source: branches/2839_HiveProjectManagement/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovarianceConst.cs @ 16057

Last change on this file since 16057 was 16057, checked in by jkarder, 15 months ago

#2839:

File size: 3.4 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2018 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 = "CovarianceConst",
32    Description = "Constant covariance function for Gaussian processes.")]
33  public sealed class CovarianceConst : 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    [StorableConstructor]
41    private CovarianceConst(bool deserializing)
42      : base(deserializing) {
43    }
44
45    private CovarianceConst(CovarianceConst original, Cloner cloner)
46      : base(original, cloner) {
47    }
48
49    public CovarianceConst()
50      : base() {
51      Name = ItemName;
52      Description = ItemDescription;
53
54      Parameters.Add(new OptionalValueParameter<DoubleValue>("Scale", "The scale of the constant covariance function."));
55    }
56
57    public override IDeepCloneable Clone(Cloner cloner) {
58      return new CovarianceConst(this, cloner);
59    }
60
61    public int GetNumberOfParameters(int numberOfVariables) {
62      return HasFixedScaleParameter ? 0 : 1;
63    }
64
65    public void SetParameter(double[] p) {
66      double scale;
67      GetParameterValues(p, out scale);
68      ScaleParameter.Value = new DoubleValue(scale);
69    }
70
71    private void GetParameterValues(double[] p, out double scale) {
72      int c = 0;
73      // gather parameter values
74      if (HasFixedScaleParameter) {
75        scale = ScaleParameter.Value.Value;
76      } else {
77        scale = Math.Exp(2 * p[c]);
78        c++;
79      }
80      if (p.Length != c) throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovarianceConst", "p");
81    }
82
83    public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, int[] columnIndices) {
84      double scale;
85      GetParameterValues(p, out scale);
86      // create functions
87      var cov = new ParameterizedCovarianceFunction();
88      cov.Covariance = (x, i, j) => scale;
89      cov.CrossCovariance = (x, xt, i, j) => scale;
90      if (HasFixedScaleParameter) {
91        cov.CovarianceGradient = (x, i, j) => new double[0];
92      } else {
93        cov.CovarianceGradient = (x, i, j) => new[] { 2.0 * scale };
94      }
95      return cov;
96    }
97  }
98}
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