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source: stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/MeanFunctions/MeanConst.cs @ 15298

Last change on this file since 15298 was 14186, checked in by swagner, 8 years ago

#2526: Updated year of copyrights in license headers

File size: 3.0 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2016 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 HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Parameters;
29using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
30
31namespace HeuristicLab.Algorithms.DataAnalysis {
32  [StorableClass]
33  [Item(Name = "MeanConst", Description = "Constant mean function for Gaussian processes.")]
34  public sealed class MeanConst : ParameterizedNamedItem, IMeanFunction {
35    public IValueParameter<DoubleValue> ValueParameter {
36      get { return (IValueParameter<DoubleValue>)Parameters["Value"]; }
37    }
38
39    [StorableConstructor]
40    private MeanConst(bool deserializing) : base(deserializing) { }
41    private MeanConst(MeanConst original, Cloner cloner)
42      : base(original, cloner) {
43    }
44    public MeanConst()
45      : base() {
46      this.name = ItemName;
47      this.description = ItemDescription;
48
49      Parameters.Add(new OptionalValueParameter<DoubleValue>("Value", "The constant value for the constant mean function."));
50    }
51
52    public override IDeepCloneable Clone(Cloner cloner) {
53      return new MeanConst(this, cloner);
54    }
55
56    public int GetNumberOfParameters(int numberOfVariables) {
57      return ValueParameter.Value != null ? 0 : 1;
58    }
59
60    public void SetParameter(double[] p) {
61      double c;
62      GetParameters(p, out c);
63      ValueParameter.Value = new DoubleValue(c);
64    }
65
66    private void GetParameters(double[] p, out double c) {
67      if (ValueParameter.Value == null) {
68        c = p[0];
69      } else {
70        if (p.Length > 0)
71          throw new ArgumentException(
72            "The length of the parameter vector does not match the number of free parameters for the constant mean function.",
73            "p");
74        c = ValueParameter.Value.Value;
75      }
76    }
77
78    public ParameterizedMeanFunction GetParameterizedMeanFunction(double[] p, int[] columnIndices) {
79      double c;
80      GetParameters(p, out c);
81      var mf = new ParameterizedMeanFunction();
82      mf.Mean = (x, i) => c;
83      mf.Gradient = (x, i, k) => {
84        if (k > 0) throw new ArgumentException();
85        return 1.0;
86      };
87      return mf;
88    }
89  }
90}
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