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source: branches/WebJobManager/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovarianceMask.cs @ 17596

Last change on this file since 17596 was 12012, checked in by ascheibe, 10 years ago

#2212 merged r12008, r12009, r12010 back into trunk

File size: 3.3 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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 System.Linq;
25using System.Linq.Expressions;
26using HeuristicLab.Common;
27using HeuristicLab.Core;
28using HeuristicLab.Data;
29using HeuristicLab.Parameters;
30using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
31
32namespace HeuristicLab.Algorithms.DataAnalysis {
33  [StorableClass]
34  [Item(Name = "CovarianceMask",
35    Description = "Masking covariance function for dimension selection can be used to apply a covariance function only on certain input dimensions.")]
36  public sealed class CovarianceMask : ParameterizedNamedItem, ICovarianceFunction {
37    public IValueParameter<IntArray> SelectedDimensionsParameter {
38      get { return (IValueParameter<IntArray>)Parameters["SelectedDimensions"]; }
39    }
40    public IValueParameter<ICovarianceFunction> CovarianceFunctionParameter {
41      get { return (IValueParameter<ICovarianceFunction>)Parameters["CovarianceFunction"]; }
42    }
43
44    [StorableConstructor]
45    private CovarianceMask(bool deserializing)
46      : base(deserializing) {
47    }
48
49    private CovarianceMask(CovarianceMask original, Cloner cloner)
50      : base(original, cloner) {
51    }
52
53    public CovarianceMask()
54      : base() {
55      Name = ItemName;
56      Description = ItemDescription;
57
58      Parameters.Add(new OptionalValueParameter<IntArray>("SelectedDimensions", "The dimensions on which the specified covariance function should be applied to."));
59      Parameters.Add(new ValueParameter<ICovarianceFunction>("CovarianceFunction", "The covariance function that should be scaled.", new CovarianceSquaredExponentialIso()));
60    }
61
62    public override IDeepCloneable Clone(Cloner cloner) {
63      return new CovarianceMask(this, cloner);
64    }
65
66    public int GetNumberOfParameters(int numberOfVariables) {
67      if (SelectedDimensionsParameter.Value == null) return CovarianceFunctionParameter.Value.GetNumberOfParameters(numberOfVariables);
68      else return CovarianceFunctionParameter.Value.GetNumberOfParameters(SelectedDimensionsParameter.Value.Length);
69    }
70
71    public void SetParameter(double[] p) {
72      CovarianceFunctionParameter.Value.SetParameter(p);
73    }
74
75    public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, IEnumerable<int> columnIndices) {
76      var cov = CovarianceFunctionParameter.Value;
77      var selectedDimensions = SelectedDimensionsParameter.Value;
78
79      return cov.GetParameterizedCovarianceFunction(p, selectedDimensions.Intersect(columnIndices));
80    }
81  }
82}
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