Changeset 12848 for branches/DataAnalysis.ComplexityAnalyzer/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectivePearsonRSquaredTreeSizeEvaluator.cs

Timestamp:

08/12/15 10:35:02 (9 years ago)

Author:

mkommend

Message:

#2175: Merged trunk changes and extracted parameters of evaluators to their base class.

File:

• branches/DataAnalysis.ComplexityAnalyzer/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectivePearsonRSquaredTreeSizeEvaluator.cs (modified) (5 diffs)

branches/DataAnalysis.ComplexityAnalyzer/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectivePearsonRSquaredTreeSizeEvaluator.cs

@@ -26 +26 @@
 using HeuristicLab.Data;
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
-using HeuristicLab.Parameters;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
 
@@ -33 +32 @@
   [StorableClass]
   public class SymbolicRegressionMultiObjectivePearsonRSquaredTreeSizeEvaluator : SymbolicRegressionMultiObjectiveEvaluator {
-    private const string useConstantOptimizationParameterName = "Use constant optimization";
-    public IFixedValueParameter<BoolValue> UseConstantOptimizationParameter {
-      get { return (IFixedValueParameter<BoolValue>)Parameters[useConstantOptimizationParameterName]; }
-    }
-    public bool UseConstantOptimization {
-      get { return UseConstantOptimizationParameter.Value.Value; }
-      set { UseConstantOptimizationParameter.Value.Value = value; }
-    }
-
     [StorableConstructor]
     protected SymbolicRegressionMultiObjectivePearsonRSquaredTreeSizeEvaluator(bool deserializing) : base(deserializing) { }
@@ -51 +41 @@
     }
 
-    public SymbolicRegressionMultiObjectivePearsonRSquaredTreeSizeEvaluator() : base()
-    {
-      Parameters.Add(new FixedValueParameter<BoolValue>(useConstantOptimizationParameterName, "", new BoolValue(false)));
-    }
-
-    [StorableHook(HookType.AfterDeserialization)]
-    private void AfterDeserialization() {
-      if (!Parameters.ContainsKey(useConstantOptimizationParameterName)) {
-        Parameters.Add(new FixedValueParameter<BoolValue>(useConstantOptimizationParameterName, "", new BoolValue(false)));
-      }
-    }
+    public SymbolicRegressionMultiObjectivePearsonRSquaredTreeSizeEvaluator() : base() { }
 
     public override IEnumerable<bool> Maximization { get { return new bool[2] { true, false }; } }
@@ -76 +56 @@
         SymbolicRegressionConstantOptimizationEvaluator.OptimizeConstants(interpreter, solution, problemData, rows, applyLinearScaling, 5, estimationLimits.Upper, estimationLimits.Lower);
       }
-      double[] qualities = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, solution, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, ProblemDataParameter.ActualValue, rows, ApplyLinearScalingParameter.ActualValue.Value);
+      double[] qualities = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, solution, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, ProblemDataParameter.ActualValue, rows, ApplyLinearScalingParameter.ActualValue.Value, DecimalPlaces);
       QualitiesParameter.ActualValue = new DoubleArray(qualities);
       return base.InstrumentedApply();
     }
 
-    public static double[] Calculate(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, IRegressionProblemData problemData, IEnumerable<int> rows, bool applyLinearScaling) {
+    public static double[] Calculate(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, IRegressionProblemData problemData, IEnumerable<int> rows, bool applyLinearScaling, int decimalPlaces) {
       double r2 = SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.Calculate(interpreter, solution, lowerEstimationLimit, upperEstimationLimit, problemData, rows, applyLinearScaling);
-      r2 = Math.Round(r2, 3);
+      if (decimalPlaces >= 0)
+        r2 = Math.Round(r2, decimalPlaces);
       return new double[2] { r2, solution.Length };
     }
@@ -92 +73 @@
       ApplyLinearScalingParameter.ExecutionContext = context;
 
-      double[] quality = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, tree, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, problemData, rows, ApplyLinearScalingParameter.ActualValue.Value);
+      double[] quality = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, tree, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, problemData, rows, ApplyLinearScalingParameter.ActualValue.Value, DecimalPlaces);
 
       SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = null;