source: branches/2520_PersistenceReintegration/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovarianceNoise.cs @ 16453

Last change on this file since 16453 was 16453, checked in by jkarder, 11 months ago

#2520: updated year of copyrights

File size: 3.5 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;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Parameters;
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    public IValueParameter<DoubleValue> ScaleParameter {
35      get { return (IValueParameter<DoubleValue>)Parameters["Scale"]; }
36    }
37    private bool HasFixedScaleParameter {
38      get { return ScaleParameter.Value != null; }
39    }
40
41    [StorableConstructor]
42    private CovarianceNoise(bool deserializing)
43      : base(deserializing) {
44    }
45
46    private CovarianceNoise(CovarianceNoise original, Cloner cloner)
47      : base(original, cloner) {
48    }
49
50    public CovarianceNoise()
51      : base() {
52      Name = ItemName;
53      Description = ItemDescription;
54
55      Parameters.Add(new OptionalValueParameter<DoubleValue>("Scale", "The scale of noise."));
56    }
57
58    public override IDeepCloneable Clone(Cloner cloner) {
59      return new CovarianceNoise(this, cloner);
60    }
61
62    public int GetNumberOfParameters(int numberOfVariables) {
63      return HasFixedScaleParameter ? 0 : 1;
64    }
65
66    public void SetParameter(double[] p) {
67      double scale;
68      GetParameterValues(p, out scale);
69      ScaleParameter.Value = new DoubleValue(scale);
70    }
71
72    private void GetParameterValues(double[] p, out double scale) {
73      int c = 0;
74      // gather parameter values
75      if (HasFixedScaleParameter) {
76        scale = ScaleParameter.Value.Value;
77      } else {
78        scale = Math.Exp(2 * p[c]);
79        c++;
80      }
81      if (p.Length != c) throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovarianceNoise", "p");
82    }
83
84    public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, int[] columnIndices) {
85      double scale;
86      GetParameterValues(p, out scale);
87      var fixedScale = HasFixedScaleParameter;
88      // create functions
89      var cov = new ParameterizedCovarianceFunction();
90      cov.Covariance = (x, i, j) => i == j ? scale : 0.0;
91      cov.CrossCovariance = (x, xt, i, j) => Util.SqrDist(x, i, xt, j, columnIndices, 1.0) < 1e-9 ? scale : 0.0;
92      if (fixedScale)
93        cov.CovarianceGradient = (x, i, j) => new double[0];
94      else
95        cov.CovarianceGradient = (x, i, j) => new double[1] { i == j ? 2.0 * scale : 0.0 };
96      return cov;
97    }
98  }
99}
Note: See TracBrowser for help on using the repository browser.