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source: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanZero.cs @ 10614

Last change on this file since 10614 was 9456, checked in by swagner, 12 years ago

Updated copyright year and added some missing license headers (#1889)

File size: 2.3 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2013 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 System.Collections.Generic;
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 = "MeanZero", Description = "Constant zero mean function for Gaussian processes.")]
31  public sealed class MeanZero : Item, IMeanFunction {
32    [StorableConstructor]
33    private MeanZero(bool deserializing) : base(deserializing) { }
34    private MeanZero(MeanZero original, Cloner cloner)
35      : base(original, cloner) {
36    }
37    public MeanZero() {
38    }
39
40    public override IDeepCloneable Clone(Cloner cloner) {
41      return new MeanZero(this, cloner);
42    }
43
44    public int GetNumberOfParameters(int numberOfVariables) {
45      return 0;
46    }
47
48    public void SetParameter(double[] p) {
49      if (p.Length > 0) throw new ArgumentException("No parameters allowed for zero mean function.", "p");
50    }
51
52    public ParameterizedMeanFunction GetParameterizedMeanFunction(double[] p, IEnumerable<int> columnIndices) {
53      if (p.Length > 0) throw new ArgumentException("No parameters allowed for zero mean function.", "p");
54      var mf = new ParameterizedMeanFunction();
55      mf.Mean = (x, i) => 0.0;
56      mf.Gradient = (x, i, k) => {
57        if (k > 0)
58          throw new ArgumentException();
59        return 0.0;
60      };
61      return mf;
62    }
63  }
64}
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