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source: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceNoise.cs @ 8484

Last change on this file since 8484 was 8484, checked in by gkronber, 12 years ago

#1902 changed interface for covariance functions to improve readability, fixed several bugs in the covariance functions and in the line chart for Gaussian process models.

File size: 2.2 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2012 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;
23using System.Collections.Generic;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
27
28namespace HeuristicLab.Algorithms.DataAnalysis {
29  [StorableClass]
30  [Item(Name = "CovarianceNoise",
31    Description = "Noise covariance function for Gaussian processes.")]
32  public class CovarianceNoise : Item, ICovarianceFunction {
33    [Storable]
34    private double sf2;
35    public double Scale { get { return sf2; } }
36
37    [StorableConstructor]
38    protected CovarianceNoise(bool deserializing)
39      : base(deserializing) {
40    }
41
42    protected CovarianceNoise(CovarianceNoise original, Cloner cloner)
43      : base(original, cloner) {
44      this.sf2 = original.sf2;
45    }
46
47    public CovarianceNoise()
48      : base() {
49    }
50
51    public override IDeepCloneable Clone(Cloner cloner) {
52      return new CovarianceNoise(this, cloner);
53    }
54
55    public int GetNumberOfParameters(int numberOfVariables) {
56      return 1;
57    }
58
59    public void SetParameter(double[] hyp) {
60      this.sf2 = Math.Exp(2 * hyp[0]);
61    }
62
63    public double GetCovariance(double[,] x, int i, int j) {
64      return sf2;
65    }
66
67    public IEnumerable<double> GetGradient(double[,] x, int i, int j) {
68      yield return 2 * sf2;
69    }
70
71    public double GetCrossCovariance(double[,] x, double[,] xt, int i, int j) {
72      return 0.0;
73    }
74  }
75}
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