source: branches/LearningClassifierSystems/HeuristicLab.Optimization.Operators.LCS/3.3/GAssist/DefaultRule/AutoDefaultRule.cs @ 13401

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
 *
 * This file is part of HeuristicLab.
 *
 * HeuristicLab is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * HeuristicLab is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
 */
#endregion

using System;
using System.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Optimization.Operators.LCS.DefaultRule {
  [Item("AutoDefaultRule", "Description missing")]
  [StorableClass]
  public class AutoDefaultRule : DefaultRuleOperator, IStochasticOperator {

    #region Parameter Properties
    public ILookupParameter<IRandom> RandomParameter {
      get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
    }
    public IValueLookupParameter<ItemDictionary<IGAssistNiche, ItemList<DoubleValue>>> AverageAccuraciesParameter {
      get { return (IValueLookupParameter<ItemDictionary<IGAssistNiche, ItemList<DoubleValue>>>)Parameters["AverageAccuracies"]; }
    }
    public ILookupParameter<ItemArray<DoubleValue>> QualityParameter {
      get { return (ILookupParameter<ItemArray<DoubleValue>>)Parameters["Quality"]; }
    }
    public IValueLookupParameter<IntValue> AccuraciesCountParameter {
      get { return (IValueLookupParameter<IntValue>)Parameters["AccuraciesCount"]; }
    }
    public IValueLookupParameter<IGAssistNicheEqualityComparer> NicheComparerParameter {
      get { return (IValueLookupParameter<IGAssistNicheEqualityComparer>)Parameters["NicheComparer"]; }
    }
    public IValueLookupParameter<DoubleValue> NicheStandardDeviationParameter {
      get { return (IValueLookupParameter<DoubleValue>)Parameters["NicheStandardDeviation"]; }
    }
    #endregion

    public ItemDictionary<IGAssistNiche, ItemList<DoubleValue>> AverageAccuracies { get { return AverageAccuraciesParameter.ActualValue; } }
    public int AccuraciesCount { get { return AccuraciesCountParameter.ActualValue.Value; } }

    [StorableConstructor]
    protected AutoDefaultRule(bool deserializing) : base(deserializing) { }
    protected AutoDefaultRule(AutoDefaultRule original, Cloner cloner)
      : base(original, cloner) {
    }
    public AutoDefaultRule()
      : base() {
      Parameters.Add(new ValueLookupParameter<ItemDictionary<IGAssistNiche, ItemList<DoubleValue>>>("AverageAccuracies"));
      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality"));
      Parameters.Add(new LookupParameter<IRandom>("Random"));
      Parameters.Add(new ValueLookupParameter<IntValue>("AccuraciesCount", new IntValue(15)));
      Parameters.Add(new ValueLookupParameter<IGAssistNicheEqualityComparer>("NicheComparer"));
      Parameters.Add(new ValueLookupParameter<DoubleValue>("NicheStandardDeviation", new DoubleValue(0.005)));
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new AutoDefaultRule(this, cloner);
    }

    public override IOperation Apply() {
      if (NichingParameter.ActualValue == null) {
        IList<IGAssistNiche> niches = GAssistNichesProblemDataParameter.ActualValue.GetPossibleNiches().ToList();
        NichingParameter.ActualValue = new BoolValue(true);
        NichesParameter.ActualValue = new IntValue(niches.Count);
        AverageAccuraciesParameter.ActualValue = new ItemDictionary<IGAssistNiche, ItemList<DoubleValue>>(NicheComparerParameter.ActualValue as IEqualityComparer<IGAssistNiche>);
        foreach (var niche in GAssistNichesProblemDataParameter.ActualValue.GetPossibleNiches()) {
          AverageAccuracies.Add(niche, new ItemList<DoubleValue>(AccuraciesCount));
        }
      } else {
        var nicheFitness = new Dictionary<IGAssistNiche, double>(NicheComparerParameter.ActualValue);
        foreach (var niche in GAssistNichesProblemDataParameter.ActualValue.GetPossibleNiches()) {
          nicheFitness[niche] = 0.0;
          while (AverageAccuracies[niche].Count >= AccuraciesCount) {
            AverageAccuracies[niche].RemoveAt(AverageAccuracies.Count - 1);
          }
        }

        var qualityEnumerator = QualityParameter.ActualValue.GetEnumerator();
        var individualEnumerator = IndividualParameter.ActualValue.GetEnumerator();
        while (qualityEnumerator.MoveNext() && individualEnumerator.MoveNext()) {
          if (nicheFitness[individualEnumerator.Current.Niche] < qualityEnumerator.Current.Value) {
            nicheFitness[individualEnumerator.Current.Niche] = qualityEnumerator.Current.Value;
          }
        }

        foreach (var niche in GAssistNichesProblemDataParameter.ActualValue.GetPossibleNiches()) {
          AverageAccuracies[niche].Insert(0, new DoubleValue(nicheFitness[niche]));
        }

        var averages = new List<double>(GAssistNichesProblemDataParameter.ActualValue.GetPossibleNiches().Count());
        if (AverageAccuracies.Values.First().Count >= AccuraciesCount) {
          foreach (var averageAccuracy in AverageAccuracies.Values) {
            averages.Add(averageAccuracy.Select(x => x.Value).Average());
          }
          double avg = averages.Average();
          double sum = averages.Sum(d => Math.Pow(d - avg, 2));
          double std = Math.Sqrt(sum / averages.Count);

          if (std < NicheStandardDeviationParameter.ActualValue.Value) {
            NichingParameter.ActualValue.Value = false;
          }
        }
      }
      return base.Apply();
    }
  }
}