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source: trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/DiscriminantFunctionClassificationSolutionThresholdView.cs @ 6642

Last change on this file since 6642 was 6642, checked in by mkommend, 13 years ago

#1612: Implemented RegressionSolutionErrorCharacteristicsView and adapted loading of DataAnalysisSolutionEvaluationViews.

File size: 11.0 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using System.Collections.Generic;
24using System.Drawing;
25using System.Linq;
26using System.Windows.Forms;
27using System.Windows.Forms.DataVisualization.Charting;
28using HeuristicLab.Common;
29using HeuristicLab.MainForm;
30using HeuristicLab.MainForm.WindowsForms;
31
32namespace HeuristicLab.Problems.DataAnalysis.Views {
33  [View("Classification Threshold")]
34  [Content(typeof(IDiscriminantFunctionClassificationSolution), true)]
35  public sealed partial class DiscriminantFunctionClassificationSolutionThresholdView : DataAnalysisSolutionEvaluationView {
36    private const double TrainingAxisValue = 0.0;
37    private const double TestAxisValue = 10.0;
38    private const double TrainingTestBorder = (TestAxisValue - TrainingAxisValue) / 2;
39    private const string TrainingLabelText = "Training Samples";
40    private const string TestLabelText = "Test Samples";
41
42    public new IDiscriminantFunctionClassificationSolution Content {
43      get { return (IDiscriminantFunctionClassificationSolution)base.Content; }
44      set { base.Content = value; }
45    }
46
47    private Dictionary<double, Series> classValueSeriesMapping;
48    private Random random;
49    private bool updateInProgress;
50
51    public DiscriminantFunctionClassificationSolutionThresholdView()
52      : base() {
53      InitializeComponent();
54
55      classValueSeriesMapping = new Dictionary<double, Series>();
56      random = new Random();
57      updateInProgress = false;
58
59      this.chart.CustomizeAllChartAreas();
60      this.chart.ChartAreas[0].CursorX.IsUserSelectionEnabled = true;
61      this.chart.ChartAreas[0].AxisX.ScaleView.Zoomable = true;
62      this.chart.ChartAreas[0].AxisX.Minimum = TrainingAxisValue - TrainingTestBorder;
63      this.chart.ChartAreas[0].AxisX.Maximum = TestAxisValue + TrainingTestBorder;
64      AddCustomLabelToAxis(this.chart.ChartAreas[0].AxisX);
65
66      this.chart.ChartAreas[0].AxisY.Title = "Estimated Values";
67      this.chart.ChartAreas[0].CursorY.IsUserSelectionEnabled = true;
68      this.chart.ChartAreas[0].AxisX.ScaleView.Zoomable = true;
69    }
70
71    private void AddCustomLabelToAxis(Axis axis) {
72      CustomLabel trainingLabel = new CustomLabel();
73      trainingLabel.Text = TrainingLabelText;
74      trainingLabel.FromPosition = TrainingAxisValue - TrainingTestBorder;
75      trainingLabel.ToPosition = TrainingAxisValue + TrainingTestBorder;
76      axis.CustomLabels.Add(trainingLabel);
77
78      CustomLabel testLabel = new CustomLabel();
79      testLabel.Text = TestLabelText;
80      testLabel.FromPosition = TestAxisValue - TrainingTestBorder;
81      testLabel.ToPosition = TestAxisValue + TrainingTestBorder;
82      axis.CustomLabels.Add(testLabel);
83    }
84
85    protected override void RegisterContentEvents() {
86      base.RegisterContentEvents();
87      Content.ModelChanged += new EventHandler(Content_ModelChanged);
88      Content.ProblemDataChanged += new EventHandler(Content_ProblemDataChanged);
89    }
90    protected override void DeregisterContentEvents() {
91      base.DeregisterContentEvents();
92      Content.ModelChanged -= new EventHandler(Content_ModelChanged);
93      Content.ProblemDataChanged -= new EventHandler(Content_ProblemDataChanged);
94    }
95
96    private void Content_ProblemDataChanged(object sender, EventArgs e) {
97      UpdateChart();
98    }
99    private void Content_ModelChanged(object sender, EventArgs e) {
100      Content.Model.ThresholdsChanged += new EventHandler(Model_ThresholdsChanged);
101      UpdateChart();
102    }
103    private void Model_ThresholdsChanged(object sender, EventArgs e) {
104      AddThresholds();
105    }
106    protected override void OnContentChanged() {
107      base.OnContentChanged();
108      UpdateChart();
109    }
110
111    private void UpdateChart() {
112      if (InvokeRequired) Invoke((Action)UpdateChart);
113      else if (!updateInProgress) {
114        updateInProgress = true;
115        chart.Series.Clear();
116        classValueSeriesMapping.Clear();
117        if (Content != null) {
118          IEnumerator<string> classNameEnumerator = Content.ProblemData.ClassNames.GetEnumerator();
119          IEnumerator<double> classValueEnumerator = Content.ProblemData.ClassValues.OrderBy(x => x).GetEnumerator();
120          while (classNameEnumerator.MoveNext() && classValueEnumerator.MoveNext()) {
121            Series series = new Series(classNameEnumerator.Current);
122            series.ChartType = SeriesChartType.FastPoint;
123            series.Tag = classValueEnumerator.Current;
124            chart.Series.Add(series);
125            classValueSeriesMapping.Add(classValueEnumerator.Current, series);
126            FillSeriesWithDataPoints(series);
127          }
128          AddThresholds();
129        }
130        chart.ChartAreas[0].RecalculateAxesScale();
131        updateInProgress = false;
132      }
133    }
134
135    private void FillSeriesWithDataPoints(Series series) {
136      List<double> estimatedValues = Content.EstimatedValues.ToList();
137      foreach (int row in Content.ProblemData.TrainingIndizes) {
138        double estimatedValue = estimatedValues[row];
139        double targetValue = Content.ProblemData.Dataset[Content.ProblemData.TargetVariable, row];
140        if (targetValue.IsAlmost((double)series.Tag)) {
141          double jitterValue = random.NextDouble() * 2.0 - 1.0;
142          DataPoint point = new DataPoint();
143          point.XValue = TrainingAxisValue + 0.01 * jitterValue * JitterTrackBar.Value * (TrainingTestBorder * 0.9);
144          point.YValues[0] = estimatedValue;
145          point.Tag = new KeyValuePair<double, double>(TrainingAxisValue, jitterValue);
146          series.Points.Add(point);
147        }
148      }
149
150      foreach (int row in Content.ProblemData.TestIndizes) {
151        double estimatedValue = estimatedValues[row];
152        double targetValue = Content.ProblemData.Dataset[Content.ProblemData.TargetVariable, row];
153        if (targetValue == (double)series.Tag) {
154          double jitterValue = random.NextDouble() * 2.0 - 1.0;
155          DataPoint point = new DataPoint();
156          point.XValue = TestAxisValue + 0.01 * jitterValue * JitterTrackBar.Value * (TrainingTestBorder * 0.9);
157          point.YValues[0] = estimatedValue;
158          point.Tag = new KeyValuePair<double, double>(TestAxisValue, jitterValue);
159          series.Points.Add(point);
160        }
161      }
162
163      UpdateCursorInterval();
164    }
165
166    private void AddThresholds() {
167      chart.Annotations.Clear();
168      int classIndex = 1;
169      foreach (double threshold in Content.Model.Thresholds) {
170        if (!double.IsInfinity(threshold)) {
171          HorizontalLineAnnotation annotation = new HorizontalLineAnnotation();
172          annotation.AllowMoving = true;
173          annotation.AllowResizing = false;
174          annotation.LineWidth = 2;
175          annotation.LineColor = Color.Red;
176
177          annotation.IsInfinitive = true;
178          annotation.ClipToChartArea = chart.ChartAreas[0].Name;
179          annotation.Tag = classIndex;  //save classIndex as Tag to avoid moving the threshold accross class bounderies
180
181          annotation.AxisX = chart.ChartAreas[0].AxisX;
182          annotation.AxisY = chart.ChartAreas[0].AxisY;
183          annotation.Y = threshold;
184
185          chart.Annotations.Add(annotation);
186          classIndex++;
187        }
188      }
189    }
190
191    private void JitterTrackBar_ValueChanged(object sender, EventArgs e) {
192      foreach (Series series in chart.Series) {
193        foreach (DataPoint point in series.Points) {
194          double value = ((KeyValuePair<double, double>)point.Tag).Key;
195          double jitterValue = ((KeyValuePair<double, double>)point.Tag).Value; ;
196          point.XValue = value + 0.01 * jitterValue * JitterTrackBar.Value * (TrainingTestBorder * 0.9);
197        }
198      }
199    }
200
201    private void chart_CustomizeLegend(object sender, CustomizeLegendEventArgs e) {
202      foreach (LegendItem legendItem in e.LegendItems) {
203        var series = chart.Series[legendItem.SeriesName];
204        if (series != null) {
205          bool seriesIsInvisible = series.Points.Count == 0;
206          foreach (LegendCell cell in legendItem.Cells)
207            cell.ForeColor = seriesIsInvisible ? Color.Gray : Color.Black;
208        }
209      }
210    }
211
212    private void chart_MouseMove(object sender, MouseEventArgs e) {
213      HitTestResult result = chart.HitTest(e.X, e.Y);
214      if (result.ChartElementType == ChartElementType.LegendItem)
215        this.Cursor = Cursors.Hand;
216      else
217        this.Cursor = Cursors.Default;
218    }
219
220    private void ToggleSeries(Series series) {
221      if (series.Points.Count == 0)
222        FillSeriesWithDataPoints(series);
223      else
224        series.Points.Clear();
225    }
226
227    private void chart_MouseDown(object sender, MouseEventArgs e) {
228      HitTestResult result = chart.HitTest(e.X, e.Y);
229      if (result.ChartElementType == ChartElementType.LegendItem) {
230        if (result.Series != null) ToggleSeries(result.Series);
231      }
232    }
233
234    private void chart_AnnotationPositionChanging(object sender, AnnotationPositionChangingEventArgs e) {
235      int classIndex = (int)e.Annotation.Tag;
236      double[] thresholds = Content.Model.Thresholds.ToArray();
237      thresholds[classIndex] = e.NewLocationY;
238      Content.Model.SetThresholdsAndClassValues(thresholds, Content.Model.ClassValues);
239    }
240
241    private void UpdateCursorInterval() {
242      Series series = chart.Series[0];
243      double[] xValues = (from point in series.Points
244                          where !point.IsEmpty
245                          select point.XValue)
246                    .DefaultIfEmpty(1.0)
247                    .ToArray();
248      double[] yValues = (from point in series.Points
249                          where !point.IsEmpty
250                          select point.YValues[0])
251                    .DefaultIfEmpty(1.0)
252                    .ToArray();
253
254      double xRange = xValues.Max() - xValues.Min();
255      double yRange = yValues.Max() - yValues.Min();
256      if (xRange.IsAlmost(0.0)) xRange = 1.0;
257      if (yRange.IsAlmost(0.0)) yRange = 1.0;
258      double xDigits = (int)Math.Log10(xRange) - 3;
259      double yDigits = (int)Math.Log10(yRange) - 3;
260      double xZoomInterval = Math.Pow(10, xDigits);
261      double yZoomInterval = Math.Pow(10, yDigits);
262      this.chart.ChartAreas[0].CursorX.Interval = xZoomInterval;
263      this.chart.ChartAreas[0].CursorY.Interval = yZoomInterval;
264    }
265  }
266}
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