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source: trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/ICovarianceFunction.cs @ 16685

Last change on this file since 16685 was 16565, checked in by gkronber, 6 years ago

#2520: merged changes from PersistenceOverhaul branch (r16451:16564) into trunk

File size: 1.8 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2019 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.Collections.Generic;
23using HEAL.Attic;
24using HeuristicLab.Core;
25
26namespace HeuristicLab.Algorithms.DataAnalysis {
27
28  public delegate double CovarianceFunctionDelegate(double[,] x, int i, int j);
29  public delegate double CrossCovarianceFunctionDelegate(double[,] x, double[,] xt, int i, int j);
30  public delegate IList<double> CovarianceGradientFunctionDelegate(double[,] x, int i, int j);
31
32  public class ParameterizedCovarianceFunction {
33    public CovarianceFunctionDelegate Covariance { get; set; }
34    public CrossCovarianceFunctionDelegate CrossCovariance { get; set; }
35    public CovarianceGradientFunctionDelegate CovarianceGradient { get; set; }
36  }
37
38  [StorableType("d175f852-bb94-4b19-9afa-a7f554845a26")]
39  public interface ICovarianceFunction : IItem {
40    int GetNumberOfParameters(int numberOfVariables);
41    void SetParameter(double[] p);
42    ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, int[] columnIndices);
43  }
44}
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