source: branches/HeuristicLab.Analysis.AlgorithmBehavior/HeuristicLab.Analysis.AlgorithmBehavior.Analyzers/3.3/MutationPerformanceAnalyzer.cs @ 8511

#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.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.PermutationEncoding;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Problems.TravelingSalesman;

namespace HeuristicLab.Analysis.AlgorithmBehavior.Analyzers {
  [Item("MutationPerformanceAnalyzer", "An operator that analyzes the performance of mutation.")]
  [StorableClass]
  public class MutationPerformanceAnalyzer : SingleSuccessorOperator, IAnalyzer {
    private const string ResultsParameterName = "Results";
    private const string GenerationsParameterName = "Generations";

    #region IAnalyzer Members
    public bool EnabledByDefault {
      get { return true; }
    }
    #endregion


    #region Parameter properties
    public ILookupParameter<ResultCollection> ResultsParameter {
      get { return (ILookupParameter<ResultCollection>)Parameters[ResultsParameterName]; }
    }
    public ILookupParameter<IntValue> GenerationsParameter {
      get { return (ILookupParameter<IntValue>)Parameters[GenerationsParameterName]; }
    }
    public ILookupParameter<DoubleValue> QualityAfterCrossoverParameter {
      get { return (ILookupParameter<DoubleValue>)Parameters["QualityAfterCrossover"]; }
    }
    public ILookupParameter<DoubleValue> QualityAfterMutationParameter {
      get { return (ILookupParameter<DoubleValue>)Parameters["QualityAfterMutation"]; }
    }
    public ILookupParameter<Permutation> PermutationBeforeMutationParameter {
      get { return (ILookupParameter<Permutation>)Parameters["PermutationBeforeMutation"]; }
    }
    public ILookupParameter<Permutation> PermutationAfterMutationParameter {
      get { return (ILookupParameter<Permutation>)Parameters["PermutationAfterMutation"]; }
    }
    #endregion

    #region Properties
    public ResultCollection Results {
      get { return ResultsParameter.ActualValue; }
    }
    #endregion

    [Storable]
    private ScatterPlotHelper diversityPlotHelper, qualityPlotHelper;
    [Storable]
    private DataTableHelper avgDataTableHelper;
    [Storable]
    private int cnt = 0, lastGeneration = 0;
    [Storable]
    private List<double> qualityPoints = new List<double>();

    [StorableConstructor]
    private MutationPerformanceAnalyzer(bool deserializing) : base(deserializing) { }
    private MutationPerformanceAnalyzer(MutationPerformanceAnalyzer original, Cloner cloner)
      : base(original, cloner) {
      diversityPlotHelper = (ScatterPlotHelper)original.diversityPlotHelper.Clone(cloner);
      qualityPlotHelper = (ScatterPlotHelper)original.qualityPlotHelper.Clone(cloner);
      avgDataTableHelper = (DataTableHelper)original.avgDataTableHelper.Clone(cloner);
      cnt = original.cnt;
      lastGeneration = original.lastGeneration;
      qualityPoints = new List<double>(original.qualityPoints);
    }

    public MutationPerformanceAnalyzer()
      : 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>("QualityAfterCrossover", "The evaluated quality of the child solution."));
      QualityAfterCrossoverParameter.ActualName = "TSPTourLength";

      Parameters.Add(new LookupParameter<DoubleValue>("QualityAfterMutation", "The evaluated quality of the child solution."));
      QualityAfterMutationParameter.ActualName = "TSPTourLengthM";

      Parameters.Add(new LookupParameter<Permutation>("PermutationBeforeMutation"));
      PermutationBeforeMutationParameter.ActualName = "TSPTourClone";

      Parameters.Add(new LookupParameter<Permutation>("PermutationAfterMutation"));
      PermutationAfterMutationParameter.ActualName = "TSPTour";

      diversityPlotHelper = new ScatterPlotHelper(false, true);
      qualityPlotHelper = new ScatterPlotHelper(false, true);
      avgDataTableHelper = new DataTableHelper();
    }

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

    public override IOperation Apply() {
      Point2D<double> curPoint, divPoint;

      var qualityCX = QualityAfterCrossoverParameter.ActualValue.Value;
      var qualityM = QualityAfterMutationParameter.ActualValue.Value;
      var permutationBefore = PermutationBeforeMutationParameter.ActualValue;
      var permutationAfter = PermutationAfterMutationParameter.ActualValue;

      qualityPlotHelper.InitializePlot(Results, "Mutation Quality", "Solution Index", "Absolut Quality Difference");
      diversityPlotHelper.InitializePlot(Results, "Mutation Diversity", "Solution Index", "Diversity");
      avgDataTableHelper.InitializeChart(Results, "Average Mutation Performance", "Average Mutation Performance per Generation");

      divPoint = new Point2D<double>(cnt, TSPSimilarityCalculator.CalculateSimilarity(permutationBefore, permutationAfter));
      curPoint = new Point2D<double>(cnt++, qualityCX - qualityM);
      qualityPoints.Add(curPoint.Y);

      string curGenStr = GenerationsParameter.ActualValue.Value.ToString();

      qualityPlotHelper.AddPoint(curGenStr, curPoint);
      diversityPlotHelper.AddPoint(curGenStr, divPoint);

      if (GenerationsParameter.ActualValue.Value != 0) {
        if (GenerationsParameter.ActualValue.Value > lastGeneration) {
          double avg = qualityPoints.Average();
          avgDataTableHelper.AddPoint(avg);
          Reset();
        }
      } else {
        Reset();
      }

      return base.Apply();
    }

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