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source: branches/ClassificationModelComparison/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionLineChartView.cs @ 11846

Last change on this file since 11846 was 10556, checked in by mkommend, 11 years ago

#1998: Updated classification model comparison branch with trunk changes (remaining changes).
File size: 13.8 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2013 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
21using System;
22using System.Collections.Generic;
23using System.Drawing;
24using System.Linq;
25using System.Windows.Forms;
26using System.Windows.Forms.DataVisualization.Charting;
27using HeuristicLab.MainForm;
28
29namespace HeuristicLab.Problems.DataAnalysis.Views {
30  [View("Line Chart")]
31  [Content(typeof(IRegressionSolution))]
32  public partial class RegressionSolutionLineChartView : DataAnalysisSolutionEvaluationView {
33    private const string TARGETVARIABLE_SERIES_NAME = "Target Variable";
34    private const string ESTIMATEDVALUES_TRAINING_SERIES_NAME = "Estimated Values (training)";
35    private const string ESTIMATEDVALUES_TEST_SERIES_NAME = "Estimated Values (test)";
36    private const string ESTIMATEDVALUES_ALL_SERIES_NAME = "Estimated Values (all samples)";
37
38    public new IRegressionSolution Content {
39      get { return (IRegressionSolution)base.Content; }
40      set { base.Content = value; }
41    }
42
43    public RegressionSolutionLineChartView()
44      : base() {
45      InitializeComponent();
46      //configure axis
47      this.chart.CustomizeAllChartAreas();
48      this.chart.ChartAreas[0].CursorX.IsUserSelectionEnabled = true;
49      this.chart.ChartAreas[0].AxisX.ScaleView.Zoomable = true;
50      this.chart.ChartAreas[0].AxisX.IsStartedFromZero = true;
51      this.chart.ChartAreas[0].CursorX.Interval = 1;
52
53      this.chart.ChartAreas[0].CursorY.IsUserSelectionEnabled = true;
54      this.chart.ChartAreas[0].AxisY.ScaleView.Zoomable = true;
55      this.chart.ChartAreas[0].CursorY.Interval = 0;
56    }
57
58    private void RedrawChart() {
59      this.chart.Series.Clear();
60      if (Content != null) {
61        this.chart.ChartAreas[0].AxisX.Minimum = 0;
62        this.chart.ChartAreas[0].AxisX.Maximum = Content.ProblemData.Dataset.Rows - 1;
63
64        this.chart.Series.Add(TARGETVARIABLE_SERIES_NAME);
65        this.chart.Series[TARGETVARIABLE_SERIES_NAME].LegendText = Content.ProblemData.TargetVariable;
66        this.chart.Series[TARGETVARIABLE_SERIES_NAME].ChartType = SeriesChartType.FastLine;
67        this.chart.Series[TARGETVARIABLE_SERIES_NAME].Points.DataBindXY(Enumerable.Range(0, Content.ProblemData.Dataset.Rows).ToArray(),
68          Content.ProblemData.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToArray());
69        // training series
70        this.chart.Series.Add(ESTIMATEDVALUES_TRAINING_SERIES_NAME);
71        this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].LegendText = ESTIMATEDVALUES_TRAINING_SERIES_NAME;
72        this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].ChartType = SeriesChartType.FastLine;
73        this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].EmptyPointStyle.Color = this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Color;
74        this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TrainingIndices.ToArray(), Content.EstimatedTrainingValues.ToArray());
75        this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME]);
76        this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Tag = Content;
77        // test series
78        this.chart.Series.Add(ESTIMATEDVALUES_TEST_SERIES_NAME);
79        this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].LegendText = ESTIMATEDVALUES_TEST_SERIES_NAME;
80        this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].ChartType = SeriesChartType.FastLine;
81        this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TestIndices.ToArray(), Content.EstimatedTestValues.ToArray());
82        this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME]);
83        this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Tag = Content;
84        // series of remaining points
85        int[] allIndices = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndices).Except(Content.ProblemData.TestIndices).ToArray();
86        var estimatedValues = Content.EstimatedValues.ToArray();
87        List<double> allEstimatedValues = allIndices.Select(index => estimatedValues[index]).ToList();
88        this.chart.Series.Add(ESTIMATEDVALUES_ALL_SERIES_NAME);
89        this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].LegendText = ESTIMATEDVALUES_ALL_SERIES_NAME;
90        this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].ChartType = SeriesChartType.FastLine;
91        if (allEstimatedValues.Count > 0) {
92          this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].Points.DataBindXY(allIndices, allEstimatedValues);
93          this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME]);
94        }
95        this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].Tag = Content;
96        this.ToggleSeriesData(this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME]);
97
98        UpdateCursorInterval();
99        this.UpdateStripLines();
100      }
101    }
102
103    private void InsertEmptyPoints(Series series) {
104      int i = 0;
105      while (i < series.Points.Count - 1) {
106        if (series.Points[i].IsEmpty) {
107          ++i;
108          continue;
109        }
110
111        var p1 = series.Points[i];
112        var p2 = series.Points[i + 1];
113        // check for consecutive indices
114        if ((int)p2.XValue - (int)p1.XValue != 1) {
115          // insert an empty point between p1 and p2 so that the line will be invisible (transparent)
116          var p = new DataPoint((int)((p1.XValue + p2.XValue) / 2), 0.0) { IsEmpty = true };
117          series.Points.Insert(i + 1, p);
118        }
119        ++i;
120      }
121    }
122
123    private void UpdateCursorInterval() {
124      var estimatedValues = this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Points.Select(x => x.YValues[0]).DefaultIfEmpty(1.0);
125      var targetValues = this.chart.Series[TARGETVARIABLE_SERIES_NAME].Points.Select(x => x.YValues[0]).DefaultIfEmpty(1.0);
126      double estimatedValuesRange = estimatedValues.Max() - estimatedValues.Min();
127      double targetValuesRange = targetValues.Max() - targetValues.Min();
128      double interestingValuesRange = Math.Min(Math.Max(targetValuesRange, 1.0), Math.Max(estimatedValuesRange, 1.0));
129      double digits = (int)Math.Log10(interestingValuesRange) - 3;
130      double yZoomInterval = Math.Max(Math.Pow(10, digits), 10E-5);
131      this.chart.ChartAreas[0].CursorY.Interval = yZoomInterval;
132    }
133
134    #region events
135    protected override void RegisterContentEvents() {
136      base.RegisterContentEvents();
137      Content.ModelChanged += new EventHandler(Content_ModelChanged);
138      Content.ProblemDataChanged += new EventHandler(Content_ProblemDataChanged);
139    }
140    protected override void DeregisterContentEvents() {
141      base.DeregisterContentEvents();
142      Content.ModelChanged -= new EventHandler(Content_ModelChanged);
143      Content.ProblemDataChanged -= new EventHandler(Content_ProblemDataChanged);
144    }
145
146    protected override void OnContentChanged() {
147      base.OnContentChanged();
148      RedrawChart();
149    }
150    private void Content_ProblemDataChanged(object sender, EventArgs e) {
151      RedrawChart();
152    }
153    private void Content_ModelChanged(object sender, EventArgs e) {
154      RedrawChart();
155    }
156
157
158
159    private void Chart_MouseDoubleClick(object sender, MouseEventArgs e) {
160      HitTestResult result = chart.HitTest(e.X, e.Y);
161      if (result.ChartArea != null && (result.ChartElementType == ChartElementType.PlottingArea ||
162                                       result.ChartElementType == ChartElementType.Gridlines) ||
163                                       result.ChartElementType == ChartElementType.StripLines) {
164        foreach (var axis in result.ChartArea.Axes)
165          axis.ScaleView.ZoomReset(int.MaxValue);
166      }
167    }
168    #endregion
169
170    private void UpdateStripLines() {
171      this.chart.ChartAreas[0].AxisX.StripLines.Clear();
172
173      int[] attr = new int[Content.ProblemData.Dataset.Rows + 1]; // add a virtual last row that is again empty to simplify loop further down
174      foreach (var row in Content.ProblemData.TrainingIndices) {
175        attr[row] += 1;
176      }
177      foreach (var row in Content.ProblemData.TestIndices) {
178        attr[row] += 2;
179      }
180      int start = 0;
181      int curAttr = attr[start];
182      for (int row = 0; row < attr.Length; row++) {
183        if (attr[row] != curAttr) {
184          switch (curAttr) {
185            case 0: break;
186            case 1:
187              this.CreateAndAddStripLine("Training", start, row, Color.FromArgb(40, Color.Green), Color.Transparent);
188              break;
189            case 2:
190              this.CreateAndAddStripLine("Test", start, row, Color.FromArgb(40, Color.Red), Color.Transparent);
191              break;
192            case 3:
193              this.CreateAndAddStripLine("Training and Test", start, row, Color.FromArgb(40, Color.Green), Color.FromArgb(40, Color.Red), ChartHatchStyle.WideUpwardDiagonal);
194              break;
195            default:
196              // should not happen
197              break;
198          }
199          curAttr = attr[row];
200          start = row;
201        }
202      }
203    }
204
205    private void CreateAndAddStripLine(string title, int start, int end, Color color, Color secondColor, ChartHatchStyle hatchStyle = ChartHatchStyle.None) {
206      StripLine stripLine = new StripLine();
207      stripLine.BackColor = color;
208      stripLine.BackSecondaryColor = secondColor;
209      stripLine.BackHatchStyle = hatchStyle;
210      stripLine.Text = title;
211      stripLine.Font = new Font("Times New Roman", 12, FontStyle.Bold);
212      // strip range is [start .. end] inclusive, but we evaluate [start..end[ (end is exclusive)
213      // the strip should be by one longer (starting at start - 0.5 and ending at end + 0.5)
214      stripLine.StripWidth = end - start;
215      stripLine.IntervalOffset = start - 0.5; // start slightly to the left of the first point to clearly indicate the first point in the partition
216      this.chart.ChartAreas[0].AxisX.StripLines.Add(stripLine);
217    }
218
219    private void ToggleSeriesData(Series series) {
220      if (series.Points.Count > 0) {  //checks if series is shown
221        if (this.chart.Series.Any(s => s != series && s.Points.Count > 0)) {
222          ClearPointsQuick(series.Points);
223        }
224      } else if (Content != null) {
225        string targetVariableName = Content.ProblemData.TargetVariable;
226
227        IEnumerable<int> indices = null;
228        double[] predictedValues = null;
229        switch (series.Name) {
230          case ESTIMATEDVALUES_ALL_SERIES_NAME:
231            indices = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndices).Except(Content.ProblemData.TestIndices).ToArray();
232            var estimatedValues = Content.EstimatedValues.ToArray();
233            predictedValues = indices.Select(index => estimatedValues[index]).ToArray();
234            break;
235          case ESTIMATEDVALUES_TRAINING_SERIES_NAME:
236            indices = Content.ProblemData.TrainingIndices.ToArray();
237            predictedValues = Content.EstimatedTrainingValues.ToArray();
238            break;
239          case ESTIMATEDVALUES_TEST_SERIES_NAME:
240            indices = Content.ProblemData.TestIndices.ToArray();
241            predictedValues = Content.EstimatedTestValues.ToArray();
242            break;
243        }
244        if (predictedValues.Length > 0) {
245          series.Points.DataBindXY(indices, predictedValues);
246          this.InsertEmptyPoints(series);
247        }
248        chart.Legends[series.Legend].ForeColor = Color.Black;
249        UpdateCursorInterval();
250        chart.Refresh();
251      }
252    }
253
254    // workaround as per http://stackoverflow.com/questions/5744930/datapointcollection-clear-performance
255    private static void ClearPointsQuick(DataPointCollection points) {
256      points.SuspendUpdates();
257      while (points.Count > 0)
258        points.RemoveAt(points.Count - 1);
259      points.ResumeUpdates();
260    }
261
262    private void chart_MouseMove(object sender, MouseEventArgs e) {
263      HitTestResult result = chart.HitTest(e.X, e.Y);
264      if (result.ChartElementType == ChartElementType.LegendItem && result.Series.Name != TARGETVARIABLE_SERIES_NAME)
265        Cursor = Cursors.Hand;
266      else
267        Cursor = Cursors.Default;
268    }
269    private void chart_MouseDown(object sender, MouseEventArgs e) {
270      HitTestResult result = chart.HitTest(e.X, e.Y);
271      if (result.ChartElementType == ChartElementType.LegendItem && result.Series.Name != TARGETVARIABLE_SERIES_NAME) {
272        ToggleSeriesData(result.Series);
273      }
274    }
275
276    private void chart_CustomizeLegend(object sender, CustomizeLegendEventArgs e) {
277      if (chart.Series.Count != 4) return;
278      e.LegendItems[0].Cells[1].ForeColor = this.chart.Series[TARGETVARIABLE_SERIES_NAME].Points.Count == 0 ? Color.Gray : Color.Black;
279      e.LegendItems[1].Cells[1].ForeColor = this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Points.Count == 0 ? Color.Gray : Color.Black;
280      e.LegendItems[2].Cells[1].ForeColor = this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Points.Count == 0 ? Color.Gray : Color.Black;
281      e.LegendItems[3].Cells[1].ForeColor = this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].Points.Count == 0 ? Color.Gray : Color.Black;
282    }
283  }
284}
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