Changeset 8797 for branches/HeuristicLab.Analysis.AlgorithmBehavior/HeuristicLab.Analysis.AlgorithmBehavior.Analyzers/3.3/CrossoverPerformanceAnalyzer.cs

Timestamp:

10/11/12 17:17:36 (12 years ago)

Author:

ascheibe

Message:

#1886 added a comparison factor parameter to the crossover analyzer so that it can be defined what a successful crossover is

File:

• branches/HeuristicLab.Analysis.AlgorithmBehavior/HeuristicLab.Analysis.AlgorithmBehavior.Analyzers/3.3/CrossoverPerformanceAnalyzer.cs (modified) (12 diffs)

branches/HeuristicLab.Analysis.AlgorithmBehavior/HeuristicLab.Analysis.AlgorithmBehavior.Analyzers/3.3/CrossoverPerformanceAnalyzer.cs

@@ -27 +27 @@
 using HeuristicLab.Data;
 using HeuristicLab.Encodings.PermutationEncoding;
-using HeuristicLab.Operators;
 using HeuristicLab.Optimization;
 using HeuristicLab.Parameters;
@@ -35 +34 @@
   [Item("CrossoverPerformanceAnalyzer", "An operator that analyzes the performance of crossovers.")]
   [StorableClass]
-  public class CrossoverPerformanceAnalyzer : SingleSuccessorOperator, IAnalyzer {
+  public class CrossoverPerformanceAnalyzer : InitializableOperator, IAnalyzer {
     private const string ResultsParameterName = "Results";
     private const string GenerationsParameterName = "Generations";
+    private const string SuccessfullCrossoversRowName = "Successfull Crossovers per Generation with CompFact ";
 
     #region IAnalyzer Members
@@ -46 +46 @@
 
     #region Parameter properties
+    public IValueLookupParameter<BoolValue> MaximizationParameter {
+      get { return (IValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
+    }
+    public IValueParameter<ItemCollection<DoubleValue>> ComparisonFactorParameter {
+      get { return (IValueParameter<ItemCollection<DoubleValue>>)Parameters["ComparisonFactor"]; }
+    }
     public ILookupParameter<ResultCollection> ResultsParameter {
       get { return (ILookupParameter<ResultCollection>)Parameters[ResultsParameterName]; }
@@ -85 +91 @@
     private int cnt = 0;
     [Storable]
-    private int success = 0;
+    private int[] success;
     [Storable]
     private int lastGeneration = 0;
@@ -98 +104 @@
       : base(original, cloner) {
       cnt = original.cnt;
-      success = original.success;
+      success = (int[])original.success.Clone();
       lastGeneration = original.lastGeneration;
       equalParents = original.equalParents;
@@ -129 +135 @@
       Parameters.Add(new ValueParameter<ISingleObjectiveSolutionSimilarityCalculator>("SimilarityCalculator"));
       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 ValueParameter<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."));
+      ComparisonFactorParameter.Value.Add(new DoubleValue(0));
+      ComparisonFactorParameter.Value.Add(new DoubleValue(0.5));
+      ComparisonFactorParameter.Value.Add(new DoubleValue(1));
+
 
       plotHelper = new ScatterPlotHelper(false, true);
@@ -142 +154 @@
     }
 
-    public override IOperation Apply() {
+    protected override void InitializeAction() {
       if (SimilarityCalculatorParameter.Value == null) {
         SimilarityCalculatorParameter.Value = OperatorsParameter.ActualValue.OfType<ISingleObjectiveSolutionSimilarityCalculator>().FirstOrDefault();
+      }
+
+      if (success == null) {
+        success = new int[ComparisonFactorParameter.Value.Count];
       }
 
@@ -150 +166 @@
       childDiversityHelper.InitializePlot(Results, "Child Diversity", "Solution Index", "Diversity");
       parentDiversityHelper.InitializePlot(Results, "Parent Diversity", "Solution Index", "Diversity");
-
-      performanceHelper.InitializeChart(Results, "Average Crossover Performance", "Average Crossover Performance per Generation");
-      successHelper.InitializeChart(Results, "Successfull Crossovers", "Successfull Crossovers per Generation");
-      equalParentsHelper.InitializeChart(Results, "Number of equal parents", "Absolut number of equal parents");
+      performanceHelper.InitializeChart(Results, "Average Crossover Performance", new string[] { "Average Crossover Performance per Generation" });
+      equalParentsHelper.InitializeChart(Results, "Number of equal parents", new string[] { "Absolut number of equal parents" });
+
+      List<string> successfullCXRowNames = new List<string>();
+      foreach (var value in ComparisonFactorParameter.Value) {
+        successfullCXRowNames.Add(SuccessfullCrossoversRowName + value.Value.ToString());
+      }
+      successHelper.InitializeChart(Results, "Successfull Crossovers", successfullCXRowNames.ToArray());
+    }
+
+    public override IOperation Apply() {
+      Initialize();
 
       Point2D<double> qualityPoint, diversityPointChild, diversityPointParent;
       var qualityParent1 = ParentsQualityParameter.ActualValue.First().Value;
       var qualityParent2 = ParentsQualityParameter.ActualValue.Last().Value;
+      var qualityChild = QualityParameter.ActualValue.Value;
       var child = ChildParameter.ActualValue;
       var parent1 = ParentsParameter.ActualValue.First();
@@ -163 +188 @@
       var parentDiversity = SimilarityCalculatorParameter.Value.CalculateSolutionSimilarity(ExecutionContext.Scope.SubScopes.First(), ExecutionContext.Scope.SubScopes.Last());
       string curGenStr = GenerationsParameter.ActualValue.Value.ToString();
-
 
       diversityPointParent = new Point2D<double>(cnt, parentDiversity);
@@ -173 +197 @@
       }
 
-      qualityPoint = new Point2D<double>(cnt++, worseQuality - QualityParameter.ActualValue.Value);
-      if ((worseQuality - QualityParameter.ActualValue.Value) > 0) {
-        success++;
-      }
+      qualityPoint = new Point2D<double>(cnt++, worseQuality - qualityChild);
       qualityPoints.Add(qualityPoint.Y);
+
+      //track successfull cx
+      var compFactsArray = ComparisonFactorParameter.Value.ToArray();
+      for (int i = 0; i < compFactsArray.Length; i++) {
+        if (WeightedParentsQualityComparer.Compare(qualityChild, qualityParent1, qualityParent2, compFactsArray[i].Value, MaximizationParameter.ActualValue.Value)) {
+          success[i]++;
+        }
+      }
 
       if (parentDiversity == 1.0) {
@@ -188 +217 @@
 
           performanceHelper.AddPoint(avg);
-          successHelper.AddPoint(success);
           equalParentsHelper.AddPoint(equalParents);
+
+          for (int i = 0; i < compFactsArray.Length; i++) {
+            successHelper.AddPoint(SuccessfullCrossoversRowName + compFactsArray[i].Value.ToString(), success[i]);
+          }
 
           Reset();
@@ -206 +238 @@
     private void Reset() {
       cnt = 0;
-      success = 0;
+      success = new int[ComparisonFactorParameter.Value.Count];
       lastGeneration = GenerationsParameter.ActualValue.Value;
       qualityPoints.Clear();