Changeset 8430 for branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Views/3.4/TimeSeriesPrognosis

Timestamp:

08/08/12 14:04:17 (13 years ago)

Author:

mkommend

Message:

#1081: Intermediate commit of trunk updates - interpreter changes must be redone.

Location:

branches/HeuristicLab.TimeSeries

Files:

• . (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Views (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Views/3.4/TimeSeriesPrognosis/TimeSeriesPrognosisSolutionLineChartView.cs (modified) (8 diffs)
• HeuristicLab.Problems.DataAnalysis.Views/3.4/TimeSeriesPrognosis/TimeSeriesPrognosisSolutionPrognosedValuesView.cs (modified) (3 diffs)

branches/HeuristicLab.TimeSeries

@@ -20 +20 @@
 bin
 protoc.exe
+_ReSharper.HeuristicLab.TimeSeries-3.3

@@ -20 +20 @@
 bin
 protoc.exe
+_ReSharper.HeuristicLab.TimeSeries-3.3

branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Views/3.4/TimeSeriesPrognosis/TimeSeriesPrognosisSolutionLineChartView.cs

@@ -19 +19 @@
  */
 #endregion
+
 using System;
 using System.Collections.Generic;
@@ -50 +51 @@
       this.chart.CustomizeAllChartAreas();
       this.chart.ChartAreas[0].CursorX.IsUserSelectionEnabled = true;
+      this.chart.ChartAreas[0].CursorX.Interval = 1;
       this.chart.ChartAreas[0].AxisX.ScaleView.Zoomable = true;
       this.chart.ChartAreas[0].AxisX.IsStartedFromZero = true;
-      this.chart.ChartAreas[0].CursorX.Interval = 1;
 
       this.chart.ChartAreas[0].CursorY.IsUserSelectionEnabled = true;
+      this.chart.ChartAreas[0].CursorY.Interval = 0.1;
       this.chart.ChartAreas[0].AxisY.ScaleView.Zoomable = true;
-      this.chart.ChartAreas[0].CursorY.Interval = 0;
+
+      this.chart.SuppressExceptions = false;
     }
 
@@ -69 +72 @@
         this.chart.Series[TARGETVARIABLE_SERIES_NAME].LegendText = targetVariable;
         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(targetVariable).ToArray());
+        AddDataPoints(chart.Series[TARGETVARIABLE_SERIES_NAME].Points, Enumerable.Range(0, Content.ProblemData.Dataset.Rows), Content.ProblemData.Dataset.GetDoubleValues(targetVariable));
+        //this.chart.Series[TARGETVARIABLE_SERIES_NAME].Points.DataBindXY(Enumerable.Range(0, Content.ProblemData.Dataset.Rows).ToArray(),
+        //  Content.ProblemData.Dataset.GetDoubleValues(targetVariable).ToArray());
 
         this.chart.Series.Add(PROGNOSEDVALUES_TRAINING_SERIES_NAME);
@@ -76 +80 @@
         this.chart.Series[PROGNOSEDVALUES_TRAINING_SERIES_NAME].ChartType = SeriesChartType.FastLine;
         if (prognosedValuesCheckbox.Checked) {
-          this.chart.Series[PROGNOSEDVALUES_TRAINING_SERIES_NAME].Points
-            .DataBindXY(Content.ProblemData.TrainingIndizes.ToArray(),
-                        Content.GetPrognosedValues(Content.ProblemData.TrainingIndizes.Take(1), Content.ProblemData.TrainingIndizes.Count().ToEnumerable()).First().ToArray());
+          //this.chart.Series[PROGNOSEDVALUES_TRAINING_SERIES_NAME].Points
+          //  .DataBindXY(Content.ProblemData.TrainingIndices.ToArray(),
+          //              Content.GetPrognosedValues(Content.ProblemData.TrainingIndices.Take(1), Content.ProblemData.TrainingIndices.Count().ToEnumerable()).First().ToArray());
+          AddDataPoints(chart.Series[PROGNOSEDVALUES_TRAINING_SERIES_NAME].Points, Content.ProblemData.TrainingIndices, Content.GetPrognosedValues(Content.ProblemData.TrainingIndices.Take(1), Content.ProblemData.TrainingIndices.Count().ToEnumerable()).First());
         } else {
-          this.chart.Series[PROGNOSEDVALUES_TRAINING_SERIES_NAME].Points
-            .DataBindXY(Content.ProblemData.TrainingIndizes.ToArray(),
-                        Content.GetPrognosedValues(Content.ProblemData.TrainingIndizes, Enumerable.Repeat(1, Content.ProblemData.TrainingIndizes.Count())).SelectMany(x => x).ToArray());
+          //this.chart.Series[PROGNOSEDVALUES_TRAINING_SERIES_NAME].Points
+          //  .DataBindXY(Content.ProblemData.TrainingIndices.ToArray(),
+          //              Content.GetPrognosedValues(Content.ProblemData.TrainingIndices, Enumerable.Repeat(1, Content.ProblemData.TrainingIndices.Count())).SelectMany(x => x).ToArray());
+          AddDataPoints(chart.Series[PROGNOSEDVALUES_TRAINING_SERIES_NAME].Points, Content.ProblemData.TrainingIndices, Content.GetPrognosedValues(Content.ProblemData.TrainingIndices, Enumerable.Repeat(1, Content.ProblemData.TrainingIndices.Count())).SelectMany(x => x));
         }
         this.chart.Series[PROGNOSEDVALUES_TRAINING_SERIES_NAME].Tag = Content;
@@ -94 +100 @@
         this.chart.Series[PROGNOSEDVALUES_TEST_SERIES_NAME].ChartType = SeriesChartType.FastLine;
         if (prognosedValuesCheckbox.Checked) {
-          this.chart.Series[PROGNOSEDVALUES_TEST_SERIES_NAME].Points
-            .DataBindXY(Content.ProblemData.TestIndizes.ToArray(),
-                        Content.GetPrognosedValues(Content.ProblemData.TestIndizes.Take(1), Content.ProblemData.TestIndizes.Count().ToEnumerable()).First().ToArray());
+          //this.chart.Series[PROGNOSEDVALUES_TEST_SERIES_NAME].Points
+          //  .DataBindXY(Content.ProblemData.TestIndices.ToArray(),
+          //              Content.GetPrognosedValues(Content.ProblemData.TestIndices.Take(1), Content.ProblemData.TestIndices.Count().ToEnumerable()).First().ToArray());
+          AddDataPoints(chart.Series[PROGNOSEDVALUES_TEST_SERIES_NAME].Points, Content.ProblemData.TestIndices, Content.GetPrognosedValues(Content.ProblemData.TestIndices.Take(1), Content.ProblemData.TestIndices.Count().ToEnumerable()).First());
         } else {
-          this.chart.Series[PROGNOSEDVALUES_TEST_SERIES_NAME].Points
-            .DataBindXY(Content.ProblemData.TestIndizes.ToArray(),
-                       Content.GetPrognosedValues(Content.ProblemData.TestIndizes, Enumerable.Repeat(1, Content.ProblemData.TestIndizes.Count())).SelectMany(x => x).ToArray());
+          //this.chart.Series[PROGNOSEDVALUES_TEST_SERIES_NAME].Points
+          //  .DataBindXY(Content.ProblemData.TestIndices.ToArray(),
+          //              Content.GetPrognosedValues(Content.ProblemData.TestIndices, Enumerable.Repeat(1, Content.ProblemData.TestIndices.Count())).SelectMany(x => x).ToArray());
+          AddDataPoints(chart.Series[PROGNOSEDVALUES_TEST_SERIES_NAME].Points, Content.ProblemData.TestIndices, Content.GetPrognosedValues(Content.ProblemData.TestIndices, Enumerable.Repeat(1, Content.ProblemData.TestIndices.Count())).SelectMany(x => x));
         }
         this.chart.Series[PROGNOSEDVALUES_TEST_SERIES_NAME].Tag = Content;
-
         UpdateCursorInterval();
         this.UpdateStripLines();
+      }
+      chart.Refresh();
+    }
+
+    private void AddDataPoints(DataPointCollection points, IEnumerable<int> xValues, IEnumerable<double> yValues) {
+      var xValuesEnumerator = xValues.GetEnumerator();
+      var yValuesEnumerator = yValues.GetEnumerator();
+
+      while (xValuesEnumerator.MoveNext() & yValuesEnumerator.MoveNext()) {
+        var xValue = xValuesEnumerator.Current;
+        var yValue = yValuesEnumerator.Current;
+
+        if (yValue < (double)decimal.MaxValue && yValue > (double)decimal.MinValue) {
+          DataPoint dataPoint = new DataPoint(xValue, yValue);
+          points.Add(dataPoint);
+        }
       }
     }
@@ -166 +189 @@
 
       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;
       }
@@ -215 +238 @@
         }
       } else if (Content != null) {
-        IEnumerable<int> indizes = null;
+        IEnumerable<int> Indices = null;
         IEnumerable<double> predictedValues = null;
 
         switch (series.Name) {
           case PROGNOSEDVALUES_TRAINING_SERIES_NAME:
-            indizes = Content.ProblemData.TrainingIndizes.ToArray();
-            predictedValues = Content.GetPrognosedValues(Content.ProblemData.TrainingIndizes.Take(1), Content.ProblemData.TrainingPartition.Size.ToEnumerable()).First();
+            Indices = Content.ProblemData.TrainingIndices.ToArray();
+            predictedValues = Content.GetPrognosedValues(Content.ProblemData.TrainingIndices.Take(1), Content.ProblemData.TrainingPartition.Size.ToEnumerable()).First();
             break;
           case PROGNOSEDVALUES_TEST_SERIES_NAME:
             testPrognosisStart = Content.ProblemData.TestPartition.Start;
-            indizes = Content.ProblemData.TestIndizes.ToArray();
-            predictedValues = Content.GetPrognosedValues(Content.ProblemData.TestIndizes.Take(1), Content.ProblemData.TestPartition.Size.ToEnumerable()).First();
+            Indices = Content.ProblemData.TestIndices.ToArray();
+            predictedValues = Content.GetPrognosedValues(Content.ProblemData.TestIndices.Take(1), Content.ProblemData.TestPartition.Size.ToEnumerable()).First();
             break;
         }
-        series.Points.DataBindXY(indizes, predictedValues);
+        series.Points.DataBindXY(Indices, predictedValues);
         chart.DataManipulator.InsertEmptyPoints(1, IntervalType.Number, series.Name);
         chart.Legends[series.Legend].ForeColor = Color.Black;
@@ -238 +261 @@
 
     private void chart_MouseMove(object sender, MouseEventArgs e) {
-      HitTestResult result = chart.HitTest(e.X, e.Y);
-      if (result.ChartElementType == ChartElementType.LegendItem && result.Series.Name != TARGETVARIABLE_SERIES_NAME)
-        Cursor = Cursors.Hand;
-      else
-        Cursor = Cursors.Default;
+      //HitTestResult result = chart.HitTest(e.X, e.Y);
+      //if (result.ChartElementType == ChartElementType.LegendItem && result.Series.Name != TARGETVARIABLE_SERIES_NAME)
+      //  Cursor = Cursors.Hand;
+      //else
+      //  Cursor = Cursors.Default;
     }
 
     private void chart_MouseDown(object sender, MouseEventArgs e) {
-      HitTestResult result = chart.HitTest(e.X, e.Y);
-      if (result.ChartElementType == ChartElementType.LegendItem && result.Series.Name != TARGETVARIABLE_SERIES_NAME) {
-        ToggleSeriesData(result.Series);
-      } else if (result.ChartElementType == ChartElementType.Axis || result.ChartElementType == ChartElementType.AxisLabels ||
-        result.ChartElementType == ChartElementType.TickMarks) {
-        chart.ChartAreas[0].CursorX.SetCursorPixelPosition(new Point(e.X, e.Y), true);
-        int pos = (int)Math.Round(chart.ChartAreas[0].CursorX.Position);
-        if (pos >= Content.ProblemData.TestPartition.Start && pos < Content.ProblemData.TestPartition.End) {
-          testPrognosisStart = pos;
-          RedrawChart();
-        }
-      }
+      //HitTestResult result = chart.HitTest(e.X, e.Y);
+      //if (result.ChartElementType == ChartElementType.LegendItem && result.Series.Name != TARGETVARIABLE_SERIES_NAME) {
+      //  ToggleSeriesData(result.Series);
+      //} else if (result.ChartElementType == ChartElementType.Axis || result.ChartElementType == ChartElementType.AxisLabels ||
+      //  result.ChartElementType == ChartElementType.TickMarks) {
+      //  chart.ChartAreas[0].CursorX.SetCursorPixelPosition(new Point(e.X, e.Y), true);
+      //  int pos = (int)Math.Round(chart.ChartAreas[0].CursorX.Position);
+      //  if (pos >= Content.ProblemData.TestPartition.Start && pos < Content.ProblemData.TestPartition.End) {
+      //    testPrognosisStart = pos;
+      //    RedrawChart();
+      //  }
+      //}
     }
 

branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Views/3.4/TimeSeriesPrognosis/TimeSeriesPrognosisSolutionPrognosedValuesView.cs

@@ -95 +95 @@
 
       string[,] values = new string[Content.ProblemData.Dataset.Rows, 4];
-      var prognosedTraining = Content.GetPrognosedValues(Content.ProblemData.TrainingIndizes.Take(1), Content.ProblemData.TrainingPartition.Size.ToEnumerable()).First();
-      var prognosedTest = Content.GetPrognosedValues(Content.ProblemData.TestIndizes.Take(1), Content.ProblemData.TestPartition.Size.ToEnumerable()).First();
+      var prognosedTraining = Content.GetPrognosedValues(Content.ProblemData.TrainingIndices.Take(1), Content.ProblemData.TrainingPartition.Size.ToEnumerable()).First();
+      var prognosedTest = Content.GetPrognosedValues(Content.ProblemData.TestIndices.Take(1), Content.ProblemData.TestPartition.Size.ToEnumerable()).First();
       double[] target = Content.ProblemData.Dataset.GetDoubleValues(targetVariable).ToArray();
 
@@ -105 +105 @@
       }
 
-      var rowsEnumerator = Content.ProblemData.TrainingIndizes.GetEnumerator();
+      var rowsEnumerator = Content.ProblemData.TrainingIndices.GetEnumerator();
       var prognosisEnumerator = prognosedTraining.GetEnumerator();
       while (rowsEnumerator.MoveNext() & prognosisEnumerator.MoveNext()) {
@@ -113 +113 @@
       }
 
-      rowsEnumerator = Content.ProblemData.TestIndizes.GetEnumerator();
+      rowsEnumerator = Content.ProblemData.TestIndices.GetEnumerator();
       prognosisEnumerator = prognosedTest.GetEnumerator();
       while (rowsEnumerator.MoveNext() & prognosisEnumerator.MoveNext()) {

@@ -20 +20 @@
 bin
 protoc.exe
+_ReSharper.HeuristicLab.TimeSeries-3.3