source: branches/2520_PersistenceReintegration/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanZero.cs @ 16453

Last change on this file since 16453 was 16453, checked in by jkarder, 10 months ago

#2520: updated year of copyrights

File size: 2.2 KB
Line 
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
21using System;
22using HeuristicLab.Common;
23using HeuristicLab.Core;
24using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
25
26namespace HeuristicLab.Algorithms.DataAnalysis {
27  [StorableClass]
28  [Item(Name = "MeanZero", Description = "Constant zero mean function for Gaussian processes.")]
29  public sealed class MeanZero : Item, IMeanFunction {
30    [StorableConstructor]
31    private MeanZero(bool deserializing) : base(deserializing) { }
32    private MeanZero(MeanZero original, Cloner cloner)
33      : base(original, cloner) {
34    }
35    public MeanZero() {
36    }
37
38    public override IDeepCloneable Clone(Cloner cloner) {
39      return new MeanZero(this, cloner);
40    }
41
42    public int GetNumberOfParameters(int numberOfVariables) {
43      return 0;
44    }
45
46    public void SetParameter(double[] p) {
47      if (p.Length > 0) throw new ArgumentException("No parameters allowed for zero mean function.", "p");
48    }
49
50    public ParameterizedMeanFunction GetParameterizedMeanFunction(double[] p, int[] columnIndices) {
51      if (p.Length > 0) throw new ArgumentException("No parameters allowed for zero mean function.", "p");
52      var mf = new ParameterizedMeanFunction();
53      mf.Mean = (x, i) => 0.0;
54      mf.Gradient = (x, i, k) => {
55        if (k > 0)
56          throw new ArgumentException();
57        return 0.0;
58      };
59      return mf;
60    }
61  }
62}
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