Changeset 12422 for trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers

Timestamp:

06/10/15 11:29:34 (10 years ago)

Author:

mkommend

Message:

#2320: Merged the encoding class and all accompanying changes in the trunk.

Location:

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic

Files:

• . (modified) (1 prop)
• 3.4/Crossovers/MultiSymbolicDataAnalysisExpressionCrossover.cs (modified) (5 diffs)
• 3.4/Crossovers/SymbolicDataAnalysisExpressionContextAwareCrossover.cs (modified) (2 diffs)
• 3.4/Crossovers/SymbolicDataAnalysisExpressionDepthConstrainedCrossover.cs (modified) (3 diffs)
• 3.4/Crossovers/SymbolicDataAnalysisExpressionDeterministicBestCrossover.cs (modified) (2 diffs)
• 3.4/Crossovers/SymbolicDataAnalysisExpressionProbabilisticFunctionalCrossover.cs (modified) (3 diffs)
• 3.4/Crossovers/SymbolicDataAnalysisExpressionSemanticSimilarityCrossover.cs (modified) (2 diffs)

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/MultiSymbolicDataAnalysisExpressionCrossover.cs

@@ -35 +35 @@
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
   [Item("MultiSymbolicDataAnalysisExpressionCrossover", "Randomly selects and applies one of its crossovers every time it is called.")]
+  [StorableClass]
   public class MultiSymbolicDataAnalysisExpressionCrossover<T> : StochasticMultiBranch<ISymbolicExpressionTreeCrossover>,
     ISymbolicDataAnalysisExpressionCrossover<T> where T : class, IDataAnalysisProblemData {
     private const string ParentsParameterName = "Parents";
-    private const string ChildParameterName = "Child";
+    private const string SymbolicExpressionTreeParameterName = "SymbolicExpressionTree";
     private const string MaximumSymbolicExpressionTreeLengthParameterName = "MaximumSymbolicExpressionTreeLength";
     private const string MaximumSymbolicExpressionTreeDepthParameterName = "MaximumSymbolicExpressionTreeDepth";
@@ -62 +63 @@
       get { return (ScopeTreeLookupParameter<ISymbolicExpressionTree>)Parameters[ParentsParameterName]; }
     }
-    public ILookupParameter<ISymbolicExpressionTree> ChildParameter {
-      get { return (ILookupParameter<ISymbolicExpressionTree>)Parameters[ChildParameterName]; }
+    public ILookupParameter<ISymbolicExpressionTree> SymbolicExpressionTreeParameter {
+      get { return (ILookupParameter<ISymbolicExpressionTree>)Parameters[SymbolicExpressionTreeParameterName]; }
     }
     public IValueLookupParameter<IntValue> MaximumSymbolicExpressionTreeLengthParameter {
@@ -99 +100 @@
       Parameters.Add(new ValueLookupParameter<IntRange>(SymbolicDataAnalysisEvaluationPartitionParameterName, "The start index of the dataset partition on which the symbolic data analysis solution should be evaluated."));
       Parameters.Add(new ScopeTreeLookupParameter<ISymbolicExpressionTree>(ParentsParameterName, "The parent symbolic expression trees which should be crossed."));
-      Parameters.Add(new LookupParameter<ISymbolicExpressionTree>(ChildParameterName, "The child symbolic expression tree resulting from the crossover."));
+      Parameters.Add(new LookupParameter<ISymbolicExpressionTree>(SymbolicExpressionTreeParameterName, "The child symbolic expression tree resulting from the crossover."));
 
       EvaluatorParameter.Hidden = true;
@@ -111 +112 @@
 
       SelectedOperatorParameter.ActualName = "SelectedCrossoverOperator";
+    }
+
+    [StorableHook(HookType.AfterDeserialization)]
+    private void AfterDeserialization() {
+      // BackwardsCompatibility3.3
+      #region Backwards compatible code, remove with 3.4
+      if (!Parameters.ContainsKey(SymbolicExpressionTreeParameterName))
+        Parameters.Add(new LookupParameter<ISymbolicExpressionTree>(SymbolicExpressionTreeParameterName, "The symbolic expression tree on which the operator should be applied."));
+      #endregion
     }
 
@@ -155 +165 @@
     private void ParameterizeCrossovers() {
       foreach (ISymbolicExpressionTreeCrossover op in Operators) {
-        op.ChildParameter.ActualName = ChildParameter.Name;
+        op.SymbolicExpressionTreeParameter.ActualName = SymbolicExpressionTreeParameter.Name;
         op.ParentsParameter.ActualName = ParentsParameter.Name;
       }

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/SymbolicDataAnalysisExpressionContextAwareCrossover.cs

@@ -27 +27 @@
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Random;
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
@@ -68 +69 @@
           possibleChildren.Add(n);
       });
-      var selectedChild = possibleChildren.SelectRandom(random);
+
+      var selectedChild = possibleChildren.SampleRandom(random);
       var crossoverPoints = new List<CutPoint>();
       var qualities = new List<Tuple<CutPoint, double>>();

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/SymbolicDataAnalysisExpressionDepthConstrainedCrossover.cs

@@ -29 +29 @@
 using HeuristicLab.Parameters;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Random;
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
@@ -115 +116 @@
         throw new Exception("No crossover points available in the first parent");
 
-      var crossoverPoint0 = crossoverPoints0.SelectRandom(random);
-
+      var crossoverPoint0 = crossoverPoints0.SampleRandom(random);
       int level = parent0.Root.GetBranchLevel(crossoverPoint0.Child);
       int length = parent0.Root.GetLength() - crossoverPoint0.Child.GetLength();
@@ -126 +126 @@
                              select s).ToList();
       if (allowedBranches.Count == 0) return parent0;
-      var selectedBranch = allowedBranches.SelectRandom(random);
+
+      var selectedBranch = allowedBranches.SampleRandom(random);
       Swap(crossoverPoint0, selectedBranch);
       return parent0;

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/SymbolicDataAnalysisExpressionDeterministicBestCrossover.cs

@@ -27 +27 @@
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Random;
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
@@ -67 +68 @@
           crossoverPoints0.Add(new CutPoint(n.Parent, n));
       });
-      CutPoint crossoverPoint0 = crossoverPoints0.SelectRandom(random);
+
+      CutPoint crossoverPoint0 = crossoverPoints0.SampleRandom(random);
       int level = parent0.Root.GetBranchLevel(crossoverPoint0.Child);
       int length = parent0.Root.GetLength() - crossoverPoint0.Child.GetLength();

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/SymbolicDataAnalysisExpressionProbabilisticFunctionalCrossover.cs

@@ -27 +27 @@
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Random;
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
@@ -69 +70 @@
         }
       });
-      var crossoverPoint0 = crossoverPoints0.SelectRandom(random);
+
+      var crossoverPoint0 = crossoverPoints0.SampleRandom(random);
       int level = parent0.Root.GetBranchLevel(crossoverPoint0.Child);
       int length = parent0.Root.GetLength() - crossoverPoint0.Child.GetLength();
@@ -137 +139 @@
           weights[i] /= sum;
 
+#pragma warning disable 612, 618
         selectedBranch = allowedBranches.SelectRandom(weights, random);
+#pragma warning restore 612, 618
       }
       Swap(crossoverPoint0, selectedBranch);

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/SymbolicDataAnalysisExpressionSemanticSimilarityCrossover.cs

@@ -28 +28 @@
 using HeuristicLab.Parameters;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Random;
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
@@ -81 +82 @@
           crossoverPoints0.Add(new CutPoint(n.Parent, n));
       });
-      var crossoverPoint0 = crossoverPoints0.SelectRandom(random);
+
+      var crossoverPoint0 = crossoverPoints0.SampleRandom(random);
       int level = parent0.Root.GetBranchLevel(crossoverPoint0.Child);
       int length = parent0.Root.GetLength() - crossoverPoint0.Child.GetLength();