Changeset 8475 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis.Views
- Timestamp:
- 08/11/12 14:45:15 (12 years ago)
- File:
-
- 1 edited
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trunk/sources/HeuristicLab.Algorithms.DataAnalysis.Views/3.4/GaussianProcessRegressionSolutionLineChartView.cs
r8473 r8475 63 63 this.chart.ChartAreas[0].AxisX.Maximum = Content.ProblemData.Dataset.Rows - 1; 64 64 65 this.chart.Series.Add(TARGETVARIABLE_SERIES_NAME);66 this.chart.Series[TARGETVARIABLE_SERIES_NAME].LegendText = Content.ProblemData.TargetVariable;67 this.chart.Series[TARGETVARIABLE_SERIES_NAME].ChartType = SeriesChartType.FastLine;68 this.chart.Series[TARGETVARIABLE_SERIES_NAME].Points.DataBindXY(Enumerable.Range(0, Content.ProblemData.Dataset.Rows).ToArray(),69 Content.ProblemData.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToArray());70 65 // training series 71 66 this.chart.Series.Add(ESTIMATEDVALUES_TRAINING_SERIES_NAME); … … 75 70 var mean = Content.EstimatedTrainingValues.ToArray(); 76 71 var s2 = Content.EstimatedTrainingVariance.ToArray(); 77 var lower = mean.Zip(s2, (m, s) => m - s).ToArray();78 var upper = mean.Zip(s2, (m, s) => m + s).ToArray();72 var lower = mean.Zip(s2, (m, s) => m - 1.96 * Math.Sqrt(s)).ToArray(); 73 var upper = mean.Zip(s2, (m, s) => m + 1.96 * Math.Sqrt(s)).ToArray(); 79 74 this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TrainingIndices.ToArray(), lower, upper); 80 75 this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME]); 81 76 this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Tag = Content; 77 82 78 // test series 83 79 this.chart.Series.Add(ESTIMATEDVALUES_TEST_SERIES_NAME); … … 87 83 mean = Content.EstimatedTestValues.ToArray(); 88 84 s2 = Content.EstimatedTestVariance.ToArray(); 89 lower = mean.Zip(s2, (m, s) => m - s).ToArray();90 upper = mean.Zip(s2, (m, s) => m + s).ToArray();85 lower = mean.Zip(s2, (m, s) => m - 1.96 * Math.Sqrt(s)).ToArray(); 86 upper = mean.Zip(s2, (m, s) => m + 1.96 * Math.Sqrt(s)).ToArray(); 91 87 this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TestIndices.ToArray(), lower, upper); 92 88 this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME]); 93 89 this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Tag = Content; 90 94 91 // series of remaining points 95 92 int[] allIndices = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndices).Except(Content.ProblemData.TestIndices).ToArray(); … … 102 99 this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME]); 103 100 this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].Tag = Content; 101 102 // target 103 this.chart.Series.Add(TARGETVARIABLE_SERIES_NAME); 104 this.chart.Series[TARGETVARIABLE_SERIES_NAME].LegendText = Content.ProblemData.TargetVariable; 105 this.chart.Series[TARGETVARIABLE_SERIES_NAME].ChartType = SeriesChartType.FastLine; 106 this.chart.Series[TARGETVARIABLE_SERIES_NAME].Points.DataBindXY(Enumerable.Range(0, Content.ProblemData.Dataset.Rows).ToArray(), 107 Content.ProblemData.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToArray()); 108 104 109 this.ToggleSeriesData(this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME]); 105 110 … … 243 248 mean = Content.EstimatedValues.ToArray(); 244 249 s2 = Content.EstimatedVariance.ToArray(); 245 lower = mean.Zip(s2, (m, s) => m - s).ToArray();246 upper = mean.Zip(s2, (m, s) => m + s).ToArray();250 lower = mean.Zip(s2, (m, s) => m - 1.96 * Math.Sqrt(s)).ToArray(); 251 upper = mean.Zip(s2, (m, s) => m + 1.96 * Math.Sqrt(s)).ToArray(); 247 252 lower = indices.Select(index => lower[index]).ToArray(); 248 253 upper = indices.Select(index => upper[index]).ToArray(); … … 252 257 mean = Content.EstimatedTrainingValues.ToArray(); 253 258 s2 = Content.EstimatedTrainingVariance.ToArray(); 254 lower = mean.Zip(s2, (m, s) => m - s).ToArray();255 upper = mean.Zip(s2, (m, s) => m + s).ToArray();259 lower = mean.Zip(s2, (m, s) => m - 1.96 * Math.Sqrt(s)).ToArray(); 260 upper = mean.Zip(s2, (m, s) => m + 1.96 * Math.Sqrt(s)).ToArray(); 256 261 break; 257 262 case ESTIMATEDVALUES_TEST_SERIES_NAME:
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