source: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovarianceLinear.cs @ 13721

Last change on this file since 13721 was 13721, checked in by mkommend, 5 years ago

#2591: Changed all GP covariance and mean functions to use int[] for column indices instead of IEnumerable<int>. Changed GP utils, GPModel and StudentTProcessModell as well to use fewer iterators and adapted unit tests to new interface.

File size: 2.5 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.Linq;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
27
28namespace HeuristicLab.Algorithms.DataAnalysis {
29  [StorableClass]
30  [Item(Name = "CovarianceLinear", Description = "Linear covariance function for Gaussian processes.")]
31  public sealed class CovarianceLinear : Item, ICovarianceFunction {
32    [StorableConstructor]
33    private CovarianceLinear(bool deserializing) : base(deserializing) { }
34    private CovarianceLinear(CovarianceLinear original, Cloner cloner)
35      : base(original, cloner) {
36    }
37    public CovarianceLinear()
38      : base() {
39    }
40
41    public override IDeepCloneable Clone(Cloner cloner) {
42      return new CovarianceLinear(this, cloner);
43    }
44
45    public int GetNumberOfParameters(int numberOfVariables) {
46      return 0;
47    }
48
49    public void SetParameter(double[] p) {
50      if (p.Length > 0) throw new ArgumentException("No parameters are allowed for the linear covariance function.");
51    }
52
53    public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, int[] columnIndices) {
54      if (p.Length > 0) throw new ArgumentException("No parameters are allowed for the linear covariance function.");
55      // create functions
56      var cov = new ParameterizedCovarianceFunction();
57      cov.Covariance = (x, i, j) => Util.ScalarProd(x, i, j, columnIndices, 1.0);
58      cov.CrossCovariance = (x, xt, i, j) => Util.ScalarProd(x, i, xt, j, columnIndices, 1.0);
59      cov.CovarianceGradient = (x, i, j) => Enumerable.Empty<double>();
60      return cov;
61    }
62  }
63}
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