Changeset 13842 for branches/HeuristicLab.RegressionSolutionGradientView
- Timestamp:
- 05/11/16 12:18:00 (9 years ago)
- Location:
- branches/HeuristicLab.RegressionSolutionGradientView/HeuristicLab.Problems.DataAnalysis.Views/3.4
- Files:
-
- 5 edited
Legend:
- Unmodified
- Added
- Removed
-
branches/HeuristicLab.RegressionSolutionGradientView/HeuristicLab.Problems.DataAnalysis.Views/3.4/GradientChart.Designer.cs
r13840 r13842 64 64 this.chart.Size = new System.Drawing.Size(453, 308); 65 65 this.chart.TabIndex = 0; 66 this.chart.AnnotationPositionChanged += new System.EventHandler(this.chart_AnnotationPositionChanged);67 66 this.chart.AnnotationPositionChanging += new System.EventHandler<System.Windows.Forms.DataVisualization.Charting.AnnotationPositionChangingEventArgs>(this.chart_AnnotationPositionChanging); 68 67 this.chart.FormatNumber += new System.EventHandler<System.Windows.Forms.DataVisualization.Charting.FormatNumberEventArgs>(this.chart_FormatNumber); 69 this.chart.DragDrop += new System.Windows.Forms.DragEventHandler(this. GradientChart_DragDrop);70 this.chart.DragEnter += new System.Windows.Forms.DragEventHandler(this. GradientChart_DragEnter);68 this.chart.DragDrop += new System.Windows.Forms.DragEventHandler(this.chart_DragDrop); 69 this.chart.DragEnter += new System.Windows.Forms.DragEventHandler(this.chart_DragEnter); 71 70 this.chart.MouseMove += new System.Windows.Forms.MouseEventHandler(this.chart_MouseMove); 72 71 // -
branches/HeuristicLab.RegressionSolutionGradientView/HeuristicLab.Problems.DataAnalysis.Views/3.4/GradientChart.cs
r13840 r13842 38 38 private ModifiableDataset internalDataset; // holds the x values for each point drawn 39 39 40 private CancellationTokenSource cancelCurrentRefresh; 41 40 private CancellationTokenSource cancelCurrentRecalculateSource; 41 42 private readonly List<IRegressionSolution> solutions; 43 private readonly Dictionary<IRegressionSolution, Series> seriesCache; 44 private readonly Dictionary<IRegressionSolution, Series> ciSeriesCache; 45 46 #region Properties 42 47 public bool ShowLegend { 43 48 get { return chart.Legends[0].Enabled; } … … 60 65 public int XAxisTicks { 61 66 get { return xAxisTicks; } 62 set { if (xAxisTicks != value) { xAxisTicks = value; UpdateChart(); } } 63 } 67 set { xAxisTicks = value; } 68 } 69 private double? fixedXAxisMin; 70 public double? FixedXAxisMin { 71 get { return fixedXAxisMin; } 72 set { 73 if ((value.HasValue && fixedXAxisMin.HasValue && !value.Value.IsAlmost(fixedXAxisMin.Value)) || (value.HasValue != fixedXAxisMin.HasValue)) { 74 fixedXAxisMin = value; 75 RecalculateInternalDataset(); 76 } 77 } 78 } 79 private double? fixedXAxisMax; 80 public double? FixedXAxisMax { 81 get { return fixedXAxisMax; } 82 set { 83 if ((value.HasValue && fixedXAxisMax.HasValue && !value.Value.IsAlmost(fixedXAxisMax.Value)) || (value.HasValue != fixedXAxisMax.HasValue)) { 84 fixedXAxisMax = value; 85 RecalculateInternalDataset(); 86 } 87 } 88 } 89 64 90 private int yAxisTicks = 5; 65 public int Y XAxisTicks {91 public int YAxisTicks { 66 92 get { return yAxisTicks; } 67 set { if (yAxisTicks != value) { yAxisTicks = value; UpdateChart(); } } 93 set { yAxisTicks = value; } 94 } 95 private double? fixedYAxisMin; 96 public double? FixedYAxisMin { 97 get { return fixedYAxisMin; } 98 set { 99 if ((value.HasValue && fixedYAxisMin.HasValue && !value.Value.IsAlmost(fixedYAxisMin.Value)) || (value.HasValue != fixedYAxisMin.HasValue)) { 100 fixedYAxisMin = value; 101 } 102 } 103 } 104 private double? fixedYAxisMax; 105 public double? FixedYAxisMax { 106 get { return fixedYAxisMax; } 107 set { 108 if ((value.HasValue && fixedYAxisMax.HasValue && !value.Value.IsAlmost(fixedYAxisMax.Value)) || (value.HasValue != fixedYAxisMax.HasValue)) { 109 fixedYAxisMax = value; 110 } 111 } 68 112 } 69 113 … … 71 115 public double TrainingMin { 72 116 get { return trainingMin; } 73 set { if (!value.IsAlmost(trainingMin)) { trainingMin = value; UpdateChart(); }}117 set { trainingMin = value; } 74 118 } 75 119 private double trainingMax = double.MaxValue; 76 120 public double TrainingMax { 77 121 get { return trainingMax; } 78 set { if (!value.IsAlmost(trainingMax)) { trainingMax = value; UpdateChart(); }}122 set { trainingMax = value; } 79 123 } 80 124 … … 82 126 public int DrawingSteps { 83 127 get { return drawingSteps; } 84 set { if (value != drawingSteps) { drawingSteps = value; UpdateChart(); } } 128 set { 129 if (value != drawingSteps) { 130 drawingSteps = value; 131 RecalculateInternalDataset(); 132 ResizeAllSeriesData(); 133 } 134 } 85 135 } 86 136 … … 95 145 freeVariable = value; 96 146 RecalculateInternalDataset(); 97 UpdateChart(); 98 } 99 } 100 101 private readonly List<IRegressionSolution> solutions = new List<IRegressionSolution>(); 102 public IEnumerable<IRegressionSolution> Solutions { 103 get { return solutions; } 147 } 104 148 } 105 149 … … 107 151 get { return (VerticalLineAnnotation)chart.Annotations.SingleOrDefault(x => x is VerticalLineAnnotation); } 108 152 } 153 #endregion 109 154 110 155 public GradientChart() { 111 156 InitializeComponent(); 157 158 solutions = new List<IRegressionSolution>(); 159 seriesCache = new Dictionary<IRegressionSolution, Series>(); 160 ciSeriesCache = new Dictionary<IRegressionSolution, Series>(); 112 161 113 162 // Configure axis … … 121 170 chart.ChartAreas[0].CursorY.Interval = 0; 122 171 123 Disposed +=GradientChart_Disposed; 124 } 125 172 Disposed += GradientChart_Disposed; 173 } 126 174 private void GradientChart_Disposed(object sender, EventArgs e) { 127 if (cancelCurrentRefresh != null) { 128 if (cancelCurrentRefresh.IsCancellationRequested) 129 cancelCurrentRefresh.Cancel(); 130 cancelCurrentRefresh.Dispose(); 131 } 132 } 133 134 public void Configure(IEnumerable<IRegressionSolution> solutions, ModifiableDataset sharedFixedVariables, string freeVariable, int drawingSteps) { 175 if (cancelCurrentRecalculateSource != null) { 176 if (cancelCurrentRecalculateSource.IsCancellationRequested) 177 cancelCurrentRecalculateSource.Cancel(); 178 } 179 } 180 181 public void Configure(IEnumerable<IRegressionSolution> solutions, ModifiableDataset sharedFixedVariables, string freeVariable, int drawingSteps, bool initializeAxisRanges = true) { 135 182 if (!SolutionsCompatible(solutions)) 136 183 throw new ArgumentException("Solutions are not compatible with the problem data."); 184 this.freeVariable = freeVariable; 185 this.drawingSteps = drawingSteps; 186 137 187 this.solutions.Clear(); 138 188 this.solutions.AddRange(solutions); 139 this.freeVariable = freeVariable;140 this.drawingSteps = drawingSteps;141 189 142 190 // add an event such that whenever a value is changed in the shared dataset, … … 147 195 this.sharedFixedVariables.ItemChanged += sharedFixedVariables_ItemChanged; 148 196 149 RecalculateTrainingLimits( );197 RecalculateTrainingLimits(initializeAxisRanges); 150 198 RecalculateInternalDataset(); 151 } 152 153 private void sharedFixedVariables_ItemChanged(object o, EventArgs<int, int> e) { 154 if (o != sharedFixedVariables) return; 155 var variables = sharedFixedVariables.DoubleVariables.ToList(); 156 var rowIndex = e.Value; 157 var columnIndex = e.Value2; 158 159 var variableName = variables[columnIndex]; 160 if (variableName == FreeVariable) return; 161 var v = sharedFixedVariables.GetDoubleValue(variableName, rowIndex); 162 var values = new List<double>(Enumerable.Repeat(v, DrawingSteps)); 163 internalDataset.ReplaceVariable(variableName, values); 199 200 chart.Series.Clear(); 201 seriesCache.Clear(); 202 ciSeriesCache.Clear(); 203 foreach (var solution in this.solutions) { 204 var series = CreateSeries(solution); 205 seriesCache.Add(solution, series.Item1); 206 if (series.Item2 != null) 207 ciSeriesCache.Add(solution, series.Item2); 208 } 209 210 ResizeAllSeriesData(); 211 OrderAndColorSeries(); 212 } 213 214 public async Task RecalculateAsync() { 215 if (IsDisposed 216 || sharedFixedVariables == null || !solutions.Any() || string.IsNullOrEmpty(freeVariable) 217 || trainingMin.IsAlmost(trainingMax) || trainingMin > trainingMax || drawingSteps == 0) 218 return; 219 220 statusLabel.Visible = true; 221 Update(); // immediately show label 222 223 // cancel previous recalculate call 224 if (cancelCurrentRecalculateSource != null) 225 cancelCurrentRecalculateSource.Cancel(); 226 cancelCurrentRecalculateSource = new CancellationTokenSource(); 227 228 // Set cursor and x-axis 229 var defaultValue = sharedFixedVariables.GetDoubleValue(freeVariable, 0); 230 VerticalLineAnnotation.X = defaultValue; 231 chart.ChartAreas[0].AxisX.Title = FreeVariable + " : " + defaultValue.ToString("N3", CultureInfo.CurrentCulture); 232 SetupAxis(chart.ChartAreas[0].AxisX, trainingMin, trainingMax, XAxisTicks, fixedXAxisMin, fixedXAxisMax); 233 234 // Update series 235 var cancellationToken = cancelCurrentRecalculateSource.Token; 236 try { 237 await UpdateSeriesData(cancellationToken); 238 chart.Update(); 239 240 // Set y-axis 241 double ymin = 0, ymax = 0; 242 foreach (var vs in chart.Series.SelectMany(series => series.Points.Select(s => s.YValues))) { 243 for (int i = 0; i < vs.Length; i++) { 244 var v = vs[i]; 245 if (ymin > v) ymin = v; 246 if (ymax < v) ymax = v; 247 } 248 } 249 SetupAxis(chart.ChartAreas[0].AxisY, ymin, ymax, YAxisTicks, FixedYAxisMin, FixedYAxisMax); 250 chart.ChartAreas[0].RecalculateAxesScale(); 251 252 UpdateOutOfTrainingRangeStripLines(); 253 254 statusLabel.Visible = false; 255 Update(); // immediately show 256 } 257 catch (OperationCanceledException) { } 258 catch (AggregateException ae) { 259 if (!ae.InnerExceptions.Any(e => e is OperationCanceledException)) 260 throw; 261 } 262 } 263 264 private static void SetupAxis(Axis axis, double minValue, double maxValue, int ticks, double? fixedAxisMin, double? fixedAxisMax) { 265 double axisMin, axisMax, axisInterval; 266 ChartUtil.CalculateAxisInterval(minValue, maxValue, ticks, out axisMin, out axisMax, out axisInterval); 267 axis.Minimum = fixedAxisMin ?? axisMin; 268 axis.Maximum = fixedAxisMax ?? axisMax; 269 axis.Interval = (axisMax - axisMin) / ticks; 270 } 271 272 private void RecalculateTrainingLimits(bool initializeAxisRanges) { 273 trainingMin = solutions.Select(s => s.ProblemData.Dataset.GetDoubleValues(freeVariable, s.ProblemData.TrainingIndices).Min()).Max(); 274 trainingMax = solutions.Select(s => s.ProblemData.Dataset.GetDoubleValues(freeVariable, s.ProblemData.TrainingIndices).Max()).Min(); 275 276 if (initializeAxisRanges) { 277 double xmin, xmax, xinterval; 278 ChartUtil.CalculateAxisInterval(trainingMin, trainingMax, XAxisTicks, out xmin, out xmax, out xinterval); 279 FixedXAxisMin = xmin; 280 FixedXAxisMax = xmax; 281 } 164 282 } 165 283 … … 168 286 double xmin, xmax, xinterval; 169 287 ChartUtil.CalculateAxisInterval(trainingMin, trainingMax, XAxisTicks, out xmin, out xmax, out xinterval); 288 289 if (FixedXAxisMin.HasValue) xmin = FixedXAxisMin.Value; 290 if (FixedXAxisMax.HasValue) xmax = FixedXAxisMax.Value; 170 291 double step = (xmax - xmin) / drawingSteps; 171 292 … … 183 304 } 184 305 185 private void RecalculateTrainingLimits() { 186 trainingMin = solutions.Select(s => s.ProblemData.Dataset.GetDoubleValues(freeVariable, s.ProblemData.TrainingIndices).Min()).Max(); 187 trainingMax = solutions.Select(s => s.ProblemData.Dataset.GetDoubleValues(freeVariable, s.ProblemData.TrainingIndices).Max()).Min(); 188 } 189 190 public async void UpdateChart() { 191 // throw exceptions? 192 if (sharedFixedVariables == null || solutions == null || !solutions.Any()) 193 return; 194 if (trainingMin.IsAlmost(trainingMax) || trainingMin > trainingMax || drawingSteps == 0) 195 return; 196 if (IsDisposed) 197 return; 198 199 statusLabel.Visible = true; 200 201 if (cancelCurrentRefresh != null && !cancelCurrentRefresh.IsCancellationRequested) 202 cancelCurrentRefresh.Cancel(); 203 cancelCurrentRefresh = new CancellationTokenSource(); 204 205 // Set cursor 206 var defaultValue = sharedFixedVariables.GetDoubleValue(freeVariable, 0); 207 VerticalLineAnnotation.X = defaultValue; 208 209 // Calculate X-axis interval 210 double axisMin, axisMax, axisInterval; 211 ChartUtil.CalculateAxisInterval(trainingMin, trainingMax, XAxisTicks, out axisMin, out axisMax, out axisInterval); 212 var axis = chart.ChartAreas[0].AxisX; 213 axis.Minimum = axisMin; 214 axis.Maximum = axisMax; 215 axis.Interval = axisInterval; 216 217 var cancellationToken = cancelCurrentRefresh.Token; 218 // Create series <mean, conf. interval> 219 var seriesDict = new Dictionary<Series, Series>(); 220 for (int i = 0; i < solutions.Count; i++) { 221 var solution = solutions[i]; 222 try { 223 var series = await CreateSeriesAsync(solution, cancellationToken); 224 if (cancellationToken.IsCancellationRequested) 225 return; 226 series.Item1.Tag = i; // for sorting 227 var meanSeries = series.Item1; 228 var confidenceIntervalSeries = series.Item2; 229 meanSeries.Name = solution.ProblemData.TargetVariable + " " + i; 230 seriesDict.Add(meanSeries, confidenceIntervalSeries); 231 if (confidenceIntervalSeries != null) 232 confidenceIntervalSeries.Name = "95% Conf. Interval " + meanSeries.Name; 233 } 234 catch (TaskCanceledException) { 235 return; 236 } 237 } 238 306 private Tuple<Series, Series> CreateSeries(IRegressionSolution solution) { 307 var series = new Series { 308 ChartType = SeriesChartType.Line, 309 Name = solution.ProblemData.TargetVariable + " " + solutions.IndexOf(solution) 310 }; 311 series.LegendText = series.Name; 312 313 var confidenceBoundSolution = solution as IConfidenceBoundRegressionSolution; 314 Series confidenceIntervalSeries = null; 315 if (confidenceBoundSolution != null) { 316 confidenceIntervalSeries = new Series { 317 ChartType = SeriesChartType.Range, 318 YValuesPerPoint = 2, 319 Name = "95% Conf. Interval " + series.Name, 320 IsVisibleInLegend = false 321 }; 322 } 323 return Tuple.Create(series, confidenceIntervalSeries); 324 } 325 326 private void OrderAndColorSeries() { 239 327 chart.SuspendRepaint(); 328 240 329 chart.Series.Clear(); 241 330 // Add mean series for applying palette colors 242 foreach (var s eries in seriesDict.Keys.OrderBy(s => (int)s.Tag)) {243 series.LegendText = series.Name;244 chart.Series.Add(series);245 } 331 foreach (var solution in solutions) { 332 chart.Series.Add(seriesCache[solution]); 333 } 334 246 335 chart.Palette = ChartColorPalette.BrightPastel; 247 336 chart.ApplyPaletteColors(); 248 337 chart.Palette = ChartColorPalette.None; 249 338 250 foreach (var series in seriesDict.OrderBy(s => (int)s.Key.Tag)) { 251 if (series.Value == null) continue; 252 int idx = chart.Series.IndexOf(series.Key); 253 series.Value.Color = Color.FromArgb(40, series.Key.Color); 254 series.Value.IsVisibleInLegend = false; 255 chart.Series.Insert(idx, series.Value); 256 } 339 // Add confidence interval series before its coresponding series for correct z index 340 foreach (var solution in solutions) { 341 Series ciSeries; 342 if (ciSeriesCache.TryGetValue(solution, out ciSeries)) { 343 var series = seriesCache[solution]; 344 ciSeries.Color = Color.FromArgb(40, series.Color); 345 int idx = chart.Series.IndexOf(seriesCache[solution]); 346 chart.Series.Insert(idx, ciSeries); 347 } 348 } 349 257 350 chart.ResumeRepaint(true); 258 259 260 ////calculate Y-axis interval 261 //double ymin = 0, ymax = 0; 262 //foreach (var vs in chart.Series.SelectMany(series => series.Points.Select(s => s.YValues))) { 263 // for (int index = 0; index < vs.Length; index++) { 264 // var v = vs[index]; 265 // if (ymin > v) ymin = v; 266 // if (ymax < v) ymax = v; 267 // } 268 //} 269 //ChartUtil.CalculateAxisInterval(ymin, ymax, YXAxisTicks, out axisMin, out axisMax, out axisInterval); 270 //axis = chart.ChartAreas[0].AxisY; 271 //axis.Minimum = axisMin; 272 //axis.Maximum = axisMax; 273 //axis.Interval = axisInterval; 274 //chart.ChartAreas[0].RecalculateAxesScale(); 275 276 // set axis title 277 chart.ChartAreas[0].AxisX.Title = FreeVariable + " : " + defaultValue.ToString("N3", CultureInfo.CurrentCulture); 278 279 UpdateStripLines(); 280 281 statusLabel.Visible = false; 282 } 283 284 private Task<Tuple<Series, Series>> CreateSeriesAsync(IRegressionSolution solution, CancellationToken cancellationToken) { 351 } 352 353 private Task UpdateSeriesData(CancellationToken cancellationToken) { 285 354 return Task.Run(() => { 286 var xvalues = internalDataset.GetDoubleValues(FreeVariable).ToList(); 287 var yvalues = solution.Model.GetEstimatedValues(internalDataset, Enumerable.Range(0, internalDataset.Rows)).ToList(); 288 289 var series = new Series { ChartType = SeriesChartType.Line }; 290 series.Points.DataBindXY(xvalues, yvalues); 291 292 var confidenceBoundSolution = solution as IConfidenceBoundRegressionSolution; 293 Series confidenceIntervalSeries = null; 294 if (confidenceBoundSolution != null) { 295 var variances = confidenceBoundSolution.Model.GetEstimatedVariances(internalDataset, Enumerable.Range(0, internalDataset.Rows)).ToList(); 296 297 var lower = yvalues.Zip(variances, (m, s2) => m - 1.96 * Math.Sqrt(s2)).ToList(); 298 var upper = yvalues.Zip(variances, (m, s2) => m + 1.96 * Math.Sqrt(s2)).ToList(); 299 300 confidenceIntervalSeries = new Series { ChartType = SeriesChartType.Range, YValuesPerPoint = 2 }; 301 confidenceIntervalSeries.Points.DataBindXY(xvalues, lower, upper); 302 } 303 return Tuple.Create(series, confidenceIntervalSeries); 355 Parallel.ForEach(solutions, new ParallelOptions { CancellationToken = cancellationToken }, solution => { 356 var xvalues = internalDataset.GetDoubleValues(FreeVariable).ToList(); 357 var yvalues = solution.Model.GetEstimatedValues(internalDataset, Enumerable.Range(0, internalDataset.Rows)).ToList(); 358 359 var series = seriesCache[solution]; 360 for (int i = 0; i < xvalues.Count; i++) 361 series.Points[i].SetValueXY(xvalues[i], yvalues[i]); 362 363 var confidenceBoundSolution = solution as IConfidenceBoundRegressionSolution; 364 if (confidenceBoundSolution != null) { 365 var confidenceIntervalSeries = ciSeriesCache[solution]; 366 367 cancellationToken.ThrowIfCancellationRequested(); 368 var variances = 369 confidenceBoundSolution.Model.GetEstimatedVariances(internalDataset, 370 Enumerable.Range(0, internalDataset.Rows)).ToList(); 371 for (int i = 0; i < xvalues.Count; i++) { 372 var lower = yvalues[i] - 1.96 * Math.Sqrt(variances[i]); 373 var upper = yvalues[i] + 1.96 * Math.Sqrt(variances[i]); 374 confidenceIntervalSeries.Points[i].SetValueXY(xvalues[i], lower, upper); 375 } 376 } 377 cancellationToken.ThrowIfCancellationRequested(); 378 }); 304 379 }, cancellationToken); 305 380 } 306 381 307 public void AddSolution(IRegressionSolution solution) { 382 private void ResizeAllSeriesData() { 383 var xvalues = internalDataset.GetDoubleValues(FreeVariable).ToList(); 384 foreach (var solution in solutions) 385 ResizeSeriesData(solution, xvalues); 386 } 387 private void ResizeSeriesData(IRegressionSolution solution, IList<double> xvalues = null) { 388 if (xvalues == null) 389 xvalues = internalDataset.GetDoubleValues(FreeVariable).ToList(); 390 391 var series = seriesCache[solution]; 392 series.Points.SuspendUpdates(); 393 for (int i = 0; i < xvalues.Count; i++) 394 series.Points.Add(new DataPoint(xvalues[i], 0.0)); 395 series.Points.ResumeUpdates(); 396 397 Series confidenceIntervalSeries; 398 if (ciSeriesCache.TryGetValue(solution, out confidenceIntervalSeries)) { 399 confidenceIntervalSeries.Points.SuspendUpdates(); 400 for (int i = 0; i < xvalues.Count; i++) 401 confidenceIntervalSeries.Points.Add(new DataPoint(xvalues[i], new[] { -1.0, 1.0 })); 402 confidenceIntervalSeries.Points.ResumeUpdates(); 403 } 404 } 405 406 public async Task AddSolutionAsync(IRegressionSolution solution) { 308 407 if (!SolutionsCompatible(solutions.Concat(new[] { solution }))) 309 408 throw new ArgumentException("The solution is not compatible with the problem data."); 310 if (solutions.Contains(solution)) return; 409 if (solutions.Contains(solution)) 410 return; 411 311 412 solutions.Add(solution); 312 RecalculateTrainingLimits(); 313 UpdateChart(); 314 } 315 public void RemoveSolution(IRegressionSolution solution) { 316 if (!solutions.Remove(solution)) return; 317 RecalculateTrainingLimits(); 318 UpdateChart(); 413 RecalculateTrainingLimits(true); 414 415 var series = CreateSeries(solution); 416 seriesCache.Add(solution, series.Item1); 417 if (series.Item2 != null) 418 ciSeriesCache.Add(solution, series.Item2); 419 420 ResizeSeriesData(solution); 421 OrderAndColorSeries(); 422 423 await RecalculateAsync(); 424 } 425 public async Task RemoveSolutionAsync(IRegressionSolution solution) { 426 if (!solutions.Remove(solution)) 427 return; 428 429 RecalculateTrainingLimits(true); 430 431 seriesCache.Remove(solution); 432 ciSeriesCache.Remove(solution); 433 434 await RecalculateAsync(); 319 435 } 320 436 … … 333 449 } 334 450 335 private void Update StripLines() {451 private void UpdateOutOfTrainingRangeStripLines() { 336 452 var axisX = chart.ChartAreas[0].AxisX; 337 453 var lowerStripLine = axisX.StripLines[0]; … … 345 461 } 346 462 347 #region events463 #region Events 348 464 public event EventHandler VariableValueChanged; 349 465 public void OnVariableValueChanged(object sender, EventArgs args) { … … 353 469 } 354 470 355 private void chart_AnnotationPositionChanged(object sender, EventArgs e) { 356 //var annotation = VerticalLineAnnotation; 357 //var x = annotation.X; 358 //sharedFixedVariables.SetVariableValue(x, FreeVariable, 0); 359 360 //chart.ChartAreas[0].AxisX.Title = FreeVariable + " : " + x.ToString("N3", CultureInfo.CurrentCulture); 361 //chart.Update(); 362 363 //OnVariableValueChanged(this, EventArgs.Empty); 364 } 365 471 private void sharedFixedVariables_ItemChanged(object o, EventArgs<int, int> e) { 472 if (o != sharedFixedVariables) return; 473 var variables = sharedFixedVariables.DoubleVariables.ToList(); 474 var rowIndex = e.Value; 475 var columnIndex = e.Value2; 476 477 var variableName = variables[columnIndex]; 478 if (variableName == FreeVariable) return; 479 var v = sharedFixedVariables.GetDoubleValue(variableName, rowIndex); 480 var values = new List<double>(Enumerable.Repeat(v, DrawingSteps)); 481 internalDataset.ReplaceVariable(variableName, values); 482 } 483 484 private double oldCurserPosition = double.NaN; 366 485 private void chart_AnnotationPositionChanging(object sender, AnnotationPositionChangingEventArgs e) { 486 if (oldCurserPosition.IsAlmost(e.NewLocationX)) 487 return; 488 oldCurserPosition = e.NewLocationX; 489 367 490 var step = (trainingMax - trainingMin) / drawingSteps; 368 491 e.NewLocationX = step * (long)Math.Round(e.NewLocationX / step); … … 384 507 385 508 private void chart_MouseMove(object sender, MouseEventArgs e) { 386 chart.Cursor = chart.HitTest(e.X, e.Y).ChartElementType == ChartElementType.Annotation ? Cursors.VSplit : Cursors.Default; 509 bool hitCursor = chart.HitTest(e.X, e.Y).ChartElementType == ChartElementType.Annotation; 510 chart.Cursor = hitCursor ? Cursors.VSplit : Cursors.Default; 387 511 } 388 512 … … 402 526 } 403 527 404 private void GradientChart_DragDrop(object sender, DragEventArgs e) {528 private void chart_DragDrop(object sender, DragEventArgs e) { 405 529 var data = e.Data.GetData(HeuristicLab.Common.Constants.DragDropDataFormat); 406 530 if (data != null) { 407 531 var solution = data as IRegressionSolution; 408 if (! Solutions.Contains(solution))409 AddSolution (solution);410 } 411 } 412 private void GradientChart_DragEnter(object sender, DragEventArgs e) {532 if (!solutions.Contains(solution)) 533 AddSolutionAsync(solution); 534 } 535 } 536 private void chart_DragEnter(object sender, DragEventArgs e) { 413 537 if (!e.Data.GetDataPresent(HeuristicLab.Common.Constants.DragDropDataFormat)) return; 414 538 e.Effect = DragDropEffects.None; -
branches/HeuristicLab.RegressionSolutionGradientView/HeuristicLab.Problems.DataAnalysis.Views/3.4/RegressionSolutionGradientView.Designer.cs
r13837 r13842 89 89 this.gradientChart.TrainingMin = -1.7976931348623157E+308D; 90 90 this.gradientChart.XAxisTicks = 10; 91 this.gradientChart.Y XAxisTicks = 5;91 this.gradientChart.YAxisTicks = 5; 92 92 // 93 93 // configurationGroupBox -
branches/HeuristicLab.RegressionSolutionGradientView/HeuristicLab.Problems.DataAnalysis.Views/3.4/RegressionSolutionGradientView.cs
r13840 r13842 72 72 } 73 73 74 private void UpdateConfigurationControls() {74 private async void UpdateConfigurationControls() { 75 75 variableNames.Clear(); 76 76 trackbars.Clear(); … … 87 87 sharedFixedVariables = new ModifiableDataset(variableNames, newTrackbars.Select(tb => new List<double>(1) { (double)tb.Value })); 88 88 gradientChart.Configure(new[] { Content }, sharedFixedVariables, variableNames.First(), DrawingSteps); 89 gradientChart.UpdateChart();89 await gradientChart.RecalculateAsync(); 90 90 91 // Add to table and observable lists 91 // Add to table and observable lists 92 92 tableLayoutPanel.RowCount = variableNames.Count; 93 93 while (tableLayoutPanel.RowStyles.Count < variableNames.Count) … … 143 143 tb.Checked = false; 144 144 gradientChart.FreeVariable = variableNames[trackbars.IndexOf(trackBar)]; 145 gradientChart.RecalculateAsync(); 145 146 } 146 147 147 148 private void trackbar_LimitsChanged(object sender, EventArgs e) { 148 // Todo adapt bounds 149 var trackBar = sender as DensityTrackbar; 150 if (trackBar == null || !trackBar.Checked) return; 151 gradientChart.FixedXAxisMin = trackBar.Limits.Lower; 152 gradientChart.FixedXAxisMax = trackBar.Limits.Upper; 153 gradientChart.RecalculateAsync(); 149 154 } 150 155 … … 153 158 if (trackBar == null) return; 154 159 sharedFixedVariables.SetVariableValue((double)trackBar.Value, variableNames[trackbars.IndexOf(trackBar)], 0); 155 gradientChart. UpdateChart();160 gradientChart.RecalculateAsync(); 156 161 } 157 162 … … 182 187 } 183 188 #endregion 184 185 186 189 } 187 190 -
branches/HeuristicLab.RegressionSolutionGradientView/HeuristicLab.Problems.DataAnalysis.Views/3.4/RegressionSolutionTargetResponseGradientView.cs
r13840 r13842 76 76 foreach (var chart in gradientChartTableLayout.Controls.Cast<GradientChart>()) { 77 77 if (chart == (GradientChart)o) continue; 78 chart. UpdateChart();78 chart.RecalculateAsync(); 79 79 } 80 80 }; … … 99 99 } 100 100 101 private void variableListView_ItemChecked(object sender, ItemCheckedEventArgs e) {101 private async void variableListView_ItemChecked(object sender, ItemCheckedEventArgs e) { 102 102 if (charts == null) return; 103 103 var item = e.Item; … … 111 111 if (item.Checked) { 112 112 tl.Controls.Add(chart); 113 chart.UpdateChart();113 await chart.RecalculateAsync(); 114 114 } else { 115 115 tl.Controls.Remove(chart);
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