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source: trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovarianceMask.cs @ 17529

Last change on this file since 17529 was 17180, checked in by swagner, 5 years ago

#2875: Removed years in copyrights

File size: 3.2 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 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 HEAL.Attic;
28
29namespace HeuristicLab.Algorithms.DataAnalysis {
30  [StorableType("21D5F261-B9DF-4DC4-AF42-7B223C45840F")]
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(StorableConstructorFlag _) : base(_) {
43    }
44
45    private CovarianceMask(CovarianceMask original, Cloner cloner)
46      : base(original, cloner) {
47    }
48
49    public CovarianceMask()
50      : base() {
51      Name = ItemName;
52      Description = ItemDescription;
53
54      Parameters.Add(new OptionalValueParameter<IntArray>("SelectedDimensions", "The dimensions on which the specified covariance function should be applied to."));
55      Parameters.Add(new ValueParameter<ICovarianceFunction>("CovarianceFunction", "The covariance function that should be scaled.", new CovarianceSquaredExponentialIso()));
56    }
57
58    public override IDeepCloneable Clone(Cloner cloner) {
59      return new CovarianceMask(this, cloner);
60    }
61
62    public int GetNumberOfParameters(int numberOfVariables) {
63      if (SelectedDimensionsParameter.Value == null) return CovarianceFunctionParameter.Value.GetNumberOfParameters(numberOfVariables);
64      else return CovarianceFunctionParameter.Value.GetNumberOfParameters(SelectedDimensionsParameter.Value.Length);
65    }
66
67    public void SetParameter(double[] p) {
68      CovarianceFunctionParameter.Value.SetParameter(p);
69    }
70
71    public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, int[] columnIndices) {
72      var cov = CovarianceFunctionParameter.Value;
73      var selectedDimensions = SelectedDimensionsParameter.Value;
74
75      return cov.GetParameterizedCovarianceFunction(p, selectedDimensions.Intersect(columnIndices).ToArray());
76    }
77  }
78}
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