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Changeset 9363 for branches/OaaS/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification

Timestamp:

04/16/13 13:13:41 (12 years ago)

Author:

spimming

Message:

Merged revisions from trunk

Location:

Files:

: 9 edited
: 6 copied

Legend:

: Unmodified
: Added
: Removed

branches/OaaS

Property svn:ignore

old	new
21	21	protoc.exe
22	22	_ReSharper.HeuristicLab 3.3 Tests
	23	Google.ProtocolBuffers-2.4.1.473.dll
23	24	packages

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/branches/SlaveShutdown (added)	merged: 8944-8945,8949,8951,8953-8954
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branches/OaaS/HeuristicLab.Problems.DataAnalysis.Views

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branches/OaaS/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/ClassificationEnsembleSolutionEstimatedClassValuesView.cs

-                      r8139
+                      r9363
+      }
       int classValuesCount = Content.ProblemData.ClassValues.Count;
+      int classValuesCount = Content.ProblemData.Classes;
       int solutionsCount = Content.ClassificationSolutions.Count();
       string[,] values = new string[indices.Length, 5 + classValuesCount + solutionsCount];
 …
         int row = indices[i];
         values[i, 0] = row.ToString();
         values[i, 1] = target[i].ToString();
+        values[i, 1] = target[row].ToString();
         //display only indices and target values if no models are present
         if (solutionsCount > 0) {
           values[i, 2] = estimatedClassValues[i].ToString();
           values[i, 3] = (target[i].IsAlmost(estimatedClassValues[i])).ToString();
+          values[i, 3] = (target[row].IsAlmost(estimatedClassValues[i])).ToString();
           var groups =
             estimatedValuesVector[i].GroupBy(x => x).Select(g => new { Key = g.Key, Count = g.Count() }).ToList();
           var estimationCount = groups.Where(g => g.Key != null).Select(g => g.Count).Sum();
+          values[i, 4] =
+            (((double)groups.Where(g => g.Key == estimatedClassValues[i]).Single().Count) / estimationCount).ToString();
+          for (int classIndex = 0; classIndex < Content.ProblemData.ClassValues.Count; classIndex++) {
+            var group = groups.Where(g => g.Key == Content.ProblemData.ClassValues[classIndex]).SingleOrDefault();
+          // take care of divide by zero
+          if (estimationCount != 0) {
+            values[i, 4] = (((double)groups.Where(g => g.Key == estimatedClassValues[i]).Single().Count) / estimationCount).ToString();
+          } else {
+            values[i, 4] = double.NaN.ToString();
+          }
+          for (int classIndex = 0; classIndex < Content.ProblemData.Classes; classIndex++) {
+            var group = groups.Where(g => g.Key == Content.ProblemData.ClassValues.ElementAt(classIndex)).SingleOrDefault();
             if (group == null) values[i, 5 + classIndex] = 0.ToString();
             else values[i, 5 + classIndex] = group.Count.ToString();

branches/OaaS/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/ClassificationEnsembleSolutionModelView.cs

-                      r7259
+                      r9363
 #endregion
+using System;
 using System.Linq;
 using System.Windows.Forms;
 using HeuristicLab.Common;
+using HeuristicLab.Core;
 using HeuristicLab.Core.Views;
 using HeuristicLab.MainForm;
 …
             solutions = solutions.Select(s => cloner.Clone(s));
+          }
+          foreach (var solution in solutions)
+            Content.Add(solution);
+          var solutionCollection = Content as ItemCollection<IClassificationSolution>;
+          if (solutionCollection != null) {
+            solutionCollection.AddRange(solutions);
+          } else {
+            foreach (var solution in solutions)
+              Content.Add(solution);
+          }
+        }
+      }
+      protected override void itemsListView_KeyDown(object sender, KeyEventArgs e) {
+        var solutionCollection = Content as ItemCollection<IClassificationSolution>;
+        if (e.KeyCode == Keys.Delete && solutionCollection != null) {
+          if ((itemsListView.SelectedItems.Count > 0) && !Content.IsReadOnly && !ReadOnly) {
+            solutionCollection.RemoveRange(itemsListView.SelectedItems.Cast<ListViewItem>().Select(x => (IClassificationSolution)x.Tag));
+          }
+        } else {
+          base.itemsListView_KeyDown(sender, e);
+        }
+      }
+      protected override void removeButton_Click(object sender, EventArgs e) {
+        var solutionCollection = Content as ItemCollection<IClassificationSolution>;
+        if (itemsListView.SelectedItems.Count > 0 && solutionCollection != null) {
+          solutionCollection.RemoveRange(itemsListView.SelectedItems.Cast<ListViewItem>().Select(x => (IClassificationSolution)x.Tag));
+          itemsListView.SelectedItems.Clear();
+        } else {
+          base.removeButton_Click(sender, e);
+        }
+      }

branches/OaaS/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/ClassificationSolutionConfusionMatrixView.Designer.cs

-                      r7967
+                      r9363
+namespace HeuristicLab.Problems.DataAnalysis.Views {
+#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ *
+ * This file is part of HeuristicLab.
+ *
+ * HeuristicLab is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * HeuristicLab is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
+ */
+#endregion
+namespace HeuristicLab.Problems.DataAnalysis.Views {
   partial class ClassificationSolutionConfusionMatrixView {
     /// <summary>

branches/OaaS/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/DiscriminantFunctionClassificationRocCurvesView.Designer.cs

-                      r7967
+                      r9363
+namespace HeuristicLab.Problems.DataAnalysis.Views {
+#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ *
+ * This file is part of HeuristicLab.
+ *
+ * HeuristicLab is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * HeuristicLab is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
+ */
+#endregion
+namespace HeuristicLab.Problems.DataAnalysis.Views {
   partial class DiscriminantFunctionClassificationRocCurvesView {
     /// <summary>

branches/OaaS/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/DiscriminantFunctionClassificationRocCurvesView.cs

r8139	r9363
114	114	maxThreshold += thresholdIncrement;
115	115
116		List<double> classValues = Content.ProblemData.ClassValues.~~OrderBy(x => x).~~ToList();
	116	List<double> classValues = Content.ProblemData.ClassValues.ToList();
117	117
118	118	foreach (double classValue in classValues) {

branches/OaaS/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/DiscriminantFunctionClassificationSolutionThresholdView.Designer.cs

-                      r7967
+                      r9363
+namespace HeuristicLab.Problems.DataAnalysis.Views {
+#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ *
+ * This file is part of HeuristicLab.
+ *
+ * HeuristicLab is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * HeuristicLab is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
+ */
+#endregion
+namespace HeuristicLab.Problems.DataAnalysis.Views {
   partial class DiscriminantFunctionClassificationSolutionThresholdView {
     /// <summary>
 …
+    }
     #endregion

branches/OaaS/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/DiscriminantFunctionClassificationSolutionThresholdView.cs

-                      r8139
+                      r9363
       this.chart.ChartAreas[0].AxisY.Title = "Estimated Values";
+      this.chart.ChartAreas[0].AxisY.IsStartedFromZero = false;
       this.chart.ChartAreas[0].CursorY.IsUserSelectionEnabled = true;
       this.chart.ChartAreas[0].AxisX.ScaleView.Zoomable = true;
 …
       chart.Annotations.Clear();
       int classIndex = 1;
+      IClassificationProblemData problemData = Content.ProblemData;
+      var classValues = Content.Model.ClassValues.ToArray();
+      Axis y = chart.ChartAreas[0].AxisY;
+      Axis x = chart.ChartAreas[0].AxisX;
+      string name;
       foreach (double threshold in Content.Model.Thresholds) {
         if (!double.IsInfinity(threshold)) {
 …
           annotation.LineWidth = 2;
           annotation.LineColor = Color.Red;
           annotation.IsInfinitive = true;
           annotation.ClipToChartArea = chart.ChartAreas[0].Name;
           annotation.Tag = classIndex;  //save classIndex as Tag to avoid moving the threshold accross class bounderies
           annotation.AxisX = chart.ChartAreas[0].AxisX;
           annotation.AxisY = chart.ChartAreas[0].AxisY;
+          annotation.AxisY = y;
           annotation.Y = threshold;
+          name = problemData.GetClassName(classValues[classIndex - 1]);
+          TextAnnotation beneathLeft = CreateTextAnnotation(name, classIndex, x, y, x.Minimum, threshold, ContentAlignment.TopLeft);
+          TextAnnotation beneathRight = CreateTextAnnotation(name, classIndex, x, y, x.Maximum, threshold, ContentAlignment.TopRight);
+          name = problemData.GetClassName(classValues[classIndex]);
+          TextAnnotation aboveLeft = CreateTextAnnotation(name, classIndex, x, y, x.Minimum, threshold, ContentAlignment.BottomLeft);
+          TextAnnotation aboveRight = CreateTextAnnotation(name, classIndex, x, y, x.Maximum, threshold, ContentAlignment.BottomRight);
           chart.Annotations.Add(annotation);
+          chart.Annotations.Add(beneathLeft);
+          chart.Annotations.Add(aboveLeft);
+          chart.Annotations.Add(beneathRight);
+          chart.Annotations.Add(aboveRight);
+          beneathLeft.ResizeToContent();
+          beneathRight.ResizeToContent();
+          aboveLeft.ResizeToContent();
+          aboveRight.ResizeToContent();
+          beneathRight.Width = -beneathRight.Width;
+          aboveLeft.Height = -aboveLeft.Height;
+          aboveRight.Height = -aboveRight.Height;
+          aboveRight.Width = -aboveRight.Width;
           classIndex++;
+        }
+      }
+    }
+    private TextAnnotation CreateTextAnnotation(string name, int classIndex, Axis axisX, Axis axisY, double x, double y, ContentAlignment alignment) {
+      TextAnnotation annotation = new TextAnnotation();
+      annotation.Text = name;
+      annotation.AllowMoving = true;
+      annotation.AllowResizing = false;
+      annotation.AllowSelecting = false;
+      annotation.IsSizeAlwaysRelative = true;
+      annotation.ClipToChartArea = chart.ChartAreas[0].Name;
+      annotation.Tag = classIndex;
+      annotation.AxisX = axisX;
+      annotation.AxisY = axisY;
+      annotation.Alignment = alignment;
+      annotation.X = x;
+      annotation.Y = y;
+      return annotation;
+    }
 …
       double[] thresholds = Content.Model.Thresholds.ToArray();
       thresholds[classIndex] = e.NewLocationY;
+      Array.Sort(thresholds);
       Content.Model.SetThresholdsAndClassValues(thresholds, Content.Model.ClassValues);
+    }

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