Changeset 12155 for branches/HeuristicLab.EvolutionTracking/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/TreeMatching/SymbolicExpressionTreePhenotypicSimilarityCalculator.cs

Timestamp:

03/07/15 12:11:09 (10 years ago)

Author:

bburlacu

Message:

#1772: Merged trunk changes.

Location:

branches/HeuristicLab.EvolutionTracking/HeuristicLab.Problems.DataAnalysis.Symbolic

Files:

• . (modified) (1 prop)
• 3.4/TreeMatching/SymbolicExpressionTreePhenotypicSimilarityCalculator.cs (modified) (4 diffs)

branches/HeuristicLab.EvolutionTracking/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/TreeMatching/SymbolicExpressionTreePhenotypicSimilarityCalculator.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2014 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.
@@ -20 +20 @@
 #endregion
 
+using System;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
@@ -28 +29 @@
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
-  [Item("PhenotypicSimilarityCalculator", "An operator that calculates the similarity betweeon two trees based on the correlation of their outputs.")]
+  [Item("SymbolicExpressionTreePhenotypicSimilarityCalculator", "An operator that calculates the similarity betweeon two trees based on the correlation of their outputs.")]
   [StorableClass]
-  public class PhenotypicSimilarityCalculator : SingleObjectiveSolutionSimilarityCalculator, ISymbolicDataAnalysisExpressionSimilarityCalculator {
+  public class SymbolicExpressionTreePhenotypicSimilarityCalculator : SolutionSimilarityCalculator {
+    [Storable]
     public IDataAnalysisProblemData ProblemData { get; set; }
+    [Storable]
     public ISymbolicDataAnalysisExpressionTreeInterpreter Interpreter { get; set; }
 
+    protected override bool IsCommutative { get { return true; } }
+
     [StorableConstructor]
-    protected PhenotypicSimilarityCalculator(bool deserializing) : base(deserializing) { }
+    protected SymbolicExpressionTreePhenotypicSimilarityCalculator(bool deserializing) : base(deserializing) { }
 
-    public PhenotypicSimilarityCalculator(PhenotypicSimilarityCalculator original, Cloner cloner)
+    public SymbolicExpressionTreePhenotypicSimilarityCalculator(SymbolicExpressionTreePhenotypicSimilarityCalculator original, Cloner cloner)
       : base(original, cloner) {
-      this.ProblemData = original.ProblemData;
-      this.Interpreter = original.Interpreter;
+      this.ProblemData = cloner.Clone(original.ProblemData);
+      this.Interpreter = cloner.Clone(original.Interpreter);
     }
 
     public override IDeepCloneable Clone(Cloner cloner) {
-      return new PhenotypicSimilarityCalculator(this, cloner);
+      return new SymbolicExpressionTreePhenotypicSimilarityCalculator(this, cloner);
     }
 
-    public PhenotypicSimilarityCalculator() { }
+    public SymbolicExpressionTreePhenotypicSimilarityCalculator() { }
 
     public double CalculateSimilarity(ISymbolicExpressionTree t1, ISymbolicExpressionTree t2) {
+      if (Interpreter == null || ProblemData == null)
+        throw new InvalidOperationException("Cannot calculate phenotypic similarity when no interpreter or problem data were set.");
+
       var v1 = Interpreter.GetSymbolicExpressionTreeValues(t1, ProblemData.Dataset, ProblemData.TrainingIndices);
       var v2 = Interpreter.GetSymbolicExpressionTreeValues(t2, ProblemData.Dataset, ProblemData.TrainingIndices);
+
+      if (v1.Variance().IsAlmost(0) && v2.Variance().IsAlmost(0))
+        return 1.0;
 
       OnlineCalculatorError error;
@@ -63 +74 @@
 
     public override double CalculateSolutionSimilarity(IScope leftSolution, IScope rightSolution) {
+      if (leftSolution == rightSolution)
+        return 1.0;
+
+      if (!leftSolution.Variables.ContainsKey("EstimatedValues") || !rightSolution.Variables.ContainsKey("EstimatedValues"))
+        throw new ArgumentException("No estimated values are present in the subscopes.");
+
       var leftValues = (DoubleArray)leftSolution.Variables["EstimatedValues"].Value;
       var rightValues = (DoubleArray)rightSolution.Variables["EstimatedValues"].Value;
+
+      if (leftValues.Variance().IsAlmost(0) && rightValues.Variance().IsAlmost(0))
+        return 1.0;
+
       OnlineCalculatorError error;
       var r2 = OnlinePearsonsRSquaredCalculator.Calculate(leftValues, rightValues, out error);