Changeset 8139 for trunk/sources/HeuristicLab.Problems.DataAnalysis.Views

Timestamp:

06/27/12 17:34:17 (12 years ago)

Author:

mkommend

Message:

#1722: Renamed indizes to indices in the whole trunk solution.

Location:

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

Files:

• Classification/ClassificationEnsembleSolutionEstimatedClassValuesView.cs (modified) (2 diffs)
• Classification/ClassificationSolutionConfusionMatrixView.cs (modified) (1 diff)
• Classification/ClassificationSolutionEstimatedClassValuesView.cs (modified) (2 diffs)
• Classification/DiscriminantFunctionClassificationRocCurvesView.cs (modified) (1 diff)
• Classification/DiscriminantFunctionClassificationSolutionThresholdView.cs (modified) (2 diffs)
• Regression/RegressionSolutionErrorCharacteristicsCurveView.cs (modified) (2 diffs)
• Regression/RegressionSolutionEstimatedValuesView.cs (modified) (1 diff)
• Regression/RegressionSolutionLineChartView.cs (modified) (4 diffs)
• Regression/RegressionSolutionScatterPlotView.cs (modified) (2 diffs)

trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/ClassificationEnsembleSolutionEstimatedClassValuesView.cs

@@ -73 +73 @@
       }
 
-      int[] indizes;
+      int[] indices;
       double[] estimatedClassValues;
 
       switch (SamplesComboBox.SelectedItem.ToString()) {
         case SamplesComboBoxAllSamples: {
-            indizes = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).ToArray();
+            indices = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).ToArray();
             estimatedClassValues = Content.EstimatedClassValues.ToArray();
             break;
           }
         case SamplesComboBoxTrainingSamples: {
-            indizes = Content.ProblemData.TrainingIndizes.ToArray();
+            indices = Content.ProblemData.TrainingIndices.ToArray();
             estimatedClassValues = Content.EstimatedTrainingClassValues.ToArray();
             break;
           }
         case SamplesComboBoxTestSamples: {
-            indizes = Content.ProblemData.TestIndizes.ToArray();
+            indices = Content.ProblemData.TestIndices.ToArray();
             estimatedClassValues = Content.EstimatedTestClassValues.ToArray();
             break;
@@ -98 +98 @@
       int classValuesCount = Content.ProblemData.ClassValues.Count;
       int solutionsCount = Content.ClassificationSolutions.Count();
-      string[,] values = new string[indizes.Length, 5 + classValuesCount + solutionsCount];
+      string[,] values = new string[indices.Length, 5 + classValuesCount + solutionsCount];
       double[] target = Content.ProblemData.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToArray();
-      List<List<double?>> estimatedValuesVector = GetEstimatedValues(SamplesComboBox.SelectedItem.ToString(), indizes,
+      List<List<double?>> estimatedValuesVector = GetEstimatedValues(SamplesComboBox.SelectedItem.ToString(), indices,
                                                             Content.ClassificationSolutions);
 
-      for (int i = 0; i < indizes.Length; i++) {
-        int row = indizes[i];
+      for (int i = 0; i < indices.Length; i++) {
+        int row = indices[i];
         values[i, 0] = row.ToString();
         values[i, 1] = target[i].ToString();

trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/ClassificationSolutionConfusionMatrixView.cs

@@ -107 +107 @@
         double[] predictedValues;
         if (cmbSamples.SelectedItem.ToString() == TrainingSamples) {
-          rows = Content.ProblemData.TrainingIndizes;
+          rows = Content.ProblemData.TrainingIndices;
           predictedValues = Content.EstimatedTrainingClassValues.ToArray();
         } else if (cmbSamples.SelectedItem.ToString() == TestSamples) {
-          rows = Content.ProblemData.TestIndizes;
+          rows = Content.ProblemData.TestIndices;
           predictedValues = Content.EstimatedTestClassValues.ToArray();
         } else throw new InvalidOperationException();

trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/ClassificationSolutionEstimatedClassValuesView.cs

@@ -96 +96 @@
           var estimatedTraining = Content.EstimatedTrainingClassValues.GetEnumerator();
           estimatedTraining.MoveNext();
-          foreach (var trainingRow in Content.ProblemData.TrainingIndizes) {
+          foreach (var trainingRow in Content.ProblemData.TrainingIndices) {
             values[trainingRow, 3] = estimatedTraining.Current.ToString();
             estimatedTraining.MoveNext();
@@ -102 +102 @@
           var estimatedTest = Content.EstimatedTestClassValues.GetEnumerator();
           estimatedTest.MoveNext();
-          foreach (var testRow in Content.ProblemData.TestIndizes) {
+          foreach (var testRow in Content.ProblemData.TestIndices) {
             values[testRow, 4] = estimatedTest.Current.ToString();
             estimatedTest.MoveNext();

trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/DiscriminantFunctionClassificationRocCurvesView.cs

@@ -101 +101 @@
 
         if (cmbSamples.SelectedItem.ToString() == TrainingSamples) {
-          rows = Content.ProblemData.TrainingIndizes;
+          rows = Content.ProblemData.TrainingIndices;
         } else if (cmbSamples.SelectedItem.ToString() == TestSamples) {
-          rows = Content.ProblemData.TestIndizes;
+          rows = Content.ProblemData.TestIndices;
         } else throw new InvalidOperationException();
 

trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/DiscriminantFunctionClassificationSolutionThresholdView.cs

@@ -137 +137 @@
       var targetValues = Content.ProblemData.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToList();
 
-      foreach (int row in Content.ProblemData.TrainingIndizes) {
+      foreach (int row in Content.ProblemData.TrainingIndices) {
         double estimatedValue = estimatedValues[row];
         double targetValue = targetValues[row];
@@ -150 +150 @@
       }
 
-      foreach (int row in Content.ProblemData.TestIndizes) {
+      foreach (int row in Content.ProblemData.TestIndices) {
         double estimatedValue = estimatedValues[row];
         double targetValue = targetValues[row];

trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionErrorCharacteristicsCurveView.cs

@@ -169 +169 @@
       switch (cmbSamples.SelectedItem.ToString()) {
         case TrainingSamples:
-          originalValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes);
+          originalValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices);
           break;
         case TestSamples:
-          originalValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndizes);
+          originalValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndices);
           break;
         case AllSamples:
@@ -234 +234 @@
 
     private IRegressionSolution CreateConstantModel() {
-      double averageTrainingTarget = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes).Average();
+      double averageTrainingTarget = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices).Average();
       var solution = new ConstantRegressionModel(averageTrainingTarget).CreateRegressionSolution(ProblemData);
       solution.Name = "Baseline";

trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionEstimatedValuesView.cs

@@ -93 +93 @@
           var estimated_test = Content.EstimatedTestValues.GetEnumerator();
 
-          foreach (var row in Content.ProblemData.TrainingIndizes) {
+          foreach (var row in Content.ProblemData.TrainingIndices) {
             estimated_training.MoveNext();
             values[row, 3] = estimated_training.Current.ToString();
           }
 
-          foreach (var row in Content.ProblemData.TestIndizes) {
+          foreach (var row in Content.ProblemData.TestIndices) {
             estimated_test.MoveNext();
             values[row, 4] = estimated_test.Current.ToString();

trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionLineChartView.cs

@@ -72 +72 @@
         this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].ChartType = SeriesChartType.FastLine;
         this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].EmptyPointStyle.Color = this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Color;
-        this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TrainingIndizes.ToArray(), Content.EstimatedTrainingValues.ToArray());
+        this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TrainingIndices.ToArray(), Content.EstimatedTrainingValues.ToArray());
         this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME]);
         this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Tag = Content;
@@ -79 +79 @@
         this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].LegendText = ESTIMATEDVALUES_TEST_SERIES_NAME;
         this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].ChartType = SeriesChartType.FastLine;
-        this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TestIndizes.ToArray(), Content.EstimatedTestValues.ToArray());
+        this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TestIndices.ToArray(), Content.EstimatedTestValues.ToArray());
         this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME]);
         this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Tag = Content;
         // series of remaining points
-        int[] allIndizes = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndizes).Except(Content.ProblemData.TestIndizes).ToArray();
+        int[] allIndices = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndices).Except(Content.ProblemData.TestIndices).ToArray();
         var estimatedValues = Content.EstimatedValues.ToArray();
-        List<double> allEstimatedValues = allIndizes.Select(index => estimatedValues[index]).ToList();
+        List<double> allEstimatedValues = allIndices.Select(index => estimatedValues[index]).ToList();
         this.chart.Series.Add(ESTIMATEDVALUES_ALL_SERIES_NAME);
         this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].LegendText = ESTIMATEDVALUES_ALL_SERIES_NAME;
         this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].ChartType = SeriesChartType.FastLine;
-        this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].Points.DataBindXY(allIndizes, allEstimatedValues);
+        this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].Points.DataBindXY(allIndices, allEstimatedValues);
         this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME]);
         this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].Tag = Content;
@@ -170 +170 @@
 
       int[] attr = new int[Content.ProblemData.Dataset.Rows + 1]; // add a virtual last row that is again empty to simplify loop further down
-      foreach (var row in Content.ProblemData.TrainingIndizes) {
+      foreach (var row in Content.ProblemData.TrainingIndices) {
         attr[row] += 1;
       }
-      foreach (var row in Content.ProblemData.TestIndizes) {
+      foreach (var row in Content.ProblemData.TestIndices) {
         attr[row] += 2;
       }
@@ -223 +223 @@
         string targetVariableName = Content.ProblemData.TargetVariable;
 
-        IEnumerable<int> indizes = null;
+        IEnumerable<int> indices = null;
         IEnumerable<double> predictedValues = null;
         switch (series.Name) {
           case ESTIMATEDVALUES_ALL_SERIES_NAME:
-            indizes = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndizes).Except(Content.ProblemData.TestIndizes).ToArray();
+            indices = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndices).Except(Content.ProblemData.TestIndices).ToArray();
             var estimatedValues = Content.EstimatedValues.ToArray();
-            predictedValues = indizes.Select(index => estimatedValues[index]).ToList();
+            predictedValues = indices.Select(index => estimatedValues[index]).ToList();
             break;
           case ESTIMATEDVALUES_TRAINING_SERIES_NAME:
-            indizes = Content.ProblemData.TrainingIndizes.ToArray();
+            indices = Content.ProblemData.TrainingIndices.ToArray();
             predictedValues = Content.EstimatedTrainingValues.ToArray();
             break;
           case ESTIMATEDVALUES_TEST_SERIES_NAME:
-            indizes = Content.ProblemData.TestIndizes.ToArray();
+            indices = Content.ProblemData.TestIndices.ToArray();
             predictedValues = Content.EstimatedTestValues.ToArray();
             break;
         }
-        series.Points.DataBindXY(indizes, predictedValues);
+        series.Points.DataBindXY(indices, predictedValues);
         this.InsertEmptyPoints(series);
         chart.Legends[series.Legend].ForeColor = Color.Black;

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

@@ -148 +148 @@
         if (this.chart.Series[TRAINING_SERIES].Points.Count > 0)
           this.chart.Series[TRAINING_SERIES].Points.DataBindXY(Content.EstimatedTrainingValues.ToArray(), "",
-            dataset.GetDoubleValues(targetVariableName, Content.ProblemData.TrainingIndizes).ToArray(), "");
+            dataset.GetDoubleValues(targetVariableName, Content.ProblemData.TrainingIndices).ToArray(), "");
         if (this.chart.Series[TEST_SERIES].Points.Count > 0)
           this.chart.Series[TEST_SERIES].Points.DataBindXY(Content.EstimatedTestValues.ToArray(), "",
-           dataset.GetDoubleValues(targetVariableName, Content.ProblemData.TestIndizes).ToArray(), "");
+           dataset.GetDoubleValues(targetVariableName, Content.ProblemData.TestIndices).ToArray(), "");
 
         double max = Content.EstimatedTrainingValues.Concat(Content.EstimatedTestValues.Concat(Content.EstimatedValues.Concat(dataset.GetDoubleValues(targetVariableName)))).Max();
@@ -196 +196 @@
           case TRAINING_SERIES:
             predictedValues = Content.EstimatedTrainingValues.ToArray();
-            targetValues = Content.ProblemData.Dataset.GetDoubleValues(targetVariableName, Content.ProblemData.TrainingIndizes).ToArray();
+            targetValues = Content.ProblemData.Dataset.GetDoubleValues(targetVariableName, Content.ProblemData.TrainingIndices).ToArray();
             break;
           case TEST_SERIES:
             predictedValues = Content.EstimatedTestValues.ToArray();
-            targetValues = Content.ProblemData.Dataset.GetDoubleValues(targetVariableName, Content.ProblemData.TestIndizes).ToArray();
+            targetValues = Content.ProblemData.Dataset.GetDoubleValues(targetVariableName, Content.ProblemData.TestIndices).ToArray();
             break;
         }