source: branches/2971_named_intervals/HeuristicLab.Problems.DataAnalysis.Views/3.4/Controls/PartialDependencePlot.cs @ 17372

Last change on this file since 17372 was 17372, checked in by chaider, 10 months ago

#2971 Changed partial dependence plot range to interval range

File size: 27.9 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 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;
24using System.Collections.Generic;
25using System.Drawing;
26using System.Globalization;
27using System.Linq;
28using System.Threading;
29using System.Threading.Tasks;
30using System.Windows.Forms;
31using System.Windows.Forms.DataVisualization.Charting;
32using HeuristicLab.Common;
33using HeuristicLab.MainForm.WindowsForms;
34using HeuristicLab.Visualization.ChartControlsExtensions;
35
36namespace HeuristicLab.Problems.DataAnalysis.Views {
37  public partial class PartialDependencePlot : UserControl, IPartialDependencePlot {
38    private ModifiableDataset sharedFixedVariables; // used for synchronizing variable values between charts
39    private ModifiableDataset internalDataset; // holds the x values for each point drawn
40
41    private CancellationTokenSource cancelCurrentRecalculateSource;
42
43    private readonly List<IRegressionSolution> solutions;
44    private readonly Dictionary<IRegressionSolution, Series> seriesCache;
45    private readonly Dictionary<IRegressionSolution, Series> ciSeriesCache;
46
47    private readonly ToolStripMenuItem configToolStripMenuItem;
48    private readonly PartialDependencePlotConfigurationDialog configurationDialog;
49
50    #region Properties
51    public string XAxisTitle {
52      get { return chart.ChartAreas[0].AxisX.Title; }
53      set { chart.ChartAreas[0].AxisX.Title = value; }
54    }
55
56    public string YAxisTitle {
57      get { return chart.ChartAreas[0].AxisY.Title; }
58      set { chart.ChartAreas[0].AxisY.Title = value; }
59    }
60
61    public bool ShowLegend {
62      get { return chart.Legends[0].Enabled; }
63      set { chart.Legends[0].Enabled = value; }
64    }
65    public bool ShowCursor {
66      get { return chart.Annotations[0].Visible; }
67      set {
68        chart.Annotations[0].Visible = value;
69        if (!value) chart.Titles[0].Text = string.Empty;
70      }
71    }
72
73    public bool ShowConfigButton {
74      get { return configurationButton.Visible; }
75      set { configurationButton.Visible = value; }
76    }
77
78    private int xAxisTicks = 5;
79    public int XAxisTicks {
80      get { return xAxisTicks; }
81      set {
82        if (value != xAxisTicks) {
83          xAxisTicks = value;
84          SetupAxis(chart, chart.ChartAreas[0].AxisX, trainingMin, trainingMax, XAxisTicks, FixedXAxisMin, FixedXAxisMax);
85          RecalculateInternalDataset();
86        }
87      }
88    }
89    private double? fixedXAxisMin;
90    public double? FixedXAxisMin {
91      get { return fixedXAxisMin; }
92      set {
93        if ((value.HasValue && fixedXAxisMin.HasValue && !value.Value.IsAlmost(fixedXAxisMin.Value)) || (value.HasValue != fixedXAxisMin.HasValue)) {
94          fixedXAxisMin = value;
95          SetupAxis(chart, chart.ChartAreas[0].AxisX, trainingMin, trainingMax, XAxisTicks, FixedXAxisMin, FixedXAxisMax);
96          RecalculateInternalDataset();
97          // set the vertical line position
98          if (VerticalLineAnnotation.X <= fixedXAxisMin) {
99            var axisX = chart.ChartAreas[0].AxisX;
100            var step = (axisX.Maximum - axisX.Minimum) / drawingSteps;
101            VerticalLineAnnotation.X = axisX.Minimum + step;
102          }
103        }
104      }
105    }
106    private double? fixedXAxisMax;
107    public double? FixedXAxisMax {
108      get { return fixedXAxisMax; }
109      set {
110        if ((value.HasValue && fixedXAxisMax.HasValue && !value.Value.IsAlmost(fixedXAxisMax.Value)) || (value.HasValue != fixedXAxisMax.HasValue)) {
111          fixedXAxisMax = value;
112          SetupAxis(chart, chart.ChartAreas[0].AxisX, trainingMin, trainingMax, XAxisTicks, FixedXAxisMin, FixedXAxisMax);
113          RecalculateInternalDataset();
114          // set the vertical line position
115          if (VerticalLineAnnotation.X >= fixedXAxisMax) {
116            var axisX = chart.ChartAreas[0].AxisX;
117            var step = (axisX.Maximum - axisX.Minimum) / drawingSteps;
118            VerticalLineAnnotation.X = axisX.Maximum - step;
119          }
120        }
121      }
122    }
123
124    private int yAxisTicks = 5;
125    public int YAxisTicks {
126      get { return yAxisTicks; }
127      set {
128        if (value != yAxisTicks) {
129          yAxisTicks = value;
130          SetupAxis(chart, chart.ChartAreas[0].AxisY, yMin, yMax, YAxisTicks, FixedYAxisMin, FixedYAxisMax);
131          RecalculateInternalDataset();
132        }
133      }
134    }
135    private double? fixedYAxisMin;
136    public double? FixedYAxisMin {
137      get { return fixedYAxisMin; }
138      set {
139        if ((value.HasValue && fixedYAxisMin.HasValue && !value.Value.IsAlmost(fixedYAxisMin.Value)) || (value.HasValue != fixedYAxisMin.HasValue)) {
140          fixedYAxisMin = value;
141          SetupAxis(chart, chart.ChartAreas[0].AxisY, yMin, yMax, YAxisTicks, FixedYAxisMin, FixedYAxisMax);
142        }
143      }
144    }
145    private double? fixedYAxisMax;
146    public double? FixedYAxisMax {
147      get { return fixedYAxisMax; }
148      set {
149        if ((value.HasValue && fixedYAxisMax.HasValue && !value.Value.IsAlmost(fixedYAxisMax.Value)) || (value.HasValue != fixedYAxisMax.HasValue)) {
150          fixedYAxisMax = value;
151          SetupAxis(chart, chart.ChartAreas[0].AxisY, yMin, yMax, YAxisTicks, FixedYAxisMin, FixedYAxisMax);
152        }
153      }
154    }
155
156    private double trainingMin = -1;
157    private double trainingMax = 1;
158
159    private int drawingSteps = 1000;
160    public int DrawingSteps {
161      get { return drawingSteps; }
162      set {
163        if (value != drawingSteps) {
164          drawingSteps = value;
165          RecalculateInternalDataset();
166          ResizeAllSeriesData();
167        }
168      }
169    }
170
171    private string freeVariable;
172    public string FreeVariable {
173      get { return freeVariable; }
174      set {
175        if (value == freeVariable) return;
176        if (solutions.Any(s => !s.ProblemData.Dataset.DoubleVariables.Contains(value))) {
177          throw new ArgumentException("Variable does not exist in the ProblemData of the Solutions.");
178        }
179        freeVariable = value;
180        RecalculateInternalDataset();
181      }
182    }
183
184    private double yMin;
185    public double YMin {
186      get { return yMin; }
187    }
188    private double yMax;
189    public double YMax {
190      get { return yMax; }
191    }
192
193    public bool IsZoomed {
194      get { return chart.ChartAreas[0].AxisX.ScaleView.IsZoomed; }
195    }
196
197    private VerticalLineAnnotation VerticalLineAnnotation {
198      get { return (VerticalLineAnnotation)chart.Annotations.SingleOrDefault(x => x is VerticalLineAnnotation); }
199    }
200
201    internal ElementPosition InnerPlotPosition {
202      get { return chart.ChartAreas[0].InnerPlotPosition; }
203    }
204    #endregion
205
206    public event EventHandler ChartPostPaint;
207
208    public PartialDependencePlot() {
209      InitializeComponent();
210
211      solutions = new List<IRegressionSolution>();
212      seriesCache = new Dictionary<IRegressionSolution, Series>();
213      ciSeriesCache = new Dictionary<IRegressionSolution, Series>();
214
215      // Configure axis
216      chart.CustomizeAllChartAreas();
217      chart.ChartAreas[0].CursorX.IsUserSelectionEnabled = false;
218      chart.ChartAreas[0].CursorY.IsUserSelectionEnabled = false;
219
220      chart.ChartAreas[0].Axes.ToList().ForEach(x => { x.ScaleView.Zoomable = false; });
221
222      configToolStripMenuItem = new ToolStripMenuItem("Configuration");
223      configToolStripMenuItem.Click += config_Click;
224      chart.ContextMenuStrip.Items.Add(new ToolStripSeparator());
225      chart.ContextMenuStrip.Items.Add(configToolStripMenuItem);
226      configurationDialog = new PartialDependencePlotConfigurationDialog(this);
227
228      Disposed += Control_Disposed;
229    }
230
231    private void Control_Disposed(object sender, EventArgs e) {
232      if (cancelCurrentRecalculateSource != null)
233        cancelCurrentRecalculateSource.Cancel();
234    }
235
236    public void Configure(IEnumerable<IRegressionSolution> solutions, ModifiableDataset sharedFixedVariables, string freeVariable, int drawingSteps, bool initializeAxisRanges = true) {
237      if (!SolutionsCompatible(solutions))
238        throw new ArgumentException("Solutions are not compatible with the problem data.");
239      this.freeVariable = freeVariable;
240      this.drawingSteps = drawingSteps;
241
242      this.solutions.Clear();
243      this.solutions.AddRange(solutions);
244
245      // add an event such that whenever a value is changed in the shared dataset,
246      // this change is reflected in the internal dataset (where the value becomes a whole column)
247      if (this.sharedFixedVariables != null) {
248        this.sharedFixedVariables.ItemChanged -= sharedFixedVariables_ItemChanged;
249        this.sharedFixedVariables.Reset -= sharedFixedVariables_Reset;
250      }
251
252      this.sharedFixedVariables = sharedFixedVariables;
253      this.sharedFixedVariables.ItemChanged += sharedFixedVariables_ItemChanged;
254      this.sharedFixedVariables.Reset += sharedFixedVariables_Reset;
255
256      RecalculateTrainingLimits(initializeAxisRanges);
257      RecalculateInternalDataset();
258
259      chart.Series.Clear();
260      seriesCache.Clear();
261      ciSeriesCache.Clear();
262      foreach (var solution in this.solutions) {
263        var series = CreateSeries(solution);
264        seriesCache.Add(solution, series.Item1);
265        if (series.Item2 != null)
266          ciSeriesCache.Add(solution, series.Item2);
267      }
268
269      // Set cursor and x-axis
270      // Make sure to allow a small offset to be able to distinguish the vertical line annotation from the axis
271      var defaultValue = sharedFixedVariables.GetDoubleValue(freeVariable, 0);
272      var step = (trainingMax - trainingMin) / drawingSteps;
273      var minimum = chart.ChartAreas[0].AxisX.Minimum;
274      var maximum = chart.ChartAreas[0].AxisX.Maximum;
275      if (defaultValue <= minimum)
276        VerticalLineAnnotation.X = minimum + step;
277      else if (defaultValue >= maximum)
278        VerticalLineAnnotation.X = maximum - step;
279      else
280        VerticalLineAnnotation.X = defaultValue;
281
282      if (ShowCursor)
283        chart.Titles[0].Text = FreeVariable + " : " + defaultValue.ToString("G5", CultureInfo.CurrentCulture);
284
285      ResizeAllSeriesData();
286      OrderAndColorSeries();
287    }
288
289    public async Task RecalculateAsync(bool updateOnFinish = true, bool resetYAxis = true) {
290      if (IsDisposed
291        || sharedFixedVariables == null || !solutions.Any() || string.IsNullOrEmpty(freeVariable)
292        || trainingMin > trainingMax || drawingSteps == 0)
293        return;
294
295      calculationPendingTimer.Start();
296
297      // cancel previous recalculate call
298      if (cancelCurrentRecalculateSource != null)
299        cancelCurrentRecalculateSource.Cancel();
300      cancelCurrentRecalculateSource = new CancellationTokenSource();
301      var cancellationToken = cancelCurrentRecalculateSource.Token;
302
303      // Update series
304      try {
305        var limits = await UpdateAllSeriesDataAsync(cancellationToken);
306        chart.Invalidate();
307
308        yMin = limits.Lower;
309        yMax = limits.Upper;
310        // Set y-axis
311        if (resetYAxis)
312          SetupAxis(chart, chart.ChartAreas[0].AxisY, yMin, yMax, YAxisTicks, FixedYAxisMin, FixedYAxisMax);
313
314        UpdateOutOfTrainingRangeStripLines();
315
316        calculationPendingTimer.Stop();
317        calculationPendingLabel.Visible = false;
318        if (updateOnFinish)
319          Update();
320      } catch (OperationCanceledException) {
321      } catch (AggregateException ae) {
322        if (!ae.InnerExceptions.Any(e => e is OperationCanceledException))
323          throw;
324      }
325    }
326
327    public void UpdateTitlePosition() {
328      var title = chart.Titles[0];
329      var plotArea = InnerPlotPosition;
330
331      title.Visible = plotArea.Width != 0;
332
333      title.Position.X = plotArea.X + (plotArea.Width / 2);
334    }
335
336    private static void SetupAxis(EnhancedChart chart, Axis axis, double minValue, double maxValue, int ticks, double? fixedAxisMin, double? fixedAxisMax) {
337      //guard if only one distinct value is present
338      if (minValue.IsAlmost(maxValue)) {
339        minValue = minValue - 0.5;
340        maxValue = minValue + 0.5;
341      }
342
343      double axisMin, axisMax, axisInterval;
344      ChartUtil.CalculateAxisInterval(minValue, maxValue, ticks, out axisMin, out axisMax, out axisInterval);
345      axis.Minimum = fixedAxisMin ?? axisMin;
346      axis.Maximum = fixedAxisMax ?? axisMax;
347      axis.Interval = (axis.Maximum - axis.Minimum) / ticks;
348
349      chart.ChartAreas[0].RecalculateAxesScale();
350    }
351
352    private void RecalculateTrainingLimits(bool initializeAxisRanges) {
353      //Set min and max to the interval ranges
354      trainingMin = solutions.Select(s => s.ProblemData.VariableRanges.GetInterval(freeVariable).LowerBound).Max();
355      trainingMax = solutions.Select(s => s.ProblemData.VariableRanges.GetInterval(freeVariable).UpperBound).Min();
356
357      if (initializeAxisRanges) {
358        double xmin, xmax, xinterval;
359        //guard if only one distinct value is present
360        if (trainingMin.IsAlmost(trainingMax))
361          ChartUtil.CalculateAxisInterval(trainingMin - 0.5, trainingMax + 0.5, XAxisTicks, out xmin, out xmax, out xinterval);
362        else
363          ChartUtil.CalculateAxisInterval(trainingMin, trainingMax, XAxisTicks, out xmin, out xmax, out xinterval);
364
365        FixedXAxisMin = xmin;
366        FixedXAxisMax = xmax;
367      }
368    }
369
370    private void RecalculateInternalDataset() {
371      if (sharedFixedVariables == null)
372        return;
373
374      // we expand the range in order to get nice tick intervals on the x axis
375      double xmin, xmax, xinterval;
376      //guard if only one distinct value is present
377      if (trainingMin.IsAlmost(trainingMax))
378        ChartUtil.CalculateAxisInterval(trainingMin - 0.5, trainingMin + 0.5, XAxisTicks, out xmin, out xmax, out xinterval);
379      else
380        ChartUtil.CalculateAxisInterval(trainingMin, trainingMax, XAxisTicks, out xmin, out xmax, out xinterval);
381
382      if (FixedXAxisMin.HasValue) xmin = FixedXAxisMin.Value;
383      if (FixedXAxisMax.HasValue) xmax = FixedXAxisMax.Value;
384      double step = (xmax - xmin) / drawingSteps;
385
386      var xvalues = new List<double>();
387      for (int i = 0; i < drawingSteps; i++)
388        xvalues.Add(xmin + i * step);
389
390      if (sharedFixedVariables == null)
391        return;
392
393      var variables = sharedFixedVariables.VariableNames.ToList();
394      var values = new List<IList>();
395      foreach (var varName in variables) {
396        if (varName == FreeVariable) {
397          values.Add(xvalues);
398        } else if (sharedFixedVariables.VariableHasType<double>(varName)) {
399          values.Add(Enumerable.Repeat(sharedFixedVariables.GetDoubleValue(varName, 0), xvalues.Count).ToList());
400        } else if (sharedFixedVariables.VariableHasType<string>(varName)) {
401          values.Add(Enumerable.Repeat(sharedFixedVariables.GetStringValue(varName, 0), xvalues.Count).ToList());
402        }
403      }
404
405      internalDataset = new ModifiableDataset(variables, values);
406    }
407
408    private Tuple<Series, Series> CreateSeries(IRegressionSolution solution) {
409      var series = new Series {
410        ChartType = SeriesChartType.Line,
411        Name = solution.ProblemData.TargetVariable + " " + solutions.IndexOf(solution)
412      };
413      series.LegendText = series.Name;
414
415      var confidenceBoundSolution = solution as IConfidenceRegressionSolution;
416      Series confidenceIntervalSeries = null;
417      if (confidenceBoundSolution != null) {
418        confidenceIntervalSeries = new Series {
419          ChartType = SeriesChartType.Range,
420          YValuesPerPoint = 2,
421          Name = "95% Conf. Interval " + series.Name,
422          IsVisibleInLegend = false
423        };
424      }
425      return Tuple.Create(series, confidenceIntervalSeries);
426    }
427
428    private void OrderAndColorSeries() {
429      chart.SuspendRepaint();
430
431      chart.Series.Clear();
432      // Add mean series for applying palette colors
433      foreach (var solution in solutions) {
434        chart.Series.Add(seriesCache[solution]);
435      }
436
437      chart.Palette = ChartColorPalette.BrightPastel;
438      chart.ApplyPaletteColors();
439      chart.Palette = ChartColorPalette.None;
440
441      // Add confidence interval series before its corresponding series for correct z index
442      foreach (var solution in solutions) {
443        Series ciSeries;
444        if (ciSeriesCache.TryGetValue(solution, out ciSeries)) {
445          var series = seriesCache[solution];
446          ciSeries.Color = Color.FromArgb(40, series.Color);
447          int idx = chart.Series.IndexOf(seriesCache[solution]);
448          chart.Series.Insert(idx, ciSeries);
449        }
450      }
451
452      chart.ResumeRepaint(true);
453    }
454
455    private async Task<DoubleLimit> UpdateAllSeriesDataAsync(CancellationToken cancellationToken) {
456      var updateTasks = solutions.Select(solution => UpdateSeriesDataAsync(solution, cancellationToken));
457
458      double min = double.MaxValue, max = double.MinValue;
459      foreach (var update in updateTasks) {
460        var limit = await update;
461        if (limit.Lower < min) min = limit.Lower;
462        if (limit.Upper > max) max = limit.Upper;
463      }
464
465      return new DoubleLimit(min, max);
466    }
467
468    private Task<DoubleLimit> UpdateSeriesDataAsync(IRegressionSolution solution, CancellationToken cancellationToken) {
469      return Task.Run(() => {
470        var xvalues = internalDataset.GetDoubleValues(FreeVariable).ToList();
471        var yvalues = solution.Model.GetEstimatedValues(internalDataset, Enumerable.Range(0, internalDataset.Rows)).ToList();
472
473        double min = double.MaxValue, max = double.MinValue;
474
475        var series = seriesCache[solution];
476        for (int i = 0; i < xvalues.Count; i++) {
477          series.Points[i].SetValueXY(xvalues[i], yvalues[i]);
478          if (yvalues[i] < min) min = yvalues[i];
479          if (yvalues[i] > max) max = yvalues[i];
480        }
481
482        cancellationToken.ThrowIfCancellationRequested();
483
484        var confidenceBoundSolution = solution as IConfidenceRegressionSolution;
485        if (confidenceBoundSolution != null) {
486          var confidenceIntervalSeries = ciSeriesCache[solution];
487          var variances = confidenceBoundSolution.Model.GetEstimatedVariances(internalDataset, Enumerable.Range(0, internalDataset.Rows)).ToList();
488          for (int i = 0; i < xvalues.Count; i++) {
489            var lower = yvalues[i] - 1.96 * Math.Sqrt(variances[i]);
490            var upper = yvalues[i] + 1.96 * Math.Sqrt(variances[i]);
491            confidenceIntervalSeries.Points[i].SetValueXY(xvalues[i], lower, upper);
492            if (lower < min) min = lower;
493            if (upper > max) max = upper;
494          }
495        }
496
497        cancellationToken.ThrowIfCancellationRequested();
498        return new DoubleLimit(min, max);
499      }, cancellationToken);
500    }
501
502    private void ResizeAllSeriesData() {
503      if (internalDataset == null)
504        return;
505
506      var xvalues = internalDataset.GetDoubleValues(FreeVariable).ToList();
507      foreach (var solution in solutions)
508        ResizeSeriesData(solution, xvalues);
509    }
510    private void ResizeSeriesData(IRegressionSolution solution, IList<double> xvalues = null) {
511      if (xvalues == null)
512        xvalues = internalDataset.GetDoubleValues(FreeVariable).ToList();
513
514      var series = seriesCache[solution];
515      series.Points.SuspendUpdates();
516      series.Points.Clear();
517      for (int i = 0; i < xvalues.Count; i++)
518        series.Points.Add(new DataPoint(xvalues[i], 0.0));
519      series.Points.ResumeUpdates();
520
521      Series confidenceIntervalSeries;
522      if (ciSeriesCache.TryGetValue(solution, out confidenceIntervalSeries)) {
523        confidenceIntervalSeries.Points.SuspendUpdates();
524        confidenceIntervalSeries.Points.Clear();
525        for (int i = 0; i < xvalues.Count; i++)
526          confidenceIntervalSeries.Points.Add(new DataPoint(xvalues[i], new[] { -1.0, 1.0 }));
527        confidenceIntervalSeries.Points.ResumeUpdates();
528      }
529    }
530
531    public async Task AddSolutionAsync(IRegressionSolution solution) {
532      if (!SolutionsCompatible(solutions.Concat(new[] { solution })))
533        throw new ArgumentException("The solution is not compatible with the problem data.");
534      if (solutions.Contains(solution))
535        return;
536
537      solutions.Add(solution);
538      RecalculateTrainingLimits(true);
539
540      var series = CreateSeries(solution);
541      seriesCache.Add(solution, series.Item1);
542      if (series.Item2 != null)
543        ciSeriesCache.Add(solution, series.Item2);
544
545      ResizeSeriesData(solution);
546      OrderAndColorSeries();
547
548      await RecalculateAsync();
549      var args = new EventArgs<IRegressionSolution>(solution);
550      OnSolutionAdded(this, args);
551    }
552
553    public async Task RemoveSolutionAsync(IRegressionSolution solution) {
554      if (!solutions.Remove(solution))
555        return;
556
557      RecalculateTrainingLimits(true);
558
559      seriesCache.Remove(solution);
560      ciSeriesCache.Remove(solution);
561
562      await RecalculateAsync();
563      var args = new EventArgs<IRegressionSolution>(solution);
564      OnSolutionRemoved(this, args);
565    }
566
567    private static bool SolutionsCompatible(IEnumerable<IRegressionSolution> solutions) {
568      var refSolution = solutions.First();
569      var refSolVars = refSolution.ProblemData.Dataset.VariableNames;
570      foreach (var solution in solutions.Skip(1)) {
571        var variables1 = solution.ProblemData.Dataset.VariableNames;
572        if (!variables1.All(refSolVars.Contains))
573          return false;
574
575        foreach (var factorVar in variables1.Where(solution.ProblemData.Dataset.VariableHasType<string>)) {
576          var distinctVals = refSolution.ProblemData.Dataset.GetStringValues(factorVar).Distinct();
577          if (solution.ProblemData.Dataset.GetStringValues(factorVar).Any(val => !distinctVals.Contains(val))) return false;
578        }
579      }
580      return true;
581    }
582
583    private void UpdateOutOfTrainingRangeStripLines() {
584      var axisX = chart.ChartAreas[0].AxisX;
585      var lowerStripLine = axisX.StripLines[0];
586      var upperStripLine = axisX.StripLines[1];
587
588      lowerStripLine.IntervalOffset = axisX.Minimum;
589      lowerStripLine.StripWidth = Math.Abs(trainingMin - axisX.Minimum);
590
591      upperStripLine.IntervalOffset = trainingMax;
592      upperStripLine.StripWidth = Math.Abs(axisX.Maximum - trainingMax);
593    }
594
595    #region Events
596    public event EventHandler<EventArgs<IRegressionSolution>> SolutionAdded;
597    public void OnSolutionAdded(object sender, EventArgs<IRegressionSolution> args) {
598      var added = SolutionAdded;
599      if (added == null) return;
600      added(sender, args);
601    }
602
603    public event EventHandler<EventArgs<IRegressionSolution>> SolutionRemoved;
604    public void OnSolutionRemoved(object sender, EventArgs<IRegressionSolution> args) {
605      var removed = SolutionRemoved;
606      if (removed == null) return;
607      removed(sender, args);
608    }
609
610    public event EventHandler VariableValueChanged;
611    public void OnVariableValueChanged(object sender, EventArgs args) {
612      var changed = VariableValueChanged;
613      if (changed == null) return;
614      changed(sender, args);
615    }
616
617    public event EventHandler ZoomChanged;
618    public void OnZoomChanged(object sender, EventArgs args) {
619      var changed = ZoomChanged;
620      if (changed == null) return;
621      changed(sender, args);
622    }
623
624    private void sharedFixedVariables_ItemChanged(object o, EventArgs<int, int> e) {
625      if (o != sharedFixedVariables) return;
626      var variables = sharedFixedVariables.VariableNames.ToList();
627      var rowIndex = e.Value;
628      var columnIndex = e.Value2;
629
630      var variableName = variables[columnIndex];
631      if (variableName == FreeVariable) return;
632
633      if (internalDataset.VariableHasType<double>(variableName)) {
634        var v = sharedFixedVariables.GetDoubleValue(variableName, rowIndex);
635        var values = new List<double>(Enumerable.Repeat(v, internalDataset.Rows));
636        internalDataset.ReplaceVariable(variableName, values);
637      } else if (internalDataset.VariableHasType<string>(variableName)) {
638        var v = sharedFixedVariables.GetStringValue(variableName, rowIndex);
639        var values = new List<String>(Enumerable.Repeat(v, internalDataset.Rows));
640        internalDataset.ReplaceVariable(variableName, values);
641      } else {
642        // unsupported type
643        throw new NotSupportedException();
644      }
645    }
646
647    private void sharedFixedVariables_Reset(object sender, EventArgs e) {
648      var newValue = sharedFixedVariables.GetDoubleValue(FreeVariable, 0);
649      VerticalLineAnnotation.X = newValue;
650      UpdateCursor(); // triggers update of InternalDataset
651    }
652
653    private void chart_AnnotationPositionChanging(object sender, AnnotationPositionChangingEventArgs e) {
654      var step = (trainingMax - trainingMin) / drawingSteps;
655      double newLocation = step * (long)Math.Round(e.NewLocationX / step);
656      var axisX = chart.ChartAreas[0].AxisX;
657      if (newLocation >= axisX.Maximum)
658        newLocation = axisX.Maximum - step;
659      if (newLocation <= axisX.Minimum)
660        newLocation = axisX.Minimum + step;
661
662      e.NewLocationX = newLocation;
663
664      UpdateCursor();
665    }
666    private void chart_AnnotationPositionChanged(object sender, EventArgs e) {
667      UpdateCursor();
668    }
669    private void UpdateCursor() {
670      var x = VerticalLineAnnotation.X;
671
672      if (!sharedFixedVariables.GetDoubleValue(FreeVariable, 0).IsAlmost(x))
673        sharedFixedVariables.SetVariableValue(x, FreeVariable, 0);
674
675      if (ShowCursor) {
676        chart.Titles[0].Text = FreeVariable + " : " + x.ToString("G5", CultureInfo.CurrentCulture);
677        chart.Update();
678      }
679
680      OnVariableValueChanged(this, EventArgs.Empty);
681    }
682
683    private void chart_MouseMove(object sender, MouseEventArgs e) {
684      bool hitCursor = chart.HitTest(e.X, e.Y).ChartElementType == ChartElementType.Annotation;
685      chart.Cursor = hitCursor ? Cursors.VSplit : Cursors.Default;
686    }
687
688    private async void chart_DragDrop(object sender, DragEventArgs e) {
689      var data = e.Data.GetData(HeuristicLab.Common.Constants.DragDropDataFormat);
690      if (data != null) {
691        var solution = data as IRegressionSolution;
692        if (!solutions.Contains(solution))
693          await AddSolutionAsync(solution);
694      }
695    }
696    private void chart_DragEnter(object sender, DragEventArgs e) {
697      if (!e.Data.GetDataPresent(HeuristicLab.Common.Constants.DragDropDataFormat)) return;
698      e.Effect = DragDropEffects.None;
699
700      var data = e.Data.GetData(HeuristicLab.Common.Constants.DragDropDataFormat);
701      var regressionSolution = data as IRegressionSolution;
702      if (regressionSolution != null) {
703        e.Effect = DragDropEffects.Copy;
704      }
705    }
706
707    private void calculationPendingTimer_Tick(object sender, EventArgs e) {
708      calculationPendingLabel.Visible = true;
709      Update();
710    }
711
712    private void config_Click(object sender, EventArgs e) {
713      configurationDialog.ShowDialog(this);
714      OnZoomChanged(this, EventArgs.Empty);
715    }
716
717    private void chart_SelectionRangeChanged(object sender, CursorEventArgs e) {
718      OnZoomChanged(this, EventArgs.Empty);
719    }
720
721    private void chart_Resize(object sender, EventArgs e) {
722      UpdateTitlePosition();
723    }
724
725    private void chart_PostPaint(object sender, ChartPaintEventArgs e) {
726      if (ChartPostPaint != null)
727        ChartPostPaint(this, EventArgs.Empty);
728    }
729    #endregion
730  }
731}
732
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