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source: branches/HeuristicLab.Analysis.AlgorithmBehavior/HeuristicLab.Analysis.AlgorithmBehavior.Analyzers/3.3/CrossoverPerformanceAnalyzer.cs @ 9032

Last change on this file since 9032 was 9020, checked in by ascheibe, 12 years ago

#1886 added an analyzer for unwanted mutation for the TSP
File size: 16.0 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;
24using System.Collections.Generic;
25using System.Linq;
26using HeuristicLab.Common;
27using HeuristicLab.Core;
28using HeuristicLab.Data;
29using HeuristicLab.Encodings.PermutationEncoding;
30using HeuristicLab.Optimization;
31using HeuristicLab.Parameters;
32using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
33
34namespace HeuristicLab.Analysis.AlgorithmBehavior.Analyzers {
35  [Item("CrossoverPerformanceAnalyzer", "An operator that analyzes the performance of crossovers.")]
36  [StorableClass]
37  public class CrossoverPerformanceAnalyzer : InitializableOperator, IStatefulItem {
38    private const string ResultsParameterName = "Results";
39    private const string GenerationsParameterName = "Generations";
40    private const string SuccessfullCrossoversRowName = "Successfull Crossovers per Generation with CompFact ";
41
42    #region Parameter properties
43    public IValueLookupParameter<BoolValue> MaximizationParameter {
44      get { return (IValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
45    }
46    public IValueLookupParameter<ItemCollection<DoubleValue>> ComparisonFactorParameter {
47      get { return (IValueLookupParameter<ItemCollection<DoubleValue>>)Parameters["ComparisonFactor"]; }
48    }
49    public ILookupParameter<ResultCollection> ResultsParameter {
50      get { return (ILookupParameter<ResultCollection>)Parameters[ResultsParameterName]; }
51    }
52    public ILookupParameter<IntValue> GenerationsParameter {
53      get { return (ILookupParameter<IntValue>)Parameters[GenerationsParameterName]; }
54    }
55    public ILookupParameter<ItemArray<Permutation>> ParentsParameter {
56      get { return (ScopeTreeLookupParameter<Permutation>)Parameters["Parents"]; }
57    }
58    public ILookupParameter<ItemArray<DoubleValue>> ParentsQualityParameter {
59      get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["ParentsQuality"]; }
60    }
61    public ILookupParameter<Permutation> ChildParameter {
62      get { return ((LookupParameter<Permutation>)Parameters["Child"]); }
63    }
64    public ILookupParameter<DoubleValue> QualityParameter {
65      get { return (ILookupParameter<DoubleValue>)Parameters["Quality"]; }
66    }
67    public IValueParameter<ISingleObjectiveSolutionSimilarityCalculator> SimilarityCalculatorParameter {
68      get { return (IValueParameter<ISingleObjectiveSolutionSimilarityCalculator>)Parameters["SimilarityCalculator"]; }
69    }
70    public ILookupParameter<ItemCollection<IItem>> OperatorsParameter {
71      get { return (ILookupParameter<ItemCollection<IItem>>)Parameters["Operators"]; }
72    }
73    #endregion
74
75    #region Properties
76    public ResultCollection Results {
77      get { return ResultsParameter.ActualValue; }
78    }
79    #endregion
80
81    [Storable]
82    private ScatterPlotHelper worseParentCrossoverPerformancePlot, betterParentCrossoverPerformancePlot, childDiversityToWorseParentHelper, childDiversityToBetterParentHelper, parentDiversityHelper, parentQualityHelper, unwantedMutationsHelper;
83    [Storable]
84    private DataTableHelper successHelper, equalParentsHelper;
85    [Storable]
86    private int cnt = 0;
87    [Storable]
88    private int[] success;
89    [Storable]
90    private int lastGeneration = 0;
91    [Storable]
92    private int equalParents = 0;
93
94    [StorableConstructor]
95    private CrossoverPerformanceAnalyzer(bool deserializing) : base(deserializing) { }
96    private CrossoverPerformanceAnalyzer(CrossoverPerformanceAnalyzer original, Cloner cloner)
97      : base(original, cloner) {
98      cnt = original.cnt;
99      success = (int[])original.success.Clone();
100      lastGeneration = original.lastGeneration;
101      equalParents = original.equalParents;
102      worseParentCrossoverPerformancePlot = (ScatterPlotHelper)original.worseParentCrossoverPerformancePlot.Clone(cloner);
103      betterParentCrossoverPerformancePlot = (ScatterPlotHelper)original.betterParentCrossoverPerformancePlot.Clone(cloner);
104      childDiversityToWorseParentHelper = (ScatterPlotHelper)original.childDiversityToWorseParentHelper.Clone(cloner);
105      childDiversityToBetterParentHelper = (ScatterPlotHelper)original.childDiversityToBetterParentHelper.Clone(cloner);
106      parentDiversityHelper = (ScatterPlotHelper)original.parentDiversityHelper.Clone(cloner);
107      parentQualityHelper = (ScatterPlotHelper)original.parentQualityHelper.Clone(cloner);
108      unwantedMutationsHelper = (ScatterPlotHelper)original.unwantedMutationsHelper.Clone(cloner);
109      successHelper = (DataTableHelper)original.successHelper.Clone(cloner);
110      equalParentsHelper = (DataTableHelper)original.equalParentsHelper.Clone(cloner);
111    }
112
113    public CrossoverPerformanceAnalyzer()
114      : base() {
115      Parameters.Add(new LookupParameter<ResultCollection>(ResultsParameterName, "The results collection where the analysis values should be stored."));
116      Parameters.Add(new LookupParameter<IntValue>(GenerationsParameterName, "Nr of generations."));
117
118      Parameters.Add(new ScopeTreeLookupParameter<Permutation>("Parents", "The parent permutations which have been crossed."));
119      ParentsParameter.ActualName = "TSPTour";
120
121      Parameters.Add(new LookupParameter<Permutation>("Child", "The child permutation resulting from the crossover."));
122      ChildParameter.ActualName = "TSPTour";
123
124      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("ParentsQuality", "The quality of the parent solutions."));
125      ParentsQualityParameter.ActualName = "TSPTourLength";
126
127      Parameters.Add(new LookupParameter<DoubleValue>("Quality", "The evaluated quality of the child solution."));
128      QualityParameter.ActualName = "TSPTourLength";
129
130      Parameters.Add(new ValueParameter<ISingleObjectiveSolutionSimilarityCalculator>("SimilarityCalculator"));
131      Parameters.Add(new LookupParameter<ItemCollection<IItem>>("Operators", "The operators and items that the problem provides to the algorithms."));
132      Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, false otherwise"));
133      Parameters.Add(new ValueLookupParameter<ItemCollection<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."));
134
135
136      worseParentCrossoverPerformancePlot = new ScatterPlotHelper(false, true);
137      betterParentCrossoverPerformancePlot = new ScatterPlotHelper(false, true);
138      childDiversityToWorseParentHelper = new ScatterPlotHelper(false, true);
139      childDiversityToBetterParentHelper = new ScatterPlotHelper(false, true);
140      unwantedMutationsHelper = new ScatterPlotHelper(false, true);
141      parentDiversityHelper = new ScatterPlotHelper(false, true);
142      parentQualityHelper = new ScatterPlotHelper(false, true);
143      successHelper = new DataTableHelper();
144      equalParentsHelper = new DataTableHelper();
145    }
146
147    public override IDeepCloneable Clone(Cloner cloner) {
148      return new CrossoverPerformanceAnalyzer(this, cloner);
149    }
150
151    protected override void InitializeAction() {
152      if (SimilarityCalculatorParameter.Value == null) {
153        SimilarityCalculatorParameter.Value = OperatorsParameter.ActualValue.OfType<ISingleObjectiveSolutionSimilarityCalculator>().FirstOrDefault();
154      }
155
156      if (ComparisonFactorParameter.ActualValue == null) {
157        ComparisonFactorParameter.Value = new ItemCollection<DoubleValue>();
158        ComparisonFactorParameter.Value.Add(new DoubleValue(0));
159        ComparisonFactorParameter.Value.Add(new DoubleValue(0.5));
160        ComparisonFactorParameter.Value.Add(new DoubleValue(1));
161        ComparisonFactorParameter.Value.Add(new DoubleValue(1.5));
162      }
163
164      if (success == null) {
165        success = new int[ComparisonFactorParameter.Value.Count];
166      }
167
168      worseParentCrossoverPerformancePlot.InitializePlot(Results, "Crossover Performance compared to worse parent", "Solution Index", "Absolut Quality Difference");
169      betterParentCrossoverPerformancePlot.InitializePlot(Results, "Crossover Performance compared to better parent", "Solution Index", "Absolut Quality Difference");
170      childDiversityToWorseParentHelper.InitializePlot(Results, "Child Diversity to Worse Parent", "Solution Index", "Diversity");
171      childDiversityToBetterParentHelper.InitializePlot(Results, "Child Diversity to Better Parent", "Solution Index", "Diversity");
172      parentDiversityHelper.InitializePlot(Results, "Parent Diversity", "Solution Index", "Diversity");
173      parentQualityHelper.InitializePlot(Results, "Parent Quality Difference", "Solution Index", "Absolut Quality Difference");
174      equalParentsHelper.InitializeChart(Results, "Number of equal parents", new string[] { "Absolut number of equal parents" });
175      unwantedMutationsHelper.InitializePlot(Results, "Unwanted Mutations", "Solution Index", "Unwanted Mutation");
176
177      List<string> successfullCXRowNames = new List<string>();
178      foreach (var value in ComparisonFactorParameter.Value) {
179        successfullCXRowNames.Add(SuccessfullCrossoversRowName + value.Value.ToString());
180      }
181      successHelper.InitializeChart(Results, "Successfull Crossovers", successfullCXRowNames.ToArray());
182      Reset();
183    }
184
185    public override IOperation Apply() {
186      Initialize();
187
188      Point2D<double> worseQualityPoint, betterQualityPoint, childDiversityToWorseParent, childDiversityToBetterParent, diversityPointParent, qualityPointParent, unwantedMutationPoint;
189      var parent1 = ParentsParameter.ActualValue.First();
190      var parent2 = ParentsParameter.ActualValue.Last();
191      var qualityParent1 = ParentsQualityParameter.ActualValue.First().Value;
192      var qualityParent2 = ParentsQualityParameter.ActualValue.Last().Value;
193      var child = ChildParameter.ActualValue;
194      var qualityChild = QualityParameter.ActualValue.Value;
195
196      var parentDiversity = SimilarityCalculatorParameter.Value.CalculateSolutionSimilarity(ExecutionContext.Scope.SubScopes.First(), ExecutionContext.Scope.SubScopes.Last());
197      string curGenStr = GenerationsParameter.ActualValue.Value.ToString();
198
199      diversityPointParent = new Point2D<double>(cnt, parentDiversity);
200      qualityPointParent = new Point2D<double>(cnt, Math.Abs(qualityParent1 - qualityParent2));
201      unwantedMutationPoint = new Point2D<double>(cnt, UnwantedMutationAnalyzer.AnalyzeUnwantedMutationsForPermutationEncoding(parent1, parent2, child));
202
203      double worseQuality, betterQuality;
204
205      if (qualityParent1 > qualityParent2) {
206        if (MaximizationParameter.ActualValue.Value) {
207          childDiversityToWorseParent = new Point2D<double>(cnt, SimilarityCalculatorParameter.Value.CalculateSolutionSimilarity(ExecutionContext.Scope, ExecutionContext.Scope.SubScopes.Last()));
208          childDiversityToBetterParent = new Point2D<double>(cnt, SimilarityCalculatorParameter.Value.CalculateSolutionSimilarity(ExecutionContext.Scope, ExecutionContext.Scope.SubScopes.First()));
209          worseQuality = qualityParent2;
210          betterQuality = qualityParent1;
211        } else {
212          childDiversityToWorseParent = new Point2D<double>(cnt, SimilarityCalculatorParameter.Value.CalculateSolutionSimilarity(ExecutionContext.Scope, ExecutionContext.Scope.SubScopes.First()));
213          childDiversityToBetterParent = new Point2D<double>(cnt, SimilarityCalculatorParameter.Value.CalculateSolutionSimilarity(ExecutionContext.Scope, ExecutionContext.Scope.SubScopes.Last()));
214          worseQuality = qualityParent1;
215          betterQuality = qualityParent2;
216        }
217      } else {
218        if (MaximizationParameter.ActualValue.Value) {
219          childDiversityToWorseParent = new Point2D<double>(cnt, SimilarityCalculatorParameter.Value.CalculateSolutionSimilarity(ExecutionContext.Scope, ExecutionContext.Scope.SubScopes.First()));
220          childDiversityToBetterParent = new Point2D<double>(cnt, SimilarityCalculatorParameter.Value.CalculateSolutionSimilarity(ExecutionContext.Scope, ExecutionContext.Scope.SubScopes.Last()));
221          worseQuality = qualityParent1;
222          betterQuality = qualityParent2;
223        } else {
224          childDiversityToWorseParent = new Point2D<double>(cnt, SimilarityCalculatorParameter.Value.CalculateSolutionSimilarity(ExecutionContext.Scope, ExecutionContext.Scope.SubScopes.Last()));
225          childDiversityToBetterParent = new Point2D<double>(cnt, SimilarityCalculatorParameter.Value.CalculateSolutionSimilarity(ExecutionContext.Scope, ExecutionContext.Scope.SubScopes.First()));
226          worseQuality = qualityParent2;
227          betterQuality = qualityParent1;
228        }
229      }
230
231      worseQualityPoint = new Point2D<double>(cnt, Math.Abs(worseQuality - qualityChild));
232      betterQualityPoint = new Point2D<double>(cnt++, Math.Abs(betterQuality - qualityChild));
233
234      if (GenerationsParameter.ActualValue.Value == lastGeneration) {
235        CountSuccess(qualityChild, qualityParent1, qualityParent2);
236
237        if (parentDiversity == 1.0) {
238          equalParents++;
239        }
240      }
241
242      if (GenerationsParameter.ActualValue.Value != 0) {
243        if (GenerationsParameter.ActualValue.Value > lastGeneration) {
244          equalParentsHelper.AddPoint(equalParents);
245
246          for (int i = 0; i < ComparisonFactorParameter.Value.Count; i++) {
247            successHelper.AddPoint(SuccessfullCrossoversRowName + ComparisonFactorParameter.Value.ElementAt(i).Value.ToString(), success[i]);
248          }
249
250          Reset();
251
252          CountSuccess(qualityChild, qualityParent1, qualityParent2);
253          if (parentDiversity == 1.0) {
254            equalParents++;
255          }
256        }
257
258        betterParentCrossoverPerformancePlot.AddPoint(curGenStr, betterQualityPoint);
259        worseParentCrossoverPerformancePlot.AddPoint(curGenStr, worseQualityPoint);
260        childDiversityToWorseParentHelper.AddPoint(curGenStr, childDiversityToWorseParent);
261        childDiversityToBetterParentHelper.AddPoint(curGenStr, childDiversityToBetterParent);
262        parentDiversityHelper.AddPoint(curGenStr, diversityPointParent);
263        parentQualityHelper.AddPoint(curGenStr, qualityPointParent);
264        unwantedMutationsHelper.AddPoint(curGenStr, unwantedMutationPoint);
265      }
266
267      return base.Apply();
268    }
269
270    private void CountSuccess(double qualityChild, double qualityParent1, double qualityParent2) {
271      //track successfull cx
272      var compFactsArray = ComparisonFactorParameter.Value.ToArray();
273      for (int i = 0; i < compFactsArray.Length; i++) {
274        if (WeightedParentsQualityComparer.Compare(qualityChild, qualityParent1, qualityParent2, compFactsArray[i].Value, MaximizationParameter.ActualValue.Value)) {
275          success[i]++;
276        }
277      }
278    }
279
280    private void Reset() {
281      cnt = 0;
282      success = new int[ComparisonFactorParameter.Value.Count];
283      lastGeneration = GenerationsParameter.ActualValue.Value;
284      equalParents = 0;
285    }
286
287    public override void ClearState() {
288      betterParentCrossoverPerformancePlot.CleanUp();
289      worseParentCrossoverPerformancePlot.CleanUp();
290      childDiversityToWorseParentHelper.CleanUp();
291      childDiversityToBetterParentHelper.CleanUp();
292      parentDiversityHelper.CleanUp();
293      parentQualityHelper.CleanUp();
294      unwantedMutationsHelper.CleanUp();
295    }
296  }
297}
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