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source: branches/HeuristicLab.Analysis.AlgorithmBehavior/HeuristicLab.Analysis.AlgorithmBehavior.Analyzers/3.3/CrossoverPerformanceAnalyzer.cs @ 8499

Last change on this file since 8499 was 8499, checked in by ascheibe, 10 years ago

#1886 improved crossover analyzer and added duplicate parent counting

File size: 8.5 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22
23using System.Collections.Generic;
24using System.Linq;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Encodings.PermutationEncoding;
29using HeuristicLab.Operators;
30using HeuristicLab.Optimization;
31using HeuristicLab.Optimization.Operators;
32using HeuristicLab.Parameters;
33using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
34using HeuristicLab.Problems.TravelingSalesman;
35
36namespace HeuristicLab.Analysis.AlgorithmBehavior.Analyzers {
37  [Item("CrossoverPerformanceAnalyzer", "An operator that analyzes the performance of crossovers.")]
38  [StorableClass]
39  public class CrossoverPerformanceAnalyzer : SingleSuccessorOperator, IAnalyzer {
40    private const string ResultsParameterName = "Results";
41    private const string GenerationsParameterName = "Generations";
42
43    #region IAnalyzer Members
44    public bool EnabledByDefault {
45      get { return true; }
46    }
47    #endregion
48
49
50    #region Parameter properties
51    public ILookupParameter<ResultCollection> ResultsParameter {
52      get { return (ILookupParameter<ResultCollection>)Parameters[ResultsParameterName]; }
53    }
54    public ILookupParameter<IntValue> GenerationsParameter {
55      get { return (ILookupParameter<IntValue>)Parameters[GenerationsParameterName]; }
56    }
57    public ILookupParameter<ItemArray<Permutation>> ParentsParameter {
58      get { return (ScopeTreeLookupParameter<Permutation>)Parameters["Parents"]; }
59    }
60    public ILookupParameter<ItemArray<DoubleValue>> ParentsQualityParameter {
61      get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["ParentsQuality"]; }
62    }
63    public ILookupParameter<Permutation> ChildParameter {
64      get { return ((LookupParameter<Permutation>)Parameters["Child"]); }
65    }
66    public ILookupParameter<DoubleValue> QualityParameter {
67      get { return (ILookupParameter<DoubleValue>)Parameters["Quality"]; }
68    }
69    public IValueParameter<SingleObjectiveSolutionSimilarityCalculator> SimilarityCalculatorParameter {
70      get { return (IValueParameter<SingleObjectiveSolutionSimilarityCalculator>)Parameters["SimilarityCalculator"]; }
71    }
72    #endregion
73
74    #region Properties
75    public ResultCollection Results {
76      get { return ResultsParameter.ActualValue; }
77    }
78    #endregion
79
80    ScatterPlotHelper plotHelper, childDiversityHelper, parentDiversityHelper;
81    DataTableHelper performanceHelper, successHelper, equalParentsHelper;
82    int cnt = 0;
83    int success = 0;
84    int lastGeneration = 0;
85    int equalParents = 0;
86    List<double> qualityPoints = new List<double>();
87
88    [StorableConstructor]
89    private CrossoverPerformanceAnalyzer(bool deserializing) : base(deserializing) { }
90    private CrossoverPerformanceAnalyzer(CrossoverPerformanceAnalyzer original, Cloner cloner) : base(original, cloner) { }
91    public CrossoverPerformanceAnalyzer()
92      : base() {
93      Parameters.Add(new LookupParameter<ResultCollection>(ResultsParameterName, "The results collection where the analysis values should be stored."));
94      Parameters.Add(new LookupParameter<IntValue>(GenerationsParameterName, "Nr of generations."));
95
96      Parameters.Add(new ScopeTreeLookupParameter<Permutation>("Parents", "The parent permutations which have been crossed."));
97      ParentsParameter.ActualName = "TSPTour";
98
99      Parameters.Add(new LookupParameter<Permutation>("Child", "The child permutation resulting from the crossover."));
100      ChildParameter.ActualName = "TSPTour";
101
102      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("ParentsQuality", "The quality of the parent solutions."));
103      ParentsQualityParameter.ActualName = "TSPTourLength";
104
105      Parameters.Add(new LookupParameter<DoubleValue>("Quality", "The evaluated quality of the child solution."));
106      QualityParameter.ActualName = "TSPTourLength";
107
108      Parameters.Add(new ValueParameter<SingleObjectiveSolutionSimilarityCalculator>("SimilarityCalculator"));
109
110      plotHelper = new ScatterPlotHelper();
111      childDiversityHelper = new ScatterPlotHelper();
112      parentDiversityHelper = new ScatterPlotHelper();
113      performanceHelper = new DataTableHelper();
114      successHelper = new DataTableHelper();
115      equalParentsHelper = new DataTableHelper();
116    }
117
118    public override IDeepCloneable Clone(Cloner cloner) {
119      return new CrossoverPerformanceAnalyzer(this, cloner);
120    }
121
122    public override IOperation Apply() {
123      SimilarityCalculatorParameter.Value.QualityVariableName = "TSPTourLength";
124      SimilarityCalculatorParameter.Value.SolutionVariableName = "TSPTour";
125
126      plotHelper.InitializePlot(Results, "Crossover Performance", "Solution Index", "Absolut Quality Difference");
127      childDiversityHelper.InitializePlot(Results, "Child Diversity", "Solution Index", "Diversity");
128      parentDiversityHelper.InitializePlot(Results, "Parent Diversity", "Solution Index", "Diversity");
129
130      performanceHelper.InitializeChart(Results, "Average Crossover Performance", "Average Crossover Performance per Generation");
131      successHelper.InitializeChart(Results, "Successfull Crossovers", "Successfull Crossovers per Generation");
132      equalParentsHelper.InitializeChart(Results, "Number of equal parents", "Absolut number of equal parents");
133
134      Point2D<double> qualityPoint, diversityPointChild, diversityPointParent;
135      var qualityParent1 = ParentsQualityParameter.ActualValue.First().Value;
136      var qualityParent2 = ParentsQualityParameter.ActualValue.Last().Value;
137      var child = ChildParameter.ActualValue;
138      var parent1 = ParentsParameter.ActualValue.First();
139      var parent2 = ParentsParameter.ActualValue.Last();
140      var parentDiversity = SimilarityCalculatorParameter.Value.CalculateSolutionSimilarity(ExecutionContext.Scope.SubScopes.First(), ExecutionContext.Scope.SubScopes.Last());
141      string curGenStr = GenerationsParameter.ActualValue.Value.ToString();
142
143
144      diversityPointParent = new Point2D<double>(cnt, parentDiversity);
145      double worseQuality = qualityParent1 > qualityParent2 ? qualityParent1 : qualityParent2;
146      if (qualityParent1 > qualityParent2) {
147        diversityPointChild = new Point2D<double>(cnt, SimilarityCalculatorParameter.Value.CalculateSolutionSimilarity(ExecutionContext.Scope, ExecutionContext.Scope.SubScopes.First()));
148      } else {
149        diversityPointChild = new Point2D<double>(cnt, SimilarityCalculatorParameter.Value.CalculateSolutionSimilarity(ExecutionContext.Scope, ExecutionContext.Scope.SubScopes.Last()));
150      }
151
152      qualityPoint = new Point2D<double>(cnt++, worseQuality - QualityParameter.ActualValue.Value);
153      if ((worseQuality - QualityParameter.ActualValue.Value) > 0) {
154        success++;
155      }
156      qualityPoints.Add(qualityPoint.Y);
157
158      if (TSPSimilarityCalculator.CalculateSimilarity(parent1, parent2) == 1.0) {
159        equalParents++;
160      }
161
162      if (GenerationsParameter.ActualValue.Value != 0) {
163        if (GenerationsParameter.ActualValue.Value > lastGeneration) {
164          double avg = qualityPoints.Average();
165
166          performanceHelper.AddPoint(avg);
167          successHelper.AddPoint(success);
168          equalParentsHelper.AddPoint(equalParents);
169
170          Reset();
171        }
172
173        plotHelper.AddPoint(curGenStr, qualityPoint);
174        childDiversityHelper.AddPoint(curGenStr, diversityPointChild);
175        parentDiversityHelper.AddPoint(curGenStr, diversityPointParent);
176      } else {
177        Reset();
178      }
179
180      return base.Apply();
181    }
182
183    private void Reset() {
184      cnt = 0;
185      success = 0;
186      lastGeneration = GenerationsParameter.ActualValue.Value;
187      qualityPoints.Clear();
188      equalParents = 0;
189    }
190  }
191}
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