Changeset 8206 for branches/GP-MoveOperators/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective

Timestamp:

07/03/12 16:46:35 (12 years ago)

Author:

gkronber

Message:

#1847: merged r8084:8205 from trunk into GP move operators branch

Location:

branches/GP-MoveOperators

Files:

• . (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectiveProblem.cs (modified) (3 diffs)

branches/GP-MoveOperators/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectiveProblem.cs

@@ -53 +53 @@
     [StorableConstructor]
     protected SymbolicRegressionMultiObjectiveProblem(bool deserializing) : base(deserializing) { }
-    protected SymbolicRegressionMultiObjectiveProblem(SymbolicRegressionMultiObjectiveProblem original, Cloner cloner) : base(original, cloner) { }
+    protected SymbolicRegressionMultiObjectiveProblem(SymbolicRegressionMultiObjectiveProblem original, Cloner cloner)
+      : base(original, cloner) {
+      RegisterEventHandlers();
+    }
     public override IDeepCloneable Clone(Cloner cloner) { return new SymbolicRegressionMultiObjectiveProblem(this, cloner); }
 
@@ -66 +69 @@
       MaximumSymbolicExpressionTreeLength.Value = InitialMaximumTreeLength;
 
-      SymbolicExpressionTreeGrammarParameter.ValueChanged += (o, e) => ConfigureGrammarSymbols();
-
+      RegisterEventHandlers();
       ConfigureGrammarSymbols();
       InitializeOperators();
       UpdateEstimationLimits();
+    }
+
+    [StorableHook(HookType.AfterDeserialization)]
+    private void AfterDeserialization() {
+      RegisterEventHandlers();
+    }
+
+    private void RegisterEventHandlers() {
+      SymbolicExpressionTreeGrammarParameter.ValueChanged += (o, e) => ConfigureGrammarSymbols();
     }
 
@@ -85 +96 @@
 
     private void UpdateEstimationLimits() {
-      if (ProblemData.TrainingIndizes.Any()) {
-        var targetValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes).ToList();
+      if (ProblemData.TrainingIndices.Any()) {
+        var targetValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices).ToList();
         var mean = targetValues.Average();
         var range = targetValues.Max() - targetValues.Min();