Changeset 7842 for branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression

Timestamp:

05/16/12 16:28:49 (13 years ago)

Author:

gkronber

Message:

merged r7609:7840 from trunk into time series branch

Location:

branches/HeuristicLab.TimeSeries

Files:

• . (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionErrorCharacteristicsCurveView.Designer.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionErrorCharacteristicsCurveView.cs (modified) (5 diffs)

branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionErrorCharacteristicsCurveView.Designer.cs

@@ -49 +49 @@
       this.chart.TabIndex = 0;
       this.chart.Text = "chart";
-      this.chart.MouseDown += new System.Windows.Forms.MouseEventHandler(this.chart_MouseDown);
+      this.chart.MouseDoubleClick += new System.Windows.Forms.MouseEventHandler(this.Chart_MouseDoubleClick);
+      this.chart.MouseMove += new System.Windows.Forms.MouseEventHandler(this.chart_MouseMove);
       // 
       // label1

branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionErrorCharacteristicsCurveView.cs

@@ -27 +27 @@
 using HeuristicLab.MainForm;
 using HeuristicLab.MainForm.WindowsForms;
+
 namespace HeuristicLab.Problems.DataAnalysis.Views {
   [View("Error Characteristics Curve")]
@@ -104 +105 @@
       var originalValues = GetOriginalValues().ToList();
       constantModel = CreateConstantModel();
-      var meanModelEstimatedValues = GetEstimatedValues(constantModel);
-      var meanModelResiduals = GetResiduals(originalValues, meanModelEstimatedValues);
-
-      meanModelResiduals.Sort();
-      chart.ChartAreas[0].AxisX.Maximum = Math.Ceiling(meanModelResiduals.Last());
-      chart.ChartAreas[0].CursorX.Interval = meanModelResiduals.First() / 100;
-
-      Series meanModelSeries = new Series("Mean Model");
-      meanModelSeries.ChartType = SeriesChartType.FastLine;
-      UpdateSeries(meanModelResiduals, meanModelSeries);
-      meanModelSeries.ToolTip = "Area over Curve: " + CalculateAreaOverCurve(meanModelSeries);
-      meanModelSeries.Tag = constantModel;
-      chart.Series.Add(meanModelSeries);
+      var baselineEstimatedValues = GetEstimatedValues(constantModel);
+      var baselineResiduals = GetResiduals(originalValues, baselineEstimatedValues);
+
+      baselineResiduals.Sort();
+      chart.ChartAreas[0].AxisX.Maximum = Math.Ceiling(baselineResiduals.Last());
+      chart.ChartAreas[0].CursorX.Interval = baselineResiduals.First() / 100;
+
+      Series baselineSeries = new Series("Baseline");
+      baselineSeries.ChartType = SeriesChartType.FastLine;
+      UpdateSeries(baselineResiduals, baselineSeries);
+      baselineSeries.ToolTip = "Area over Curve: " + CalculateAreaOverCurve(baselineSeries);
+      baselineSeries.Tag = constantModel;
+      chart.Series.Add(baselineSeries);
 
       AddRegressionSolution(Content);
@@ -200 +201 @@
     }
 
-    protected IEnumerable<double> GetMeanModelEstimatedValues(IEnumerable<double> originalValues) {
+    protected IEnumerable<double> GetbaselineEstimatedValues(IEnumerable<double> originalValues) {
       double averageTrainingTarget = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes).Average();
       return Enumerable.Repeat(averageTrainingTarget, originalValues.Count());
@@ -229 +230 @@
     }
 
-    #region Mean Model
-    private void chart_MouseDown(object sender, MouseEventArgs e) {
-      if (e.Clicks < 2) return;
+    #region Baseline
+    private void Chart_MouseDoubleClick(object sender, MouseEventArgs e) {
       HitTestResult result = chart.HitTest(e.X, e.Y);
       if (result.ChartElementType != ChartElementType.LegendItem) return;
-      if (result.Series.Name != constantModel.Name) return;
 
       MainFormManager.MainForm.ShowContent((IRegressionSolution)result.Series.Tag);
@@ -242 +241 @@
       double averageTrainingTarget = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes).Average();
       var solution = new ConstantRegressionModel(averageTrainingTarget).CreateRegressionSolution(ProblemData);
-      solution.Name = "Mean Model";
+      solution.Name = "Baseline";
       return solution;
     }
     #endregion
+
+    private void chart_MouseMove(object sender, MouseEventArgs e) {
+      HitTestResult result = chart.HitTest(e.X, e.Y);
+      if (result.ChartElementType == ChartElementType.LegendItem)
+        Cursor = Cursors.Hand;
+      else
+        Cursor = Cursors.Default;
+    }
   }
 }