Changeset 14029 for branches/crossvalidation-2434/HeuristicLab.Algorithms.DataAnalysis.Views/3.4/GaussianProcessRegressionSolutionLineChartView.cs
- Timestamp:
- 07/08/16 14:40:02 (8 years ago)
- Location:
- branches/crossvalidation-2434
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- 3 edited
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/stable/HeuristicLab.Algorithms.DataAnalysis.Views merged eligible /trunk/sources/HeuristicLab.Algorithms.DataAnalysis.Views merged eligible /branches/1721-RandomForestPersistence/HeuristicLab.Algorithms.DataAnalysis.Views 10321-10322 /branches/Algorithms.GradientDescent/HeuristicLab.Algorithms.DataAnalysis.Views 5516-5520 /branches/Benchmarking/sources/HeuristicLab.Algorithms.DataAnalysis.Views 6917-7005 /branches/ClassificationModelComparison/HeuristicLab.Algorithms.DataAnalysis.Views 9117-13099 /branches/CloningRefactoring/HeuristicLab.Algorithms.DataAnalysis.Views 4656-4721 /branches/CodeEditor/HeuristicLab.Algorithms.DataAnalysis.Views 11700-11806 /branches/DataAnalysis Refactoring/HeuristicLab.Algorithms.DataAnalysis.Views 5471-5808 /branches/DataAnalysis SolutionEnsembles/HeuristicLab.Algorithms.DataAnalysis.Views 5815-6180 /branches/DataAnalysis/HeuristicLab.Algorithms.DataAnalysis.Views 4458-4459,4462,4464 /branches/DataPreprocessing/HeuristicLab.Algorithms.DataAnalysis.Views 10085-11101 /branches/GP.Grammar.Editor/HeuristicLab.Algorithms.DataAnalysis.Views 6284-6795 /branches/GP.Symbols (TimeLag, Diff, Integral)/HeuristicLab.Algorithms.DataAnalysis.Views 5060 /branches/HLScript/HeuristicLab.Algorithms.DataAnalysis.Views 10331-10358 /branches/HeuristicLab.DatasetRefactor/sources/HeuristicLab.Algorithms.DataAnalysis.Views 11570-12508 /branches/HeuristicLab.Problems.DataAnalysis.Trading/HeuristicLab.Algorithms.DataAnalysis.Views 6123-9799 /branches/HeuristicLab.Problems.Orienteering/HeuristicLab.Algorithms.DataAnalysis.Views 11130-12721 /branches/HiveStatistics/sources/HeuristicLab.Algorithms.DataAnalysis.Views 12440-12877 /branches/LogResidualEvaluator/HeuristicLab.Algorithms.DataAnalysis.Views 10202-10483 /branches/NET40/sources/HeuristicLab.Algorithms.DataAnalysis.Views 5138-5162 /branches/NSGA-II Changes/HeuristicLab.Algorithms.DataAnalysis.Views 12033-12122 /branches/ParallelEngine/HeuristicLab.Algorithms.DataAnalysis.Views 5175-5192 /branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Algorithms.DataAnalysis.Views 7568-7810 /branches/QAPAlgorithms/HeuristicLab.Algorithms.DataAnalysis.Views 6350-6627 /branches/Restructure trunk solution/HeuristicLab.Algorithms.DataAnalysis.Views 6828 /branches/RuntimeOptimizer/HeuristicLab.Algorithms.DataAnalysis.Views 8943-9078 /branches/ScatterSearch (trunk integration)/HeuristicLab.Algorithms.DataAnalysis.Views 7787-8333 /branches/SlaveShutdown/HeuristicLab.Algorithms.DataAnalysis.Views 8944-8956 /branches/SpectralKernelForGaussianProcesses/HeuristicLab.Algorithms.DataAnalysis.Views 10204-10479 /branches/SuccessProgressAnalysis/HeuristicLab.Algorithms.DataAnalysis.Views 5370-5682 /branches/Trunk/HeuristicLab.Algorithms.DataAnalysis.Views 6829-6865 /branches/UnloadJobs/HeuristicLab.Algorithms.DataAnalysis.Views 9168-9215 /branches/VNS/HeuristicLab.Algorithms.DataAnalysis.Views 5594-5752 /branches/histogram/HeuristicLab.Algorithms.DataAnalysis.Views 5959-6341
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branches/crossvalidation-2434/HeuristicLab.Algorithms.DataAnalysis.Views/3.4/GaussianProcessRegressionSolutionLineChartView.cs
r12012 r14029 70 70 var mean = Content.EstimatedTrainingValues.ToArray(); 71 71 var s2 = Content.EstimatedTrainingVariance.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();72 var lower = mean.Zip(s2, GetLowerConfBound).ToArray(); 73 var upper = mean.Zip(s2, GetUpperConfBound).ToArray(); 74 74 this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TrainingIndices.ToArray(), lower, upper); 75 75 this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME]); … … 83 83 mean = Content.EstimatedTestValues.ToArray(); 84 84 s2 = Content.EstimatedTestVariance.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();85 lower = mean.Zip(s2, GetLowerConfBound).ToArray(); 86 upper = mean.Zip(s2, GetUpperConfBound).ToArray(); 87 87 this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TestIndices.ToArray(), lower, upper); 88 88 this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME]); … … 93 93 mean = Content.EstimatedValues.ToArray(); 94 94 s2 = Content.EstimatedVariance.ToArray(); 95 lower = mean.Zip(s2, (m, s) => m - 1.96 * Math.Sqrt(s)).ToArray();96 upper = mean.Zip(s2, (m, s) => m + 1.96 * Math.Sqrt(s)).ToArray();95 lower = mean.Zip(s2, GetLowerConfBound).ToArray(); 96 upper = mean.Zip(s2, GetUpperConfBound).ToArray(); 97 97 List<double> allLower = allIndices.Select(index => lower[index]).ToList(); 98 98 List<double> allUpper = allIndices.Select(index => upper[index]).ToList(); … … 265 265 mean = Content.EstimatedValues.ToArray(); 266 266 s2 = Content.EstimatedVariance.ToArray(); 267 lower = mean.Zip(s2, (m, s) => m - 1.96 * Math.Sqrt(s)).ToArray();268 upper = mean.Zip(s2, (m, s) => m + 1.96 * Math.Sqrt(s)).ToArray();267 lower = mean.Zip(s2, GetLowerConfBound).ToArray(); 268 upper = mean.Zip(s2, GetUpperConfBound).ToArray(); 269 269 lower = indices.Select(index => lower[index]).ToArray(); 270 270 upper = indices.Select(index => upper[index]).ToArray(); … … 274 274 mean = Content.EstimatedTrainingValues.ToArray(); 275 275 s2 = Content.EstimatedTrainingVariance.ToArray(); 276 lower = mean.Zip(s2, (m, s) => m - 1.96 * Math.Sqrt(s)).ToArray();277 upper = mean.Zip(s2, (m, s) => m + 1.96 * Math.Sqrt(s)).ToArray();276 lower = mean.Zip(s2, GetLowerConfBound).ToArray(); 277 upper = mean.Zip(s2, GetUpperConfBound).ToArray(); 278 278 break; 279 279 case ESTIMATEDVALUES_TEST_SERIES_NAME: … … 281 281 mean = Content.EstimatedTestValues.ToArray(); 282 282 s2 = Content.EstimatedTestVariance.ToArray(); 283 lower = mean.Zip(s2, (m, s) => m - 1.96 * Math.Sqrt(s)).ToArray();284 upper = mean.Zip(s2, (m, s) => m + 1.96 * Math.Sqrt(s)).ToArray();283 lower = mean.Zip(s2, GetLowerConfBound).ToArray(); 284 upper = mean.Zip(s2, GetUpperConfBound).ToArray(); 285 285 break; 286 286 } … … 295 295 } 296 296 297 private double GetLowerConfBound(double m, double s) { 298 return m - 1.96 * Math.Sqrt(s); 299 } 300 301 302 private double GetUpperConfBound(double m, double s) { 303 return m + 1.96 * Math.Sqrt(s); 304 } 305 297 306 // workaround as per http://stackoverflow.com/questions/5744930/datapointcollection-clear-performance 298 307 private static void ClearPointsQuick(DataPointCollection points) {
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