1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 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.Parameters;
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29 | using HEAL.Attic;
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30 |
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31 | namespace HeuristicLab.Algorithms.DataAnalysis {
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32 | [StorableType("88CB6895-6CD8-4F81-8E3D-905EEBB7E77A")]
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33 | [Item(Name = "CovarianceSquaredExponentialArd", Description = "Squared exponential covariance function with automatic relevance determination for Gaussian processes.")]
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34 | public sealed class CovarianceSquaredExponentialArd : ParameterizedNamedItem, ICovarianceFunction {
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35 | public IValueParameter<DoubleValue> ScaleParameter {
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36 | get { return (IValueParameter<DoubleValue>)Parameters["Scale"]; }
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37 | }
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38 |
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39 | public IValueParameter<DoubleArray> InverseLengthParameter {
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40 | get { return (IValueParameter<DoubleArray>)Parameters["InverseLength"]; }
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41 | }
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42 | private bool HasFixedInverseLengthParameter {
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43 | get { return InverseLengthParameter.Value != null; }
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44 | }
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45 | private bool HasFixedScaleParameter {
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46 | get { return ScaleParameter.Value != null; }
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47 | }
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48 |
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49 | [StorableConstructor]
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50 | private CovarianceSquaredExponentialArd(StorableConstructorFlag _) : base(_) { }
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51 | private CovarianceSquaredExponentialArd(CovarianceSquaredExponentialArd original, Cloner cloner)
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52 | : base(original, cloner) {
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53 | }
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54 | public CovarianceSquaredExponentialArd()
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55 | : base() {
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56 | Name = ItemName;
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57 | Description = ItemDescription;
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58 |
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59 | Parameters.Add(new OptionalValueParameter<DoubleValue>("Scale", "The scale parameter of the squared exponential covariance function with ARD."));
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60 | Parameters.Add(new OptionalValueParameter<DoubleArray>("InverseLength", "The inverse length parameter for automatic relevance determination."));
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61 | }
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62 |
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63 | public override IDeepCloneable Clone(Cloner cloner) {
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64 | return new CovarianceSquaredExponentialArd(this, cloner);
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65 | }
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66 |
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67 | public int GetNumberOfParameters(int numberOfVariables) {
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68 | return
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69 | (HasFixedScaleParameter ? 0 : 1) +
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70 | (HasFixedInverseLengthParameter ? 0 : numberOfVariables);
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71 | }
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72 |
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73 | public void SetParameter(double[] p) {
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74 | double scale;
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75 | double[] inverseLength;
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76 | GetParameterValues(p, out scale, out inverseLength);
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77 | ScaleParameter.Value = new DoubleValue(scale);
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78 | InverseLengthParameter.Value = new DoubleArray(inverseLength);
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79 | }
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80 |
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81 | private void GetParameterValues(double[] p, out double scale, out double[] inverseLength) {
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82 | int c = 0;
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83 | // gather parameter values
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84 | if (HasFixedInverseLengthParameter) {
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85 | inverseLength = InverseLengthParameter.Value.ToArray();
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86 | } else {
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87 | int length = p.Length;
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88 | if (!HasFixedScaleParameter) length--;
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89 | inverseLength = p.Select(e => 1.0 / Math.Exp(e)).Take(length).ToArray();
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90 | c += inverseLength.Length;
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91 | }
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92 | if (HasFixedScaleParameter) {
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93 | scale = ScaleParameter.Value.Value;
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94 | } else {
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95 | scale = Math.Exp(2 * p[c]);
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96 | c++;
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97 | }
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98 | if (p.Length != c) throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovarianceSquaredExponentialArd", "p");
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99 | }
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100 |
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101 | public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, int[] columnIndices) {
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102 | double scale;
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103 | double[] inverseLength;
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104 | GetParameterValues(p, out scale, out inverseLength);
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105 | var fixedInverseLength = HasFixedInverseLengthParameter;
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106 | var fixedScale = HasFixedScaleParameter;
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107 | // create functions
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108 | var cov = new ParameterizedCovarianceFunction();
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109 | cov.Covariance = (x, i, j) => {
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110 | double d = i == j
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111 | ? 0.0
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112 | : Util.SqrDist(x, i, j, inverseLength, columnIndices);
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113 | return scale * Math.Exp(-d / 2.0);
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114 | };
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115 | cov.CrossCovariance = (x, xt, i, j) => {
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116 | double d = Util.SqrDist(x, i, xt, j, inverseLength, columnIndices);
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117 | return scale * Math.Exp(-d / 2.0);
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118 | };
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119 | cov.CovarianceGradient = (x, i, j) => GetGradient(x, i, j, columnIndices, scale, inverseLength, fixedInverseLength, fixedScale);
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120 | return cov;
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121 | }
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122 |
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123 | // order of returned gradients must match the order in GetParameterValues!
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124 | private static IList<double> GetGradient(double[,] x, int i, int j, int[] columnIndices, double scale, double[] inverseLength,
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125 | bool fixedInverseLength, bool fixedScale) {
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126 | double d = i == j
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127 | ? 0.0
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128 | : Util.SqrDist(x, i, j, inverseLength, columnIndices);
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129 |
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130 | int k = 0;
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131 | var g = new List<double>((!fixedInverseLength ? columnIndices.Length : 0) + (!fixedScale ? 1 : 0));
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132 | if (!fixedInverseLength) {
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133 | for (int c = 0; c < columnIndices.Length; c++) {
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134 | var columnIndex = columnIndices[c];
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135 | double sqrDist = Util.SqrDist(x[i, columnIndex] * inverseLength[k], x[j, columnIndex] * inverseLength[k]);
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136 | g.Add(scale * Math.Exp(-d / 2.0) * sqrDist);
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137 | k++;
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138 | }
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139 | }
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140 | if (!fixedScale) g.Add(2.0 * scale * Math.Exp(-d / 2.0));
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141 | return g;
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142 | }
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143 | }
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144 | }
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