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source: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceNoise.cs @ 8771

Last change on this file since 8771 was 8771, checked in by gkronber, 11 years ago

#1902: fixed a bug in the noise covariance function

File size: 3.4 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.Data;
27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
28
29namespace HeuristicLab.Algorithms.DataAnalysis {
30  [StorableClass]
31  [Item(Name = "CovarianceNoise",
32    Description = "Noise covariance function for Gaussian processes.")]
33  public sealed class CovarianceNoise : ParameterizedNamedItem, ICovarianceFunction {
34
35
36    [Storable]
37    private double sf2;
38    [Storable]
39    private readonly HyperParameter<DoubleValue> scaleParameter;
40    public IValueParameter<DoubleValue> ScaleParameter {
41      get { return scaleParameter; }
42    }
43
44    [StorableConstructor]
45    private CovarianceNoise(bool deserializing)
46      : base(deserializing) {
47    }
48
49    private CovarianceNoise(CovarianceNoise original, Cloner cloner)
50      : base(original, cloner) {
51      this.scaleParameter = cloner.Clone(original.scaleParameter);
52      this.sf2 = original.sf2;
53      RegisterEvents();
54    }
55
56    public CovarianceNoise()
57      : base() {
58      Name = ItemName;
59      Description = ItemDescription;
60
61      this.scaleParameter = new HyperParameter<DoubleValue>("Scale", "The scale of noise.");
62      Parameters.Add(this.scaleParameter);
63
64      RegisterEvents();
65    }
66
67    public override IDeepCloneable Clone(Cloner cloner) {
68      return new CovarianceNoise(this, cloner);
69    }
70
71    [StorableHook(HookType.AfterDeserialization)]
72    private void AfterDeserialization() {
73      RegisterEvents();
74    }
75
76    private void RegisterEvents() {
77      Util.AttachValueChangeHandler<DoubleValue, double>(scaleParameter, () => { sf2 = scaleParameter.Value.Value; });
78    }
79
80    public int GetNumberOfParameters(int numberOfVariables) {
81      return scaleParameter.Fixed ? 0 : 1;
82    }
83
84    public void SetParameter(double[] hyp) {
85      if (!scaleParameter.Fixed) {
86        scaleParameter.SetValue(new DoubleValue(Math.Exp(2 * hyp[0])));
87      } else {
88        if (hyp.Length > 0) throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovarianceNoise", "hyp");
89      }
90    }
91
92    public double GetCovariance(double[,] x, int i, int j, IEnumerable<int> columnIndices) {
93      return i == j ? sf2 : 0.0;
94    }
95
96    public IEnumerable<double> GetGradient(double[,] x, int i, int j, IEnumerable<int> columnIndices) {
97      yield return i == j ? 2 * sf2 : 0.0;
98    }
99
100    public double GetCrossCovariance(double[,] x, double[,] xt, int i, int j, IEnumerable<int> columnIndices) {
101      return 0.0;
102    }
103  }
104}
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