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

Last change on this file since 16453 was 16453, checked in by jkarder, 12 months ago

#2520: updated year of copyrights

File size: 3.3 KB
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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.Linq;
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 = "CovarianceMask",
32    Description = "Masking covariance function for dimension selection can be used to apply a covariance function only on certain input dimensions.")]
33  public sealed class CovarianceMask : ParameterizedNamedItem, ICovarianceFunction {
34    public IValueParameter<IntArray> SelectedDimensionsParameter {
35      get { return (IValueParameter<IntArray>)Parameters["SelectedDimensions"]; }
36    }
37    public IValueParameter<ICovarianceFunction> CovarianceFunctionParameter {
38      get { return (IValueParameter<ICovarianceFunction>)Parameters["CovarianceFunction"]; }
39    }
40
41    [StorableConstructor]
42    private CovarianceMask(bool deserializing)
43      : base(deserializing) {
44    }
45
46    private CovarianceMask(CovarianceMask original, Cloner cloner)
47      : base(original, cloner) {
48    }
49
50    public CovarianceMask()
51      : base() {
52      Name = ItemName;
53      Description = ItemDescription;
54
55      Parameters.Add(new OptionalValueParameter<IntArray>("SelectedDimensions", "The dimensions on which the specified covariance function should be applied to."));
56      Parameters.Add(new ValueParameter<ICovarianceFunction>("CovarianceFunction", "The covariance function that should be scaled.", new CovarianceSquaredExponentialIso()));
57    }
58
59    public override IDeepCloneable Clone(Cloner cloner) {
60      return new CovarianceMask(this, cloner);
61    }
62
63    public int GetNumberOfParameters(int numberOfVariables) {
64      if (SelectedDimensionsParameter.Value == null) return CovarianceFunctionParameter.Value.GetNumberOfParameters(numberOfVariables);
65      else return CovarianceFunctionParameter.Value.GetNumberOfParameters(SelectedDimensionsParameter.Value.Length);
66    }
67
68    public void SetParameter(double[] p) {
69      CovarianceFunctionParameter.Value.SetParameter(p);
70    }
71
72    public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, int[] columnIndices) {
73      var cov = CovarianceFunctionParameter.Value;
74      var selectedDimensions = SelectedDimensionsParameter.Value;
75
76      return cov.GetParameterizedCovarianceFunction(p, selectedDimensions.Intersect(columnIndices).ToArray());
77    }
78  }
79}
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