Changeset 7989 for branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis.Views/3.4/InteractiveSymbolicTimeSeriesPrognosisSolutionSimplifierView.cs

Timestamp:

06/12/12 10:31:56 (12 years ago)

Author:

mkommend

Message:

#1081: Improved performance of time series prognosis.

File:

• branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis.Views/3.4/InteractiveSymbolicTimeSeriesPrognosisSolutionSimplifierView.cs (modified) (3 diffs)

branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis.Views/3.4/InteractiveSymbolicTimeSeriesPrognosisSolutionSimplifierView.cs

@@ -50 +50 @@
 
     protected override void UpdateModel(ISymbolicExpressionTree tree) {
-      var model = new SymbolicTimeSeriesPrognosisModel(tree, Content.Model.Interpreter, Content.ProblemData.TargetVariables.ToArray());
+      var model = new SymbolicTimeSeriesPrognosisModel(tree, Content.Model.Interpreter);
       SymbolicTimeSeriesPrognosisModel.Scale(model, Content.ProblemData);
       Content.Model = model;
@@ -66 +66 @@
     protected override Dictionary<ISymbolicExpressionTreeNode, double> CalculateImpactValues(ISymbolicExpressionTree tree) {
       var interpreter = Content.Model.Interpreter;
+      var rows = Content.ProblemData.TrainingIndizes;
       var dataset = Content.ProblemData.Dataset;
-      var rows = Content.ProblemData.TrainingIndizes;
-      Dictionary<ISymbolicExpressionTreeNode, double> impactValues =
-        new Dictionary<ISymbolicExpressionTreeNode, double>();
-      var originalOutput = interpreter.GetSymbolicExpressionTreeValues(tree, dataset, Content.ProblemData.TargetVariables.ToArray(), rows, 1)
-        .ToArray();
-      int i = 0;
-      int nTargetVariables = Content.ProblemData.TargetVariables.Count();
-      foreach (var targetVariable in Content.ProblemData.TargetVariables) {
-        List<ISymbolicExpressionTreeNode> nodes = tree.Root.GetSubtree(0).GetSubtree(i).IterateNodesPostfix().ToList();
-        var targetValues = dataset.GetDoubleValues(targetVariable, rows);
-        OnlineCalculatorError errorState;
-        double originalR2 = OnlinePearsonsRSquaredCalculator.Calculate(targetValues, originalOutput.Skip(i).TakeEvery(nTargetVariables), out errorState);
-        if (errorState != OnlineCalculatorError.None) originalR2 = 0.0;
+      var targetVariable = Content.ProblemData.TargetVariable;
+      var targetValues = dataset.GetDoubleValues(targetVariable, rows);
+      var originalOutput = interpreter.GetSymbolicExpressionTreeValues(tree, dataset, rows).ToArray();
 
-        foreach (ISymbolicExpressionTreeNode node in nodes) {
-          var parent = node.Parent;
-          constantNode.Value = CalculateReplacementValue(node, tree);
-          ISymbolicExpressionTreeNode replacementNode = constantNode;
-          SwitchNode(parent, node, replacementNode);
-          var newOutput = interpreter.GetSymbolicExpressionTreeValues(tree, dataset, Content.ProblemData.TargetVariables.ToArray(), rows, 1);
-          double newR2 = OnlinePearsonsRSquaredCalculator.Calculate(targetValues, newOutput.Skip(i).TakeEvery(nTargetVariables), out errorState);
-          if (errorState != OnlineCalculatorError.None) newR2 = 0.0;
+      Dictionary<ISymbolicExpressionTreeNode, double> impactValues = new Dictionary<ISymbolicExpressionTreeNode, double>();
+      List<ISymbolicExpressionTreeNode> nodes = tree.Root.GetSubtree(0).GetSubtree(0).IterateNodesPostfix().ToList();
+      OnlineCalculatorError errorState;
+      double originalR2 = OnlinePearsonsRSquaredCalculator.Calculate(targetValues, originalOutput, out errorState);
+      if (errorState != OnlineCalculatorError.None) originalR2 = 0.0;
 
-          // impact = 0 if no change
-          // impact < 0 if new solution is better
-          // impact > 0 if new solution is worse
-          impactValues[node] = originalR2 - newR2;
-          SwitchNode(parent, replacementNode, node);
-        }
-        i++;
+      foreach (ISymbolicExpressionTreeNode node in nodes) {
+        var parent = node.Parent;
+        constantNode.Value = CalculateReplacementValue(node, tree);
+        ISymbolicExpressionTreeNode replacementNode = constantNode;
+        SwitchNode(parent, node, replacementNode);
+        var newOutput = interpreter.GetSymbolicExpressionTreeValues(tree, dataset, rows);
+        double newR2 = OnlinePearsonsRSquaredCalculator.Calculate(targetValues, newOutput, out errorState);
+        if (errorState != OnlineCalculatorError.None) newR2 = 0.0;
+
+        // impact = 0 if no change
+        // impact < 0 if new solution is better
+        // impact > 0 if new solution is worse
+        impactValues[node] = originalR2 - newR2;
+        SwitchNode(parent, replacementNode, node);
       }
       return impactValues;
@@ -113 +108 @@
       var interpreter = Content.Model.Interpreter;
       var rows = Content.ProblemData.TrainingIndizes;
-      var allPrognosedValues = interpreter.GetSymbolicExpressionTreeValues(tempTree, Content.ProblemData.Dataset, Content.ProblemData.TargetVariables.ToArray(), rows, 1);
+      var allPrognosedValues = interpreter.GetSymbolicExpressionTreeValues(tempTree, Content.ProblemData.Dataset, rows);
 
       return allPrognosedValues.Median();