Changeset 16692 for branches/2521_ProblemRefactoring/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovarianceProduct.cs
- Timestamp:
- 03/18/19 17:24:30 (5 years ago)
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- branches/2521_ProblemRefactoring
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- 4 edited
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branches/2521_ProblemRefactoring
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branches/2521_ProblemRefactoring/HeuristicLab.Algorithms.DataAnalysis
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branches/2521_ProblemRefactoring/HeuristicLab.Algorithms.DataAnalysis/3.4
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/stable/HeuristicLab.Algorithms.DataAnalysis/3.4 merged eligible /branches/1721-RandomForestPersistence/HeuristicLab.Algorithms.DataAnalysis/3.4 10321-10322 /branches/Async/HeuristicLab.Algorithms.DataAnalysis/3.4 13329-15286 /branches/Benchmarking/sources/HeuristicLab.Algorithms.DataAnalysis/3.4 6917-7005 /branches/ClassificationModelComparison/HeuristicLab.Algorithms.DataAnalysis/3.4 9070-13099 /branches/CloningRefactoring/HeuristicLab.Algorithms.DataAnalysis/3.4 4656-4721 /branches/DataAnalysis Refactoring/HeuristicLab.Algorithms.DataAnalysis/3.4 5471-5808 /branches/DataAnalysis SolutionEnsembles/HeuristicLab.Algorithms.DataAnalysis/3.4 5815-6180 /branches/DataAnalysis/HeuristicLab.Algorithms.DataAnalysis/3.4 4458-4459,4462,4464 /branches/DataPreprocessing/HeuristicLab.Algorithms.DataAnalysis/3.4 10085-11101 /branches/GP.Grammar.Editor/HeuristicLab.Algorithms.DataAnalysis/3.4 6284-6795 /branches/GP.Symbols (TimeLag, Diff, Integral)/HeuristicLab.Algorithms.DataAnalysis/3.4 5060 /branches/HeuristicLab.DatasetRefactor/sources/HeuristicLab.Algorithms.DataAnalysis/3.4 11570-12508 /branches/HeuristicLab.Problems.Orienteering/HeuristicLab.Algorithms.DataAnalysis/3.4 11130-12721 /branches/HeuristicLab.RegressionSolutionGradientView/HeuristicLab.Algorithms.DataAnalysis/3.4 13819-14091 /branches/HeuristicLab.TimeSeries/HeuristicLab.Algorithms.DataAnalysis/3.4 8116-8789 /branches/LogResidualEvaluator/HeuristicLab.Algorithms.DataAnalysis/3.4 10202-10483 /branches/NET40/sources/HeuristicLab.Algorithms.DataAnalysis/3.4 5138-5162 /branches/ParallelEngine/HeuristicLab.Algorithms.DataAnalysis/3.4 5175-5192 /branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Algorithms.DataAnalysis/3.4 7773-7810 /branches/QAPAlgorithms/HeuristicLab.Algorithms.DataAnalysis/3.4 6350-6627 /branches/Restructure trunk solution/HeuristicLab.Algorithms.DataAnalysis/3.4 6828 /branches/SpectralKernelForGaussianProcesses/HeuristicLab.Algorithms.DataAnalysis/3.4 10204-10479 /branches/SuccessProgressAnalysis/HeuristicLab.Algorithms.DataAnalysis/3.4 5370-5682 /branches/Trunk/HeuristicLab.Algorithms.DataAnalysis/3.4 6829-6865 /branches/VNS/HeuristicLab.Algorithms.DataAnalysis/3.4 5594-5752 /branches/Weighted TSNE/3.4 15451-15531 /branches/histogram/HeuristicLab.Algorithms.DataAnalysis/3.4 5959-6341 /branches/symbreg-factors-2650/HeuristicLab.Algorithms.DataAnalysis/3.4 14232-14825 /trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4 13331-15681
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branches/2521_ProblemRefactoring/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovarianceProduct.cs
r12012 r16692 1 1 #region License Information 2 2 /* HeuristicLab 3 * Copyright (C) 2002-201 5Heuristic and Evolutionary Algorithms Laboratory (HEAL)3 * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL) 4 4 * 5 5 * This file is part of HeuristicLab. … … 23 23 using System.Collections.Generic; 24 24 using System.Linq; 25 using System.Linq.Expressions;26 25 using HeuristicLab.Common; 27 26 using HeuristicLab.Core; … … 76 75 } 77 76 78 public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, IEnumerable<int>columnIndices) {77 public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, int[] columnIndices) { 79 78 if (factors.Count == 0) throw new ArgumentException("at least one factor is necessary for the product covariance function."); 80 79 var functions = new List<ParameterizedCovarianceFunction>(); … … 93 92 } 94 93 95 public static I Enumerable<double> GetGradient(double[,] x, int i, int j, List<ParameterizedCovarianceFunction> factorFunctions) {94 public static IList<double> GetGradient(double[,] x, int i, int j, List<ParameterizedCovarianceFunction> factorFunctions) { 96 95 var covariances = factorFunctions.Select(f => f.Covariance(x, i, j)).ToArray(); 96 var gr = new List<double>(); 97 97 for (int ii = 0; ii < factorFunctions.Count; ii++) { 98 98 foreach (var g in factorFunctions[ii].CovarianceGradient(x, i, j)) { … … 100 100 for (int jj = 0; jj < covariances.Length; jj++) 101 101 if (ii != jj) res *= covariances[jj]; 102 yield return res;102 gr.Add(res); 103 103 } 104 104 } 105 return gr; 105 106 } 106 107 }
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