Class: Mjai::Manue::HoraProbabilityEstimator

Inherits:

Object

• Object
• Mjai::Manue::HoraProbabilityEstimator

Defined in:

lib/mjai/manue/hora_probability_estimator.rb

Defined Under Namespace

Classes: Criterion, Metrics, Scene, Tehais

Class Method Summary

• .estimate(archive_paths, output_metrics_path) ⇒ Object

Instance Method Summary

• #adjust ⇒ Object
• #adjust_for_sequence(criteria) ⇒ Object
• #dump_metrics_map ⇒ Object
• #get_hora_prob(num_remain_turns, shanten) ⇒ Object
• #get_scene(params) ⇒ Object
• #initialize(metrics_path) ⇒ HoraProbabilityEstimator constructor

  A new instance of HoraProbabilityEstimator.

Constructor Details

#initialize(metrics_path) ⇒ HoraProbabilityEstimator

Returns a new instance of HoraProbabilityEstimator.

# File 'lib/mjai/manue/hora_probability_estimator.rb', line 263

def initialize(metrics_path)
  open(metrics_path, "rb") do |f|
    @metrics_map = Marshal.load(f)
  end
  adjust()
end

Class Method Details

.estimate(archive_paths, output_metrics_path) ⇒ Object

# File 'lib/mjai/manue/hora_probability_estimator.rb', line 197

def self.estimate(archive_paths, output_metrics_path)
  freqs_map = {}
  archive_paths.each_with_progress() do |path|
    p [:path, path]
    archive = Archive.load(path)
    criteria_map = nil
    winners = nil
    archive.each_action() do |action|
      next if action.actor && ["ASAPIN", "（≧▽≦）"].include?(action.actor.name)
      archive.dump_action(action)
      case action.type
        when :start_kyoku
          criteria_map = {}
          winners = []
        when :dahai
          shanten_analysis = ShantenAnalysis.new(
              action.actor.tehais,
              nil,
              ShantenAnalysis::ALL_TYPES,
              action.actor.tehais.size,
              false)
          criterion = Criterion.new(
              archive.num_pipais / 4.0,
              ShantenAnalysis.new(action.actor.tehais).shanten)
          p [:criterion, criterion]
          criteria_map[action.actor] ||= []
          criteria_map[action.actor].push(criterion)
        when :hora
          winners.push(action.actor)
        when :end_kyoku
          num_remain_turns = archive.num_pipais / 4.0
          for player, criteria in criteria_map
            for criterion in criteria
              if winners.include?(player)
                if criterion.num_remain_turns - num_remain_turns <= 2.0
                  result = :quick_hora
                else
                  result = :slow_hora
                end
              else
                result = :no_hora
              end
              normalized_criterion = Criterion.new(
                  criterion.num_remain_turns.to_i(),
                  criterion.shanten)
              #p [player, normalized_criterion, result]
              freqs_map[normalized_criterion] ||= Hash.new(0)
              freqs_map[normalized_criterion][:total] += 1
              freqs_map[normalized_criterion][result] += 1
            end
          end
      end
    end
  end
  metrics_map = {}
  for criterion, freqs in freqs_map
    metrics_map[criterion] = Metrics.new(
        (freqs[:quick_hora] + freqs[:slow_hora]).to_f() / freqs[:total],
        freqs[:quick_hora].to_f() / freqs[:total],
        freqs[:total])
  end
  open(output_metrics_path, "wb") do |f|
    Marshal.dump(metrics_map, f)
  end
end

Instance Method Details

#adjust ⇒ Object

# File 'lib/mjai/manue/hora_probability_estimator.rb', line 297

def adjust()
  for shanten in 0..6
    adjust_for_sequence(17.downto(0).map(){ |n| Criterion.new(n, shanten) })
  end
  for num_remain_turns in 0..17
    adjust_for_sequence((0..6).map(){ |s| Criterion.new(num_remain_turns, s) })
  end
end

#adjust_for_sequence(criteria) ⇒ Object

# File 'lib/mjai/manue/hora_probability_estimator.rb', line 306

def adjust_for_sequence(criteria)
  prev_prob = 1.0
  for criterion in criteria
    metrics = @metrics_map[criterion]
    if !metrics || metrics.hora_prob > prev_prob
      #p [criterion, metrics && metrics.hora_prob, prev_prob]
      @metrics_map[criterion] = Metrics.new(prev_prob, nil, nil)
    end
    prev_prob = @metrics_map[criterion].hora_prob
  end
end

#dump_metrics_map ⇒ Object

# File 'lib/mjai/manue/hora_probability_estimator.rb', line 284

def dump_metrics_map()
  puts("\#turns\tshanten\thora_p\tsamples")
  for criterion, metrics in @metrics_map.sort_by(){ |c, m| [c.num_remain_turns, c.shanten] }
  #for criterion, metrics in @metrics_map.sort_by(){ |c, m| [c.shanten, c.num_remain_turns] }
    puts("%d\t%d\t%.3f\t%p" % [
        criterion.num_remain_turns,
        criterion.shanten,
        metrics.hora_prob,
        metrics.num_samples,
    ])
  end
end

#get_hora_prob(num_remain_turns, shanten) ⇒ Object

# File 'lib/mjai/manue/hora_probability_estimator.rb', line 274

def get_hora_prob(num_remain_turns, shanten)
  if shanten <= -1
    return 1.0
  elsif num_remain_turns < 0
    return 0.0
  else
    return @metrics_map[Criterion.new(num_remain_turns, shanten)].hora_prob
  end
end

#get_scene(params) ⇒ Object

# File 'lib/mjai/manue/hora_probability_estimator.rb', line 270

def get_scene(params)
  return Scene.new(self, params)
end