Changeset 1894 for trunk/sources/HeuristicLab.GP.StructureIdentification/3.3/Evaluators/VarianceAccountedForEvaluator.cs

Timestamp:

05/25/09 18:43:26 (15 years ago)

Author:

gkronber

Message:

Fixed #643 (Simple evaluation operators in HL.Modeling and GP specific evaluation operators in HL.GP.StructureIdentification should be unified).

File:

• trunk/sources/HeuristicLab.GP.StructureIdentification/3.3/Evaluators/VarianceAccountedForEvaluator.cs (modified) (2 diffs)

trunk/sources/HeuristicLab.GP.StructureIdentification/3.3/Evaluators/VarianceAccountedForEvaluator.cs

@@ -28 +28 @@
 using HeuristicLab.Operators;
 using HeuristicLab.DataAnalysis;
+using HeuristicLab.Modeling;
 
 namespace HeuristicLab.GP.StructureIdentification {
-  public class VarianceAccountedForEvaluator : GPEvaluatorBase {
+  /// <summary>
+  /// The Variance Accounted For (VAF) function calculates is computed as
+  /// VAF(y,y') = ( 1 - var(y-y')/var(y) )
+  /// where y' denotes the predicted / modelled values for y and var(x) the variance of a signal x.
+  /// </summary>
+  public class VarianceAccountedForEvaluator : SimpleGPEvaluatorBase {
+    public override string OutputVariableName {
+      get {
+        return "VAF";
+      }
+    }
     public override string Description {
       get {
@@ -42 +53 @@
     }
 
-    /// <summary>
-    /// The Variance Accounted For (VAF) function calculates is computed as
-    /// VAF(y,y') = ( 1 - var(y-y')/var(y) )
-    /// where y' denotes the predicted / modelled values for y and var(x) the variance of a signal x.
-    /// </summary>
-    public VarianceAccountedForEvaluator()
-      : base() {
-      AddVariableInfo(new VariableInfo("VAF", "The variance-accounted-for quality of the model", typeof(DoubleData), VariableKind.New));
-
-    }
-
-    public override void Evaluate(IScope scope, ITreeEvaluator evaluator, Dataset dataset, int targetVariable, int start, int end, bool updateTargetValues) {
-      int nSamples = end - start;
-      double[] errors = new double[nSamples];
-      double[] originalTargetVariableValues = new double[nSamples];
-      for (int sample = start; sample < end; sample++) {
-        double estimated = evaluator.Evaluate(sample);
-        double original = dataset.GetValue(sample, targetVariable);
-        if (updateTargetValues) {
-          dataset.SetValue(sample, targetVariable, estimated);
-        }
-        if (!double.IsNaN(original) && !double.IsInfinity(original)) {
-          errors[sample - start] = original - estimated;
-          originalTargetVariableValues[sample - start] = original;
-        } else {
-          errors[sample - start] = double.NaN;
-          originalTargetVariableValues[sample - start] = double.NaN;
-        }
-      }
-      double errorsVariance = Statistics.Variance(errors);
-      double originalsVariance = Statistics.Variance(originalTargetVariableValues);
-      double quality = 1 - errorsVariance / originalsVariance;
+    public override double Evaluate(double[,] values) {
+      double quality = SimpleVarianceAccountedForEvaluator.Calculate(values);
 
       if (double.IsNaN(quality) || double.IsInfinity(quality)) {
         quality = double.MaxValue;
       }
-      DoubleData vaf = GetVariableValue<DoubleData>("VAF", scope, false, false);
-      if (vaf == null) {
-        vaf = new DoubleData();
-        scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("VAF"), vaf));
-      }
-
-      vaf.Data = quality;
+      return quality;
     }
   }