Changeset 8971 for branches/RuntimeOptimizer/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression.Views

Timestamp:

11/29/12 09:57:15 (11 years ago)

Author:

abeham

Message:

#1985: Synchronized with trunk

Location:

branches/RuntimeOptimizer

Files:

• . (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression.Views (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression.Views/3.4/InteractiveSymbolicRegressionSolutionSimplifierView.cs (modified) (4 diffs)

branches/RuntimeOptimizer/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression.Views/3.4/InteractiveSymbolicRegressionSolutionSimplifierView.cs

@@ -23 +23 @@
 using System.Collections.Generic;
 using System.Linq;
-using HeuristicLab.Common;
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
 using HeuristicLab.Problems.DataAnalysis.Symbolic.Views;
@@ -29 +28 @@
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression.Views {
   public partial class InteractiveSymbolicRegressionSolutionSimplifierView : InteractiveSymbolicDataAnalysisSolutionSimplifierView {
-    private readonly ConstantTreeNode constantNode;
-    private readonly SymbolicExpressionTree tempTree;
+    private readonly SymbolicRegressionSolutionImpactValuesCalculator calculator;
 
     public new SymbolicRegressionSolution Content {
@@ -41 +39 @@
       InitializeComponent();
       this.Caption = "Interactive Regression Solution Simplifier";
-
-      constantNode = ((ConstantTreeNode)new Constant().CreateTreeNode());
-      ISymbolicExpressionTreeNode root = new ProgramRootSymbol().CreateTreeNode();
-      ISymbolicExpressionTreeNode start = new StartSymbol().CreateTreeNode();
-      root.AddSubtree(start);
-      tempTree = new SymbolicExpressionTree(root);
+      calculator = new SymbolicRegressionSolutionImpactValuesCalculator();
     }
 
@@ -56 +49 @@
 
     protected override Dictionary<ISymbolicExpressionTreeNode, double> CalculateReplacementValues(ISymbolicExpressionTree tree) {
-      Dictionary<ISymbolicExpressionTreeNode, double> replacementValues = new Dictionary<ISymbolicExpressionTreeNode, double>();
-      foreach (ISymbolicExpressionTreeNode node in tree.Root.GetSubtree(0).GetSubtree(0).IterateNodesPrefix()) {
-        replacementValues[node] = CalculateReplacementValue(node, tree);
-      }
-      return replacementValues;
+      return tree.Root.GetSubtree(0).GetSubtree(0).IterateNodesPrefix().ToDictionary(
+        n => n,
+        n => calculator.CalculateReplacementValue(Content.Model, n, Content.ProblemData, Content.ProblemData.TrainingIndices)
+        );
     }
 
     protected override Dictionary<ISymbolicExpressionTreeNode, double> CalculateImpactValues(ISymbolicExpressionTree tree) {
-      var interpreter = Content.Model.Interpreter;
-      var dataset = Content.ProblemData.Dataset;
-      var rows = Content.ProblemData.TrainingIndices;
-      string targetVariable = Content.ProblemData.TargetVariable;
-      Dictionary<ISymbolicExpressionTreeNode, double> impactValues = new Dictionary<ISymbolicExpressionTreeNode, double>();
-      List<ISymbolicExpressionTreeNode> nodes = tree.Root.GetSubtree(0).GetSubtree(0).IterateNodesPostfix().ToList();
-      var originalOutput = interpreter.GetSymbolicExpressionTreeValues(tree, dataset, rows).LimitToRange(Content.Model.LowerEstimationLimit, Content.Model.UpperEstimationLimit).ToArray();
-      var targetValues = dataset.GetDoubleValues(targetVariable, rows);
-      OnlineCalculatorError errorState;
-      double originalR2 = OnlinePearsonsRSquaredCalculator.Calculate(targetValues, originalOutput, out errorState);
-      if (errorState != OnlineCalculatorError.None) originalR2 = 0.0;
-
-      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).LimitToRange(Content.Model.LowerEstimationLimit, Content.Model.UpperEstimationLimit);
-        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;
+      return tree.Root.GetSubtree(0).GetSubtree(0).IterateNodesPrefix().ToDictionary(
+        n => n,
+        n => calculator.CalculateImpactValue(Content.Model, n, Content.ProblemData, Content.ProblemData.TrainingIndices, Content.TrainingRSquared)
+        );
     }
-
-    private double CalculateReplacementValue(ISymbolicExpressionTreeNode node, ISymbolicExpressionTree sourceTree) {
-      // remove old ADFs
-      while (tempTree.Root.SubtreeCount > 1) tempTree.Root.RemoveSubtree(1);
-      // clone ADFs of source tree
-      for (int i = 1; i < sourceTree.Root.SubtreeCount; i++) {
-        tempTree.Root.AddSubtree((ISymbolicExpressionTreeNode)sourceTree.Root.GetSubtree(i).Clone());
-      }
-      var start = tempTree.Root.GetSubtree(0);
-      while (start.SubtreeCount > 0) start.RemoveSubtree(0);
-      start.AddSubtree((ISymbolicExpressionTreeNode)node.Clone());
-      var interpreter = Content.Model.Interpreter;
-      var rows = Content.ProblemData.TrainingIndices;
-      return interpreter.GetSymbolicExpressionTreeValues(tempTree, Content.ProblemData.Dataset, rows)
-                         .LimitToRange(Content.Model.LowerEstimationLimit, Content.Model.UpperEstimationLimit)
-                         .Median();
-    }
-
-
-    private void SwitchNode(ISymbolicExpressionTreeNode root, ISymbolicExpressionTreeNode oldBranch, ISymbolicExpressionTreeNode newBranch) {
-      for (int i = 0; i < root.SubtreeCount; i++) {
-        if (root.GetSubtree(i) == oldBranch) {
-          root.RemoveSubtree(i);
-          root.InsertSubtree(i, newBranch);
-          return;
-        }
-      }
-    }
-
-    protected override void OnModelChanged() {
-      base.OnModelChanged();
-      if (Content != null)
-        btnOptimizeConstants.Enabled =
-          SymbolicRegressionConstantOptimizationEvaluator.CanOptimizeConstants(Content.Model.SymbolicExpressionTree);
-      else
-        btnOptimizeConstants.Enabled = false;
-    }
-    protected override void OnContentChanged() {
-      base.OnContentChanged();
-      base.OnModelChanged();
-      if (Content != null)
-        btnOptimizeConstants.Enabled =
-          SymbolicRegressionConstantOptimizationEvaluator.CanOptimizeConstants(Content.Model.SymbolicExpressionTree);
-      else
-        btnOptimizeConstants.Enabled = false;
-    }
-
 
     protected override void btnOptimizeConstants_Click(object sender, EventArgs e) {
       var model = Content.Model;
-      SymbolicRegressionConstantOptimizationEvaluator.OptimizeConstants(Content.Model.Interpreter, Content.Model.SymbolicExpressionTree, Content.ProblemData, Content.ProblemData.TrainingIndices,
+      SymbolicRegressionConstantOptimizationEvaluator.OptimizeConstants(model.Interpreter, model.SymbolicExpressionTree, Content.ProblemData, Content.ProblemData.TrainingIndices,
         applyLinearScaling: true, maxIterations: 50, upperEstimationLimit: model.UpperEstimationLimit, lowerEstimationLimit: model.LowerEstimationLimit);
       UpdateModel(Content.Model.SymbolicExpressionTree);