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 collapse
Instance Method Summary collapse
- #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.
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# 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
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# 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
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# 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
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# 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
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# 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
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# 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 |