Computing</em>, Vol. 1, No. 2, pp. 146-160, June 1972.
#

module TSort
  class Cyclic < StandardError
  end

  #
  # Returns a topologically sorted array of nodes.
  # The array is sorted from children to parents, i.e.
  # the first element has no child and the last node has no parent.
  #
  # If there is a cycle, TSort::Cyclic is raised.
  #
  def tsort
    result = []
    tsort_each {|element| result << element}
    result
  end

  #
  # The iterator version of the #tsort method.
  # <tt><em>obj</em>.tsort_each</tt> is similar to <tt><em>obj</em>.tsort.each</tt>, but
  # modification of _obj_ during the iteration may lead to unexpected results.
  #
  # #tsort_each returns +nil+.
  # If there is a cycle, TSort::Cyclic is raised.
  #
  def tsort_each # :yields: node
    each_strongly_connected_component {|component|
      if component.size == 1
        yield component.first
      else
        raise Cyclic.new("topological sort failed: #{component.inspect}")
      end
    }
  end

  #
  # Returns strongly connected components as an array of arrays of nodes.
  # The array is sorted from children to parents.
  # Each elements of the array represents a strongly connected component.
  #
  def strongly_connected_components
    result = []
    each_strongly_connected_component {|component| result << component}
    result
  end

  #
  # The iterator version of the #strongly_connected_components method.
  # <tt><em>obj</em>.each_strongly_connected_component</tt> is similar to
  # <tt><em>obj</em>.strongly_connected_components.each</tt>, but
  # modification of _obj_ during the iteration may lead to unexpected results.
  #
  #
  # #each_strongly_connected_component returns +nil+.
  #
  def each_strongly_connected_component # :yields: nodes
    id_map = {}
    stack = []
    tsort_each_node {|node|
      unless id_map.include? node
        each_strongly_connected_component_from(node, id_map, stack) {|c|
          yield c
        }
      end
    }
    nil
  end

  #
  # Iterates over strongly connected component in the subgraph reachable from 
  # _node_.
  #
  # Return value is unspecified.
  #
  # #each_strongly_connected_component_from doesn't call #tsort_each_node.
  #
  def each_strongly_connected_component_from(node, id_map={}, stack=[]) # :yields: nodes
    minimum_id = node_id = id_map[node] = id_map.size
    stack_length = stack.length
    stack << node

    tsort_each_child(node) {|child|
      if id_map.include? child
        child_id = id_map[child]
        minimum_id = child_id if child_id && child_id < minimum_id
      else
        sub_minimum_id =
          each_strongly_connected_component_from(child, id_map, stack) {|c|
            yield c
          }
        minimum_id = sub_minimum_id if sub_minimum_id < minimum_id
      end
    }

    if node_id == minimum_id
      component = stack.slice!(stack_length .. -1)
      component.each {|n| id_map[n] = nil}
      yield component
    end

    minimum_id
  end

  #
  # Should be implemented by a extended class.
  #
  # #tsort_each_node is used to iterate for all nodes over a graph.
  #
  def tsort_each_node # :yields: node
    raise NotImplementedError.new
  end

  #
  # Should be implemented by a extended class.
  #
  # #tsort_each_child is used to iterate for child nodes of _node_.
  #
  def tsort_each_child(node) # :yields: child
    raise NotImplementedError.new
  end
end

if __FILE__ == $0
  require 'test/unit'

  class TSortHash < Hash # :nodoc:
    include TSort
    alias tsort_each_node each_key
    def tsort_each_child(node, &block)
      fetch(node).each(&block)
    end
  end

  class TSortArray < Array # :nodoc:
    include TSort
    alias tsort_each_node each_index
    def tsort_each_child(node, &block)
      fetch(node).each(&block)
    end
  end

  class TSortTest < Test::Unit::TestCase # :nodoc:
    def test_dag
      h = TSortHash[{1=>[2, 3], 2=>[3], 3=>[]}]
      assert_equal([3, 2, 1], h.tsort)
      assert_equal([[3], [2], [1]], h.strongly_connected_components)
    end

    def test_cycle
      h = TSortHash[{1=>[2], 2=>[3, 4], 3=>[2], 4=>[]}]
      assert_equal([[4], [2, 3], [1]],
        h.strongly_connected_components.map {|nodes| nodes.sort})
      assert_raise(TSort::Cyclic) { h.tsort }
    end

    def test_array
      a = TSortArray[[1], [0], [0], [2]]
      assert_equal([[0, 1], [2], [3]],
        a.strongly_connected_components.map {|nodes| nodes.sort})

      a = TSortArray[[], [0]]
      assert_equal([[0], [1]],
        a.strongly_connected_components.map {|nodes| nodes.sort})
    end
  end

end

