Changeset 15785

Timestamp:

02/19/18 16:32:54 (6 years ago)

Author:

fholzing

Message:

#2383: Added additional filtering logic for double.NaN and double.Inf

Location:

trunk/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression

Files:

• RegressionSolutionLineChartViewBase.cs (modified) (2 diffs)
• RegressionSolutionResidualHistogram.cs (modified) (1 diff)
• RegressionSolutionResidualsLineChartView.cs (modified) (1 diff)
• RegressionSolutionScatterPlotView.cs (modified) (1 diff)

trunk/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionLineChartViewBase.cs

@@ -72 +72 @@
         this.chart.Series[TARGETVARIABLE_SERIES_NAME].LegendText = TARGETVARIABLE_SERIES_NAME;
         this.chart.Series[TARGETVARIABLE_SERIES_NAME].ChartType = SeriesChartType.FastLine;
-        this.chart.Series[TARGETVARIABLE_SERIES_NAME].Points.DataBindXY(Enumerable.Range(0, Content.ProblemData.Dataset.Rows).ToArray(),
-          Content.ProblemData.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToArray());
+
+        var rows = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).ToArray();
+        var targetVariables = Content.ProblemData.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToArray();
+        List<int> xVals = new List<int>();
+        List<double> yVals = new List<double>();
+
+        for (int i = 0; i < rows.Length; i++) {
+          if (!double.IsInfinity(targetVariables[i])) {
+            xVals.Add(rows[i]);
+            yVals.Add(targetVariables[i]);
+          }
+        }
+
+        this.chart.Series[TARGETVARIABLE_SERIES_NAME].Points.DataBindXY(xVals.ToArray(), yVals.ToArray());
         // training series
         this.chart.Series.Add(ESTIMATEDVALUES_TRAINING_SERIES_NAME);
@@ -161 +173 @@
       var targetValues = this.chart.Series[TARGETVARIABLE_SERIES_NAME].Points.Select(x => x.YValues[0]).DefaultIfEmpty(1.0);
       double estimatedValuesRange = estimatedValues.Max() - estimatedValues.Min();
-      double targetValuesRange = targetValues.Max() - targetValues.Min();
+      double targetValuesRange = targetValues.Where(v => !double.IsInfinity(v)).Max() - targetValues.Where(v => !double.IsNaN(v) && !double.IsNegativeInfinity(v)).Min();
       double interestingValuesRange = Math.Min(Math.Max(targetValuesRange, 1.0), Math.Max(estimatedValuesRange, 1.0));
       double digits = (int)Math.Log10(interestingValuesRange) - 3;

trunk/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionResidualHistogram.cs

@@ -81 +81 @@
       if (Content != null) {
         List<double> residuals = CalculateResiduals(Content);
+        residuals.Remove(double.NaN);
+        residuals.Remove(double.PositiveInfinity);
+        residuals.Remove(double.NegativeInfinity);
 
         double max = 0.0;

trunk/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionResidualsLineChartView.cs

@@ -38 +38 @@
       var target = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, idx).ToArray();
       for (int i = 0; i < idx.Length; i++) {
-        x[i] = target[i] - x[i];
+        if (!double.IsInfinity(target[i])) {
+          x[i] = target[i] - x[i];
+        }
       }
     }

trunk/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionScatterPlotView.cs

@@ -166 +166 @@
           this.chart.Series[TEST_SERIES].Points.DataBindXY(dataset.GetDoubleValues(targetVariableName, Content.ProblemData.TestIndices).ToArray(), "",
             Content.EstimatedTestValues.ToArray(), "");
-        double max = Content.EstimatedTrainingValues.Concat(Content.EstimatedTestValues.Concat(Content.EstimatedValues.Concat(dataset.GetDoubleValues(targetVariableName)))).Max();
-        double min = Content.EstimatedTrainingValues.Concat(Content.EstimatedTestValues.Concat(Content.EstimatedValues.Concat(dataset.GetDoubleValues(targetVariableName)))).Min();
+        double max = Content.EstimatedTrainingValues.Concat(Content.EstimatedTestValues.Concat(Content.EstimatedValues.Concat(dataset.GetDoubleValues(targetVariableName)))).Where(v => !double.IsInfinity(v)).Max();
+        double min = Content.EstimatedTrainingValues.Concat(Content.EstimatedTestValues.Concat(Content.EstimatedValues.Concat(dataset.GetDoubleValues(targetVariableName)))).Where(v => !double.IsNaN(v) && !double.IsNegativeInfinity(v)).Min();
 
         double axisMin, axisMax, axisInterval;