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source: branches/GP-MoveOperators/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanZero.cs @ 9844

Last change on this file since 9844 was 8612, checked in by gkronber, 12 years ago

#1902 implemented all mean and covariance functions with parameters as ParameterizedNamedItems

File size: 2.1 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2012 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.Linq;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
26
27namespace HeuristicLab.Algorithms.DataAnalysis {
28  [StorableClass]
29  [Item(Name = "MeanZero", Description = "Constant zero mean function for Gaussian processes.")]
30  public sealed class MeanZero : Item, IMeanFunction {
31    [StorableConstructor]
32    private MeanZero(bool deserializing) : base(deserializing) { }
33    private MeanZero(MeanZero original, Cloner cloner)
34      : base(original, cloner) {
35    }
36    public MeanZero() {
37    }
38
39    public override IDeepCloneable Clone(Cloner cloner) {
40      return new MeanZero(this, cloner);
41    }
42
43    public int GetNumberOfParameters(int numberOfVariables) {
44      return 0;
45    }
46
47    public void SetParameter(double[] hyp) {
48      if (hyp.Length > 0) throw new ArgumentException("No hyper-parameters allowed for zero mean function.", "hyp");
49    }
50
51    public double[] GetMean(double[,] x) {
52      return Enumerable.Repeat(0.0, x.GetLength(0)).ToArray();
53    }
54
55    public double[] GetGradients(int k, double[,] x) {
56      if (k > 0) throw new ArgumentException();
57      return Enumerable.Repeat(0.0, x.GetLength(0)).ToArray();
58    }
59  }
60}
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