source: branches/VOSGA/HeuristicLab.Algorithms.VOffspringSelectionGeneticAlgorithm/PopulationDiversityComparator.cs @ 11843

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2014 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.Linq;
using HeuristicLab.Analysis;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Optimization.Operators;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.PluginInfrastructure;

namespace HeuristicLab.Algorithms.VOffspringSelectionGeneticAlgorithm {
  [Item("PopulationDiversityComparator", "Compares the similarity against that of its parents (assumes the parents are subscopes to the child scope). This operator works with any number of subscopes > 0.")]
  [StorableClass]
  public class PopulationDiversityComparator : SingleSuccessorOperator, ISubScopesQualityComparatorOperator, ISimilarityBasedOperator {
    [Storable]
    public ISolutionSimilarityCalculator SimilarityCalculator { get; set; }
    public IValueLookupParameter<BoolValue> MaximizationParameter {
      get { return (IValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
    }
    public ILookupParameter<DoubleValue> LeftSideParameter {
      get { return (ILookupParameter<DoubleValue>)Parameters["LeftSide"]; }
    }
    public ILookupParameter<ItemArray<DoubleValue>> RightSideParameter {
      get { return (ILookupParameter<ItemArray<DoubleValue>>)Parameters["RightSide"]; }
    }
    public ILookupParameter<BoolValue> ResultParameter {
      get { return (ILookupParameter<BoolValue>)Parameters["Result"]; }
    }
    public ValueLookupParameter<DoubleValue> ComparisonFactorParameter {
      get { return (ValueLookupParameter<DoubleValue>)Parameters["ComparisonFactor"]; }
    }
    public ValueLookupParameter<DoubleValue> DiversityComparisonFactorParameter {
      get { return (ValueLookupParameter<DoubleValue>)Parameters["DiversityComparisonFactor"]; }
    }
    private ValueLookupParameter<DoubleValue> ComparisonFactorLowerBoundParameter {
      get { return (ValueLookupParameter<DoubleValue>)Parameters["DiversityComparisonFactorLowerBound"]; }
    }
    private ValueLookupParameter<DoubleValue> ComparisonFactorUpperBoundParameter {
      get { return (ValueLookupParameter<DoubleValue>)Parameters["DiversityComparisonFactorUpperBound"]; }
    }
    public IConstrainedValueParameter<IDiscreteDoubleValueModifier> ComparisonFactorModifierParameter {
      get { return (IConstrainedValueParameter<IDiscreteDoubleValueModifier>)Parameters["ComparisonFactorModifier"]; }
    }
    public ValueLookupParameter<ResultCollection> ResultsParameter {
      get { return (ValueLookupParameter<ResultCollection>)Parameters["Results"]; }
    }
    public ILookupParameter<IntValue> GenerationsParameter {
      get { return (LookupParameter<IntValue>)Parameters["Generations"]; }
    }
    public ValueParameter<BoolValue> EnableDivCriteriaParameter {
      get { return (ValueParameter<BoolValue>)Parameters["EnableDivCriteria"]; }
    }

    private const string spDetailsParameterName = "SPDetails";
    private const string divDataRowName = "DiversitySuccessCount";
    private const string qualityDataRowName = "QualitySuccessCount";
    private const string divFailDataRowName = "DiversityFailCount";
    private const string qualityFailDataRowName = "QualityFailCount";
    private const string overallCountDataRowName = "OverallCount";
    private const string successCountDataRowName = "SuccessCount";

    [Storable]
    private int currentGeneration;
    [Storable]
    private int divCount;
    [Storable]
    private int qualityCount;
    [Storable]
    private int badQualityCount;
    [Storable]
    private int badDivCount;
    [Storable]
    private int overallCount;
    [Storable]
    private int successCount;

    [StorableConstructor]
    protected PopulationDiversityComparator(bool deserializing) : base(deserializing) { }
    protected PopulationDiversityComparator(PopulationDiversityComparator original, Cloner cloner)
      : base(original, cloner) {
      SimilarityCalculator = cloner.Clone(original.SimilarityCalculator);
      currentGeneration = original.currentGeneration;
      divCount = original.divCount;
      qualityCount = original.qualityCount;
      overallCount = original.overallCount;
      successCount = original.successCount;
      badDivCount = original.badDivCount;
      badQualityCount = original.badQualityCount;
    }
    public PopulationDiversityComparator()
      : base() {
      Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, false otherwise"));
      Parameters.Add(new LookupParameter<DoubleValue>("LeftSide", "The quality of the child."));
      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("RightSide", "The qualities of the parents."));
      Parameters.Add(new LookupParameter<BoolValue>("Result", "The result of the comparison: True means Quality is better, False means it is worse than parents."));
      Parameters.Add(new ValueLookupParameter<DoubleValue>("ComparisonFactor", "Determines if the quality should be compared to the better parent (1.0), to the worse (0.0) or to any linearly interpolated value between them."));
      Parameters.Add(new ValueLookupParameter<DoubleValue>("DiversityComparisonFactor", "Determines if the quality should be compared to the better parent (1.0), to the worse (0.0) or to any linearly interpolated value between them.", new DoubleValue(0.0)));
      Parameters.Add(new ValueLookupParameter<DoubleValue>("DiversityComparisonFactorLowerBound", "The lower bound of the comparison factor (start).", new DoubleValue(0.5)));
      Parameters.Add(new ValueLookupParameter<DoubleValue>("DiversityComparisonFactorUpperBound", "The upper bound of the comparison factor (end).", new DoubleValue(1.0)));
      Parameters.Add(new OptionalConstrainedValueParameter<IDiscreteDoubleValueModifier>("ComparisonFactorModifier", "The operator used to modify the comparison factor.", new ItemSet<IDiscreteDoubleValueModifier>(new IDiscreteDoubleValueModifier[] { new LinearDiscreteDoubleValueModifier() }), new LinearDiscreteDoubleValueModifier()));
      Parameters.Add(new ValueLookupParameter<ResultCollection>("Results", "The result collection where the population diversity analysis results should be stored."));
      Parameters.Add(new LookupParameter<IntValue>("Generations", "The current number of generations."));
      Parameters.Add(new ValueParameter<BoolValue>("EnableDivCriteria", "Use diversity as additional offspring selection criteria.", new BoolValue(true)));

      foreach (IDiscreteDoubleValueModifier modifier in ApplicationManager.Manager.GetInstances<IDiscreteDoubleValueModifier>().OrderBy(x => x.Name))
        ComparisonFactorModifierParameter.ValidValues.Add(modifier);
      IDiscreteDoubleValueModifier linearModifier = ComparisonFactorModifierParameter.ValidValues.FirstOrDefault(x => x.GetType().Name.Equals("LinearDiscreteDoubleValueModifier"));
      if (linearModifier != null) ComparisonFactorModifierParameter.Value = linearModifier;
      ParameterizeComparisonFactorModifiers();
    }

    public override IDeepCloneable Clone(Cloner cloner) {
      return new PopulationDiversityComparator(this, cloner);
    }

    private void ParameterizeComparisonFactorModifiers() {
      //TODO: does not work if Generations parameter names are changed
      foreach (IDiscreteDoubleValueModifier modifier in ComparisonFactorModifierParameter.ValidValues) {
        modifier.IndexParameter.ActualName = "Generations";
        modifier.EndIndexParameter.ActualName = "MaximumGenerations";
        modifier.EndValueParameter.ActualName = ComparisonFactorUpperBoundParameter.Name;
        modifier.StartIndexParameter.Value = new IntValue(0);
        modifier.StartValueParameter.ActualName = ComparisonFactorLowerBoundParameter.Name;
        modifier.ValueParameter.ActualName = "DiversityComparisonFactor";
      }
    }

    private IScope GetRemainingScope() {
      var scope = ExecutionContext.Scope;

      while (scope != null) {
        if (scope.SubScopes.Any(x => x.Name == "Remaining")) {
          return scope.SubScopes.Single(x => x.Name == "Remaining");
        }
        scope = scope.Parent;
      }
      return null;
    }

    public override IOperation Apply() {
      ItemArray<DoubleValue> rightQualities = RightSideParameter.ActualValue;
      if (rightQualities.Length < 1) throw new InvalidOperationException(Name + ": No subscopes found.");
      double compFact = ComparisonFactorParameter.ActualValue.Value;
      double diversityComFact = DiversityComparisonFactorParameter.ActualValue.Value;
      bool maximization = MaximizationParameter.ActualValue.Value;
      double leftQuality = LeftSideParameter.ActualValue.Value;
      bool resultDiversity;
      double threshold = 0;

      DataTable spDetailsTable;
      if (ResultsParameter.ActualValue.ContainsKey(spDetailsParameterName)) {
        spDetailsTable = (DataTable)ResultsParameter.ActualValue[spDetailsParameterName].Value;
      } else {
        spDetailsTable = new DataTable(spDetailsParameterName);
        spDetailsTable.Rows.Add(new DataRow(divDataRowName));
        spDetailsTable.Rows.Add(new DataRow(qualityDataRowName));
        spDetailsTable.Rows.Add(new DataRow(overallCountDataRowName));
        spDetailsTable.Rows.Add(new DataRow(successCountDataRowName));
        spDetailsTable.Rows.Add(new DataRow(divFailDataRowName));
        spDetailsTable.Rows.Add(new DataRow(qualityFailDataRowName));
        ResultsParameter.ActualValue.Add(new Result(spDetailsParameterName, spDetailsTable));
      }

      if (GenerationsParameter.ActualValue.Value != currentGeneration) {
        spDetailsTable.Rows[divDataRowName].Values.Add(divCount);
        divCount = 0;
        spDetailsTable.Rows[qualityDataRowName].Values.Add(qualityCount);
        qualityCount = 0;
        spDetailsTable.Rows[overallCountDataRowName].Values.Add(overallCount);
        overallCount = 0;
        spDetailsTable.Rows[successCountDataRowName].Values.Add(successCount);
        successCount = 0;
        spDetailsTable.Rows[qualityFailDataRowName].Values.Add(badQualityCount);
        badQualityCount = 0;
        spDetailsTable.Rows[divFailDataRowName].Values.Add(badDivCount);
        badDivCount = 0;
        currentGeneration = GenerationsParameter.ActualValue.Value;
      }

      #region Calculate threshold
      if (rightQualities.Length == 2) {
        var remainingScope = GetRemainingScope();
        Scope fakeScope = new Scope();
        fakeScope.SubScopes.Add((IScope)ExecutionContext.Scope.Clone());
        var similarities = SimilarityCalculator.CalculateSolutionCrowdSimilarity(fakeScope, remainingScope);
        double averageSimilarity = similarities[0].Average();
        resultDiversity = averageSimilarity < diversityComFact;

        double minQuality = Math.Min(rightQualities[0].Value, rightQualities[1].Value);
        double maxQuality = Math.Max(rightQualities[0].Value, rightQualities[1].Value);
        if (maximization)
          threshold = minQuality + (maxQuality - minQuality) * compFact;
        else
          threshold = maxQuality - (maxQuality - minQuality) * compFact;
      } else {
        throw new NotImplementedException("Only 2 parents are supported.");
      }
      #endregion

      bool result = maximization && leftQuality > threshold || !maximization && leftQuality < threshold;

      //collect statistics
      if (result) {
        qualityCount++;
      } else {
        badQualityCount++;
      }
      if (resultDiversity) {
        divCount++;
      } else {
        badDivCount++;
      }
      if (result && resultDiversity) {
        successCount++;
      }
      overallCount++;

      //use diveristiy criteria or not
      if (EnableDivCriteriaParameter.Value.Value) {
        result = result && resultDiversity;
      }

      BoolValue resultValue = ResultParameter.ActualValue;
      if (resultValue == null) {
        ResultParameter.ActualValue = new BoolValue(result);
      } else {
        resultValue.Value = result;
      }

      //like the placeholder, though we create child operations
      OperationCollection next = new OperationCollection(base.Apply());
      IOperator op = ComparisonFactorModifierParameter.Value;
      if (op != null)
        next.Insert(0, ExecutionContext.CreateChildOperation(op));
      return next;
    }
  }
}