source: branches/HeuristicLab.Analysis.AlgorithmBehavior/HeuristicLab.Analysis.AlgorithmBehavior.Analyzers/3.3/SolutionToPopulationAnalyzer.cs @ 10007

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2013 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.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Analysis.AlgorithmBehavior.Analyzers {
  [Item("SolutionToPopulationAnalyzer", "An operator that analyzes the diversity of solutions compared to the population.")]
  [StorableClass]
  public class SolutionToPopulationAnalyzer : InitializableOperator, IStatefulItem {
    private const string ResultsParameterName = "Results";
    private const string GenerationsParameterName = "Generations";

    #region Parameter properties
    public IValueLookupParameter<BoolValue> MaximizationParameter {
      get { return (IValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
    }
    public ILookupParameter<ResultCollection> ResultsParameter {
      get { return (ILookupParameter<ResultCollection>)Parameters[ResultsParameterName]; }
    }
    public ILookupParameter<IntValue> GenerationsParameter {
      get { return (ILookupParameter<IntValue>)Parameters[GenerationsParameterName]; }
    }
    public ILookupParameter<DoubleValue> QualityParameter {
      get { return (ILookupParameter<DoubleValue>)Parameters["Quality"]; }
    }
    public ILookupParameter<IItem> SolutionParameter {
      get { return (ILookupParameter<IItem>)Parameters["Solution"]; }
    }
    public ILookupParameter<ItemCollection<IItem>> OperatorsParameter {
      get { return (ILookupParameter<ItemCollection<IItem>>)Parameters["Operators"]; }
    }
    public IValueParameter<ISingleObjectiveSolutionSimilarityCalculator> SimilarityCalculatorParameter {
      get { return (IValueParameter<ISingleObjectiveSolutionSimilarityCalculator>)Parameters["SimilarityCalculator"]; }
    }
    public IValueParameter<StringValue> ChartPostfixParameter {
      get { return (IValueParameter<StringValue>)Parameters["ChartPostfix"]; }
    }
    public ILookupParameter<DoubleValue> BestKnownQualityParameter {
      get { return (ILookupParameter<DoubleValue>)Parameters["BestKnownQuality"]; }
    }
    public ILookupParameter<DoubleValue> WorstKnownQualityParameter {
      get { return (ILookupParameter<DoubleValue>)Parameters["WorstKnownQuality"]; }
    }
    #endregion

    #region Properties
    public ResultCollection Results {
      get { return ResultsParameter.ActualValue; }
    }
    [Storable]
    private ScatterPlotHelper populationDiversityPlot, populationQualityPlot, qualityPlot;
    [Storable]
    private int cnt = 0;
    [Storable]
    private int lastGeneration = 0;
    [Storable]
    private bool scalingFinished = false;
    #endregion

    [StorableConstructor]
    private SolutionToPopulationAnalyzer(bool deserializing) : base(deserializing) { }
    private SolutionToPopulationAnalyzer(SolutionToPopulationAnalyzer original, Cloner cloner)
      : base(original, cloner) {
      cnt = original.cnt;
      lastGeneration = original.lastGeneration;
      populationDiversityPlot = (ScatterPlotHelper)original.populationDiversityPlot.Clone(cloner);
      populationQualityPlot = (ScatterPlotHelper)original.populationQualityPlot.Clone(cloner);
      qualityPlot = (ScatterPlotHelper)original.qualityPlot.Clone(cloner);
      scalingFinished = original.scalingFinished;
    }

    public SolutionToPopulationAnalyzer()
      : base() {
      Parameters.Add(new LookupParameter<ResultCollection>(ResultsParameterName, "The results collection where the analysis values should be stored."));
      Parameters.Add(new LookupParameter<IntValue>(GenerationsParameterName, "Nr of generations."));
      Parameters.Add(new LookupParameter<DoubleValue>("Quality", "The evaluated quality of the child solution."));
      QualityParameter.ActualName = "TSPTourLength";
      Parameters.Add(new LookupParameter<IItem>("Solution"));
      SolutionParameter.ActualName = "TSPTour";
      Parameters.Add(new ValueParameter<ISingleObjectiveSolutionSimilarityCalculator>("SimilarityCalculator"));
      Parameters.Add(new ValueParameter<StringValue>("ChartPostfix", new StringValue(string.Empty)));
      Parameters.Add(new LookupParameter<ItemCollection<IItem>>("Operators", "The operators and items that the problem provides to the algorithms."));
      Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, false otherwise"));
      Parameters.Add(new LookupParameter<DoubleValue>("BestKnownQuality", "The quality of the best known solution of this problem."));
      Parameters.Add(new LookupParameter<DoubleValue>("WorstKnownQuality", "The quality of the worst known solution of this problem."));

      populationDiversityPlot = new ScatterPlotHelper(false, true, false, true);
      populationQualityPlot = new ScatterPlotHelper(false, true, true, true);
      qualityPlot = new ScatterPlotHelper(false, true, true, true);
    }

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

    protected override void InitializeAction() {
      if (SimilarityCalculatorParameter.Value == null) {
        SimilarityCalculatorParameter.Value = OperatorsParameter.ActualValue.OfType<ISingleObjectiveSolutionSimilarityCalculator>().FirstOrDefault();
      }

      populationDiversityPlot.InitializePlot(Results, "Solution to Population Diversity " + ChartPostfixParameter.Value.Value, "Solution Index", "Diversity");
      populationQualityPlot.InitializePlot(Results, "Solution Quality Difference to Population " + ChartPostfixParameter.Value.Value, "Solution Index", "Quality Difference");
      qualityPlot.InitializePlot(Results, "Solution Quality " + ChartPostfixParameter.Value.Value, "Solution Index", "Quality");

      Reset();
    }

    public override IOperation Apply() {
      Initialize();

      string curGenStr = GenerationsParameter.ActualValue.Value.ToString();
      double quality = QualityParameter.ActualValue.Value;
      IItem solution = SolutionParameter.ActualValue;
      string qualityVariableName = QualityParameter.ActualName;
      string solutionVariableName = SolutionParameter.ActualName;
      ISingleObjectiveSolutionSimilarityCalculator simCalc = SimilarityCalculatorParameter.Value;
      Scope artificialSolutionScope = new Scope();
      artificialSolutionScope.Variables.Add(new Variable(solutionVariableName, solution));


      IScope oldPop = ReverseScopeTreeLookup("Remaining");
      if (oldPop == null)
        throw new Exception("Couldn't find the remaining scope");

      if (GenerationsParameter.ActualValue.Value != 0) {
        if (GenerationsParameter.ActualValue.Value > lastGeneration) {
          Reset();
        }

        double oldPopQuality = 0.0;
        double solToPopDiversity = 0.0;
        int popSize = 0;
        foreach (IScope oldSolScope in oldPop.SubScopes) {
          double curQuality = ((DoubleValue)oldSolScope.Variables[qualityVariableName].Value).Value;
          IItem curSol = oldSolScope.Variables[solutionVariableName].Value;
          oldPopQuality += curQuality;
          solToPopDiversity += simCalc.CalculateSolutionSimilarity(artificialSolutionScope, oldSolScope);
          popSize++;
        }

        if (WorstKnownQualityParameter.ActualValue != null && !scalingFinished) {
          scalingFinished = true;
          double bkQuality = BestKnownQualityParameter.ActualValue.Value;
          double wkQuality = WorstKnownQualityParameter.ActualValue.Value;

          if (MaximizationParameter.ActualValue.Value) {
            if (populationQualityPlot.Max == double.MinValue) {
              populationQualityPlot.Max = bkQuality - wkQuality;
              qualityPlot.Max = bkQuality;
              populationQualityPlot.Min = 0;
              qualityPlot.Min = wkQuality;
            }
          } else {
            if (populationQualityPlot.Min == double.MaxValue) {
              populationQualityPlot.Max = wkQuality - bkQuality;
              qualityPlot.Max = wkQuality;
              populationQualityPlot.Min = 0;
              qualityPlot.Min = bkQuality;
            }
          }
        }

        Point2D<double> popQualityPoint;
        if (MaximizationParameter.ActualValue.Value) {
          popQualityPoint = new Point2D<double>(cnt, quality - (oldPopQuality / popSize));
        } else {
          popQualityPoint = new Point2D<double>(cnt, (oldPopQuality / popSize) - quality);
        }

        Point2D<double> solQuality = new Point2D<double>(cnt, quality);
        Point2D<double> diversityPoint = new Point2D<double>(cnt++, solToPopDiversity / popSize);

        populationDiversityPlot.AddPoint(curGenStr, diversityPoint);
        populationQualityPlot.AddPoint(curGenStr, popQualityPoint);
        qualityPlot.AddPoint(curGenStr, solQuality);
      }

      return base.Apply();
    }

    private void Reset() {
      cnt = 0;
      lastGeneration = GenerationsParameter.ActualValue.Value;
    }

    public override void ClearState() {
      populationQualityPlot.CleanUp();
      populationDiversityPlot.CleanUp();
      qualityPlot.CleanUp();
      scalingFinished = false;
    }

    private IScope ReverseScopeTreeLookup(string scopeName) {
      var currentScope = ExecutionContext.Scope;
      while (currentScope != null) {
        var scopes = currentScope.SubScopes.Where(x => x.Name == scopeName);
        if (scopes.Count() > 0)
          return scopes.First();

        currentScope = currentScope.Parent;
      }
      return null;
    }
  }
}