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("25439318-762C-4ED6-BAE7-E53860598A01")]
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33 | [Item(Name = "CovarianceRationalQuadraticArd",
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34 | Description = "Rational quadratic covariance function with automatic relevance determination for Gaussian processes.")]
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35 | public sealed class CovarianceRationalQuadraticArd : ParameterizedNamedItem, ICovarianceFunction {
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36 | public IValueParameter<DoubleValue> ScaleParameter {
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37 | get { return (IValueParameter<DoubleValue>)Parameters["Scale"]; }
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38 | }
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39 |
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40 | public IValueParameter<DoubleArray> InverseLengthParameter {
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41 | get { return (IValueParameter<DoubleArray>)Parameters["InverseLength"]; }
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42 | }
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43 |
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44 | public IValueParameter<DoubleValue> ShapeParameter {
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45 | get { return (IValueParameter<DoubleValue>)Parameters["Shape"]; }
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46 | }
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47 | private bool HasFixedScaleParameter {
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48 | get { return ScaleParameter.Value != null; }
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49 | }
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50 | private bool HasFixedInverseLengthParameter {
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51 | get { return InverseLengthParameter.Value != null; }
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52 | }
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53 | private bool HasFixedShapeParameter {
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54 | get { return ShapeParameter.Value != null; }
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55 | }
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56 |
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57 | [StorableConstructor]
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58 | private CovarianceRationalQuadraticArd(StorableConstructorFlag _) : base(_) {
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59 | }
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60 |
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61 | private CovarianceRationalQuadraticArd(CovarianceRationalQuadraticArd original, Cloner cloner)
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62 | : base(original, cloner) {
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63 | }
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64 |
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65 | public CovarianceRationalQuadraticArd()
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66 | : base() {
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67 | Name = ItemName;
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68 | Description = ItemDescription;
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69 |
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70 | Parameters.Add(new OptionalValueParameter<DoubleValue>("Scale", "The scale parameter of the rational quadratic covariance function with ARD."));
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71 | Parameters.Add(new OptionalValueParameter<DoubleArray>("InverseLength", "The inverse length parameter for automatic relevance determination."));
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72 | Parameters.Add(new OptionalValueParameter<DoubleValue>("Shape", "The shape parameter (alpha) of the rational quadratic covariance function with ARD."));
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73 | }
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74 |
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75 | public override IDeepCloneable Clone(Cloner cloner) {
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76 | return new CovarianceRationalQuadraticArd(this, cloner);
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77 | }
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78 |
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79 | public int GetNumberOfParameters(int numberOfVariables) {
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80 | return
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81 | (HasFixedScaleParameter ? 0 : 1) +
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82 | (HasFixedShapeParameter ? 0 : 1) +
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83 | (HasFixedInverseLengthParameter ? 0 : numberOfVariables);
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84 | }
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85 |
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86 | public void SetParameter(double[] p) {
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87 | double scale, shape;
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88 | double[] inverseLength;
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89 | GetParameterValues(p, out scale, out shape, out inverseLength);
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90 | ScaleParameter.Value = new DoubleValue(scale);
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91 | ShapeParameter.Value = new DoubleValue(shape);
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92 | InverseLengthParameter.Value = new DoubleArray(inverseLength);
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93 | }
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94 |
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95 | private void GetParameterValues(double[] p, out double scale, out double shape, out double[] inverseLength) {
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96 | int c = 0;
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97 | // gather parameter values
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98 | if (HasFixedInverseLengthParameter) {
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99 | inverseLength = InverseLengthParameter.Value.ToArray();
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100 | } else {
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101 | int length = p.Length;
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102 | if (!HasFixedScaleParameter) length--;
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103 | if (!HasFixedShapeParameter) length--;
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104 | inverseLength = p.Select(e => 1.0 / Math.Exp(e)).Take(length).ToArray();
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105 | c += inverseLength.Length;
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106 | }
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107 | if (HasFixedScaleParameter) {
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108 | scale = ScaleParameter.Value.Value;
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109 | } else {
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110 | scale = Math.Exp(2 * p[c]);
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111 | c++;
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112 | }
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113 | if (HasFixedShapeParameter) {
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114 | shape = ShapeParameter.Value.Value;
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115 | } else {
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116 | shape = Math.Exp(p[c]);
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117 | c++;
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118 | }
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119 | if (p.Length != c) throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovarianceRationalQuadraticArd", "p");
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120 | }
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121 |
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122 | public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, int[] columnIndices) {
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123 | double scale, shape;
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124 | double[] inverseLength;
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125 | GetParameterValues(p, out scale, out shape, out inverseLength);
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126 | var fixedInverseLength = HasFixedInverseLengthParameter;
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127 | var fixedScale = HasFixedScaleParameter;
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128 | var fixedShape = HasFixedShapeParameter;
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129 | // create functions
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130 | var cov = new ParameterizedCovarianceFunction();
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131 | cov.Covariance = (x, i, j) => {
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132 | double d = i == j
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133 | ? 0.0
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134 | : Util.SqrDist(x, i, j, inverseLength, columnIndices);
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135 | return scale * Math.Pow(1 + 0.5 * d / shape, -shape);
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136 | };
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137 | cov.CrossCovariance = (x, xt, i, j) => {
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138 | double d = Util.SqrDist(x, i, xt, j, inverseLength, columnIndices);
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139 | return scale * Math.Pow(1 + 0.5 * d / shape, -shape);
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140 | };
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141 | cov.CovarianceGradient = (x, i, j) => GetGradient(x, i, j, columnIndices, scale, shape, inverseLength, fixedInverseLength, fixedScale, fixedShape);
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142 | return cov;
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143 | }
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144 |
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145 | private static IList<double> GetGradient(double[,] x, int i, int j, int[] columnIndices, double scale, double shape, double[] inverseLength,
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146 | bool fixedInverseLength, bool fixedScale, bool fixedShape) {
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147 | double d = i == j
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148 | ? 0.0
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149 | : Util.SqrDist(x, i, j, inverseLength, columnIndices);
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150 | double b = 1 + 0.5 * d / shape;
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151 | int k = 0;
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152 | var g = new List<double>(columnIndices.Length + 2);
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153 | if (!fixedInverseLength) {
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154 | foreach (var columnIndex in columnIndices) {
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155 | g.Add(
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156 | scale * Math.Pow(b, -shape - 1) *
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157 | Util.SqrDist(x[i, columnIndex] * inverseLength[k], x[j, columnIndex] * inverseLength[k]));
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158 | k++;
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159 | }
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160 | }
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161 | if (!fixedScale) g.Add(2 * scale * Math.Pow(b, -shape));
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162 | if (!fixedShape) g.Add(scale * Math.Pow(b, -shape) * (0.5 * d / b - shape * Math.Log(b)));
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163 | return g;
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164 | }
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165 | }
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166 | }
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