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 HeuristicLab.Common;
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25 | using HeuristicLab.Core;
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26 | using HeuristicLab.Data;
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27 | using HeuristicLab.Parameters;
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28 | using HEAL.Attic;
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29 |
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30 | namespace HeuristicLab.Algorithms.DataAnalysis {
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31 | [StorableType("198B5472-6CAA-4C39-BB1F-6EC16CB7801B")]
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32 | [Item(Name = "CovariancePeriodic", Description = "Periodic covariance function for Gaussian processes.")]
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33 | public sealed class CovariancePeriodic : ParameterizedNamedItem, ICovarianceFunction {
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34 |
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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<DoubleValue> InverseLengthParameter {
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40 | get { return (IValueParameter<DoubleValue>)Parameters["InverseLength"]; }
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41 | }
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42 |
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43 | public IValueParameter<DoubleValue> PeriodParameter {
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44 | get { return (IValueParameter<DoubleValue>)Parameters["Period"]; }
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45 | }
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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 HasFixedPeriodParameter {
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54 | get { return PeriodParameter.Value != null; }
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55 | }
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56 |
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57 |
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58 | [StorableConstructor]
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59 | private CovariancePeriodic(StorableConstructorFlag _) : base(_) { }
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60 | private CovariancePeriodic(CovariancePeriodic original, Cloner cloner)
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61 | : base(original, cloner) {
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62 | }
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63 |
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64 | public CovariancePeriodic()
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65 | : base() {
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66 | Name = ItemName;
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67 | Description = ItemDescription;
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68 |
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69 | Parameters.Add(new OptionalValueParameter<DoubleValue>("Scale", "The scale of the periodic covariance function."));
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70 | Parameters.Add(new OptionalValueParameter<DoubleValue>("InverseLength", "The inverse length parameter for the periodic covariance function."));
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71 | Parameters.Add(new OptionalValueParameter<DoubleValue>("Period", "The period parameter for the periodic covariance function."));
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72 | }
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73 |
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74 | public override IDeepCloneable Clone(Cloner cloner) {
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75 | return new CovariancePeriodic(this, cloner);
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76 | }
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77 |
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78 | public int GetNumberOfParameters(int numberOfVariables) {
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79 | return (HasFixedScaleParameter ? 0 : 1) +
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80 | (HasFixedPeriodParameter ? 0 : 1) +
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81 | (HasFixedInverseLengthParameter ? 0 : 1);
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82 | }
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83 |
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84 | public void SetParameter(double[] p) {
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85 | double scale, inverseLength, period;
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86 | GetParameterValues(p, out scale, out period, out inverseLength);
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87 | ScaleParameter.Value = new DoubleValue(scale);
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88 | PeriodParameter.Value = new DoubleValue(period);
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89 | InverseLengthParameter.Value = new DoubleValue(inverseLength);
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90 | }
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91 |
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92 |
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93 | private void GetParameterValues(double[]
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94 | p, out double scale, out double period, out double inverseLength) {
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95 | // gather parameter values
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96 | int c = 0;
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97 | if (HasFixedInverseLengthParameter) {
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98 | inverseLength = InverseLengthParameter.Value.Value;
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99 | } else {
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100 | inverseLength = 1.0 / Math.Exp(p[c]);
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101 | c++;
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102 | }
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103 | if (HasFixedPeriodParameter) {
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104 | period = PeriodParameter.Value.Value;
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105 | } else {
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106 | period = Math.Exp(p[c]);
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107 | c++;
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108 | }
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109 | if (HasFixedScaleParameter) {
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110 | scale = ScaleParameter.Value.Value;
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111 | } else {
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112 | scale = Math.Exp(2 * p[c]);
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113 | c++;
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114 | }
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115 | if (p.Length != c) throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovariancePeriodic", "p");
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116 | }
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117 |
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118 | public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, int[] columnIndices) {
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119 | double inverseLength, period, scale;
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120 | GetParameterValues(p, out scale, out period, out inverseLength);
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121 | var fixedInverseLength = HasFixedInverseLengthParameter;
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122 | var fixedPeriod = HasFixedPeriodParameter;
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123 | var fixedScale = HasFixedScaleParameter;
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124 | // create functions
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125 | var cov = new ParameterizedCovarianceFunction();
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126 | cov.Covariance = (x, i, j) => {
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127 | double k = i == j ? 0.0 : GetDistance(x, x, i, j, columnIndices);
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128 | k = Math.PI * k / period;
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129 | k = Math.Sin(k) * inverseLength;
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130 | k = k * k;
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131 |
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132 | return scale * Math.Exp(-2.0 * k);
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133 | };
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134 | cov.CrossCovariance = (x, xt, i, j) => {
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135 | double k = GetDistance(x, xt, i, j, columnIndices);
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136 | k = Math.PI * k / period;
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137 | k = Math.Sin(k) * inverseLength;
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138 | k = k * k;
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139 |
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140 | return scale * Math.Exp(-2.0 * k);
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141 | };
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142 | cov.CovarianceGradient = (x, i, j) => GetGradient(x, i, j, columnIndices, scale, period, inverseLength, fixedInverseLength, fixedPeriod, fixedScale);
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143 | return cov;
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144 | }
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145 |
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146 | private static IList<double> GetGradient(double[,] x, int i, int j, int[] columnIndices, double scale, double period, double inverseLength,
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147 | bool fixedInverseLength, bool fixedPeriod, bool fixedScale) {
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148 | double k = i == j ? 0.0 : Math.PI * GetDistance(x, x, i, j, columnIndices) / period;
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149 | double gradient = Math.Sin(k) * inverseLength;
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150 | gradient *= gradient;
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151 | var g = new List<double>(3);
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152 | if (!fixedInverseLength)
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153 | g.Add(4.0 * scale * Math.Exp(-2.0 * gradient) * gradient);
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154 | if (!fixedPeriod) {
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155 | double r = Math.Sin(k) * inverseLength;
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156 | g.Add(2.0 * k * scale * Math.Exp(-2 * r * r) * Math.Sin(2 * k) * inverseLength * inverseLength);
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157 | }
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158 | if (!fixedScale)
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159 | g.Add(2.0 * scale * Math.Exp(-2 * gradient));
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160 | return g;
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161 | }
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162 |
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163 | private static double GetDistance(double[,] x, double[,] xt, int i, int j, int[] columnIndices) {
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164 | return Math.Sqrt(Util.SqrDist(x, i, xt, j, columnIndices, 1));
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165 | }
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166 | }
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167 | }
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