1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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4 | *
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5 | * This file is part of HeuristicLab.
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6 | *
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7 | * HeuristicLab is free software: you can redistribute it and/or modify
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8 | * it under the terms of the GNU General Public License as published by
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9 | * the Free Software Foundation, either version 3 of the License, or
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10 | * (at your option) any later version.
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11 | *
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12 | * HeuristicLab is distributed in the hope that it will be useful,
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13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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15 | * GNU General Public License for more details.
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16 | *
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17 | * You should have received a copy of the GNU General Public License
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18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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19 | */
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20 | #endregion
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21 |
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22 | using System;
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23 | using System.Collections.Generic;
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24 | using System.Linq;
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25 | using HeuristicLab.Common;
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26 | using HeuristicLab.Core;
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27 | using HeuristicLab.Data;
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28 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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29 |
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30 | namespace HeuristicLab.Algorithms.DataAnalysis {
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31 | [StorableClass]
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32 | [Item(Name = "CovarianceLinearArd",
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33 | Description = "Linear covariance function with automatic relevance determination for Gaussian processes.")]
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34 | public class CovarianceLinearArd : CovarianceFunction {
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35 | public IValueParameter<DoubleArray> InverseLengthParameter {
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36 | get { return inverseLengthParameter; }
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37 | }
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38 |
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39 | [Storable]
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40 | private HyperParameter<DoubleArray> inverseLengthParameter;
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41 |
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42 | [Storable]
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43 | private double[] inverseLength;
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44 |
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45 | [StorableConstructor]
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46 | protected CovarianceLinearArd(bool deserializing) : base(deserializing) { }
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47 | protected CovarianceLinearArd(CovarianceLinearArd original, Cloner cloner)
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48 | : base(original, cloner) {
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49 | inverseLengthParameter = cloner.Clone(original.inverseLengthParameter);
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50 | if (original.inverseLength != null) {
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51 | this.inverseLength = new double[original.inverseLength.Length];
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52 | Array.Copy(original.inverseLength, inverseLength, inverseLength.Length);
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53 | }
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54 |
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55 | RegisterEvents();
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56 | }
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57 | public CovarianceLinearArd()
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58 | : base() {
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59 | inverseLengthParameter = new HyperParameter<DoubleArray>("InverseLength",
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60 | "The inverse length parameter for ARD.");
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61 | Parameters.Add(inverseLengthParameter);
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62 | RegisterEvents();
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63 | }
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64 |
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65 | [StorableHook(HookType.AfterDeserialization)]
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66 | private void AfterDeserialization() {
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67 | RegisterEvents();
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68 | }
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69 |
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70 | public override IDeepCloneable Clone(Cloner cloner) {
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71 | return new CovarianceLinearArd(this, cloner);
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72 | }
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73 |
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74 | // caching
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75 | private void RegisterEvents() {
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76 | AttachArrayChangeHandler<DoubleArray, double>(inverseLengthParameter, () => { inverseLength = inverseLengthParameter.Value.ToArray(); });
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77 | }
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78 |
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79 |
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80 | public override int GetNumberOfParameters(int numberOfVariables) {
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81 | if (!inverseLengthParameter.Fixed)
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82 | return numberOfVariables;
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83 | else
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84 | return 0;
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85 | }
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86 |
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87 | public override void SetParameter(double[] hyp) {
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88 | if (!inverseLengthParameter.Fixed && hyp.Length > 0) {
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89 | inverseLengthParameter.SetValue(new DoubleArray(hyp.Select(e => 1.0 / Math.Exp(e)).ToArray()));
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90 | } else throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovarianceLinearArd", "hyp");
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91 | }
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92 |
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93 | public override double GetCovariance(double[,] x, int i, int j) {
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94 | return Util.ScalarProd(x, i, j, inverseLength);
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95 | }
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96 |
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97 | public override IEnumerable<double> GetGradient(double[,] x, int i, int j) {
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98 | for (int k = 0; k < inverseLength.Length; k++) {
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99 | yield return -2.0 * x[i, k] * x[j, k] * inverseLength[k] * inverseLength[k];
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100 | }
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101 | }
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102 |
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103 | public override double GetCrossCovariance(double[,] x, double[,] xt, int i, int j) {
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104 | return Util.ScalarProd(x, i, xt, j, inverseLength);
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105 | }
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106 | }
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107 | }
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