Changeset 5275 for branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/SymbolicRegressionSolution.cs

Timestamp:

01/11/11 15:03:46 (13 years ago)

Author:

gkronber

Message:

Merged changes from trunk to data analysis exploration branch and added fractional distance metric evaluator. #1142

File:

• branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/SymbolicRegressionSolution.cs (modified) (4 diffs)

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/SymbolicRegressionSolution.cs

@@ -24 +24 @@
 using System.Drawing;
 using System.Linq;
+using HeuristicLab.Common;
 using HeuristicLab.Core;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
@@ -34 +35 @@
   [Item("SymbolicRegressionSolution", "Represents a solution for a symbolic regression problem which can be visualized in the GUI.")]
   [StorableClass]
-  public sealed class SymbolicRegressionSolution : DataAnalysisSolution {
-    public SymbolicRegressionSolution() : base() { } // for cloning
-    [StorableConstructor]
-    public SymbolicRegressionSolution(bool deserializing) : base(deserializing) { }
-    public SymbolicRegressionSolution(DataAnalysisProblemData problemData, SymbolicRegressionModel model, double lowerEstimationLimit, double upperEstimationLimit)
-      : base(problemData, lowerEstimationLimit, upperEstimationLimit) {
-      this.Model = model;
-    }
-
+  public class SymbolicRegressionSolution : DataAnalysisSolution {
     public override Image ItemImage {
       get { return HeuristicLab.Common.Resources.VS2008ImageLibrary.Function; }
@@ -50 +43 @@
       get { return (SymbolicRegressionModel)base.Model; }
       set { base.Model = value; }
+    }
+
+    protected List<double> estimatedValues;
+    public override IEnumerable<double> EstimatedValues {
+      get {
+        if (estimatedValues == null) RecalculateEstimatedValues();
+        return estimatedValues;
+      }
+    }
+
+    public override IEnumerable<double> EstimatedTrainingValues {
+      get { return GetEstimatedValues(ProblemData.TrainingIndizes); }
+    }
+
+    public override IEnumerable<double> EstimatedTestValues {
+      get { return GetEstimatedValues(ProblemData.TestIndizes); }
+    }
+
+    [StorableConstructor]
+    protected SymbolicRegressionSolution(bool deserializing) : base(deserializing) { }
+    protected SymbolicRegressionSolution(SymbolicRegressionSolution original, Cloner cloner)
+      : base(original, cloner) {
+    }
+    public SymbolicRegressionSolution(DataAnalysisProblemData problemData, SymbolicRegressionModel model, double lowerEstimationLimit, double upperEstimationLimit)
+      : base(problemData, lowerEstimationLimit, upperEstimationLimit) {
+      this.Model = model;
+    }
+
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new SymbolicRegressionSolution(this, cloner);
     }
 
@@ -65 +88 @@
     }
 
-    private List<double> estimatedValues;
-    public override IEnumerable<double> EstimatedValues {
-      get {
-        if (estimatedValues == null) RecalculateEstimatedValues();
-        return estimatedValues.AsEnumerable();
-      }
-    }
-
-    public override IEnumerable<double> EstimatedTrainingValues {
-      get {
-        if (estimatedValues == null) RecalculateEstimatedValues();
-        int start = ProblemData.TrainingSamplesStart.Value;
-        int n = ProblemData.TrainingSamplesEnd.Value - start;
-        return estimatedValues.Skip(start).Take(n).ToList();
-      }
-    }
-
-    public override IEnumerable<double> EstimatedTestValues {
-      get {
-        if (estimatedValues == null) RecalculateEstimatedValues();
-        int start = ProblemData.TestSamplesStart.Value;
-        int n = ProblemData.TestSamplesEnd.Value - start;
-        return estimatedValues.Skip(start).Take(n).ToList();
-      }
+    public virtual IEnumerable<double> GetEstimatedValues(IEnumerable<int> rows) {
+      if (estimatedValues == null) RecalculateEstimatedValues();
+      foreach (int row in rows)
+        yield return estimatedValues[row];
     }
   }