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source: branches/2925_AutoDiffForDynamicalModels/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceFunctions/CovariancePolynomial.cs @ 16662

Last change on this file since 16662 was 16662, checked in by gkronber, 5 years ago

#2925: merged all changes from trunk to branch (up to r16659)

File size: 5.2 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
21
22using System;
23using System.Collections.Generic;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Data;
27using HeuristicLab.Parameters;
28using HEAL.Attic;
29
30namespace HeuristicLab.Algorithms.DataAnalysis {
31  [StorableType("BD6DF0C6-07A2-44CE-8EDB-92561505EF6E")]
32  [Item(Name = "CovariancePolynomial",
33    Description = "Polynomial covariance function for Gaussian processes.")]
34  public sealed class CovariancePolynomial : ParameterizedNamedItem, ICovarianceFunction {
35    public IValueParameter<DoubleValue> ConstParameter {
36      get { return (IValueParameter<DoubleValue>)Parameters["Const"]; }
37    }
38
39    public IValueParameter<DoubleValue> ScaleParameter {
40      get { return (IValueParameter<DoubleValue>)Parameters["Scale"]; }
41    }
42
43    public IValueParameter<IntValue> DegreeParameter {
44      get { return (IValueParameter<IntValue>)Parameters["Degree"]; }
45    }
46    private bool HasFixedConstParameter {
47      get { return ConstParameter.Value != null; }
48    }
49    private bool HasFixedScaleParameter {
50      get { return ScaleParameter.Value != null; }
51    }
52
53    [StorableConstructor]
54    private CovariancePolynomial(StorableConstructorFlag _) : base(_) {
55    }
56
57    private CovariancePolynomial(CovariancePolynomial original, Cloner cloner)
58      : base(original, cloner) {
59    }
60
61    public CovariancePolynomial()
62      : base() {
63      Name = ItemName;
64      Description = ItemDescription;
65
66      Parameters.Add(new OptionalValueParameter<DoubleValue>("Const", "Additive constant in the polymomial."));
67      Parameters.Add(new OptionalValueParameter<DoubleValue>("Scale", "The scale parameter of the polynomial covariance function."));
68      Parameters.Add(new ValueParameter<IntValue>("Degree", "The degree of the polynomial (only non-zero positive values allowed).", new IntValue(2)));
69    }
70
71    public override IDeepCloneable Clone(Cloner cloner) {
72      return new CovariancePolynomial(this, cloner);
73    }
74
75    public int GetNumberOfParameters(int numberOfVariables) {
76      return
77        (HasFixedConstParameter ? 0 : 1) +
78        (HasFixedScaleParameter ? 0 : 1);
79    }
80
81    public void SetParameter(double[] p) {
82      double @const, scale;
83      GetParameterValues(p, out @const, out scale);
84      ConstParameter.Value = new DoubleValue(@const);
85      ScaleParameter.Value = new DoubleValue(scale);
86    }
87
88    private void GetParameterValues(double[] p, out double @const, out double scale) {
89      // gather parameter values
90      int n = 0;
91      if (HasFixedConstParameter) {
92        @const = ConstParameter.Value.Value;
93      } else {
94        @const = Math.Exp(p[n]);
95        n++;
96      }
97
98      if (HasFixedScaleParameter) {
99        scale = ScaleParameter.Value.Value;
100      } else {
101        scale = Math.Exp(2 * p[n]);
102        n++;
103      }
104      if (p.Length != n) throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovariancePolynomial", "p");
105    }
106
107    public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, int[] columnIndices) {
108      double @const, scale;
109      int degree = DegreeParameter.Value.Value;
110      if (degree <= 0) throw new ArgumentException("The degree parameter for CovariancePolynomial must be greater than zero.");
111      GetParameterValues(p, out @const, out scale);
112      var fixedConst = HasFixedConstParameter;
113      var fixedScale = HasFixedScaleParameter;
114      // create functions
115      var cov = new ParameterizedCovarianceFunction();
116      cov.Covariance = (x, i, j) => scale * Math.Pow(@const + Util.ScalarProd(x, i, j, columnIndices, 1.0), degree);
117      cov.CrossCovariance = (x, xt, i, j) => scale * Math.Pow(@const + Util.ScalarProd(x, i, xt, j, columnIndices, 1.0), degree);
118      cov.CovarianceGradient = (x, i, j) => GetGradient(x, i, j, @const, scale, degree, columnIndices, fixedConst, fixedScale);
119      return cov;
120    }
121
122    private static IList<double> GetGradient(double[,] x, int i, int j, double c, double scale, int degree, int[] columnIndices,
123      bool fixedConst, bool fixedScale) {
124      double s = Util.ScalarProd(x, i, j, columnIndices, 1.0);
125      var g = new List<double>(2);
126      if (!fixedConst) g.Add(c * degree * scale * Math.Pow(c + s, degree - 1));
127      if (!fixedScale) g.Add(2 * scale * Math.Pow(c + s, degree));
128      return g;
129    }
130  }
131}
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