[8417] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[9456] | 3 | * Copyright (C) 2002-2013 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[8417] | 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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[8323] | 21 |
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[8417] | 22 | using System;
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[8484] | 23 | using System.Collections.Generic;
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[8582] | 24 | using System.Linq;
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[8417] | 25 | using HeuristicLab.Common;
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| 26 | using HeuristicLab.Core;
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[8582] | 27 | using HeuristicLab.Data;
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[8982] | 28 | using HeuristicLab.Parameters;
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[8417] | 29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 30 |
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| 31 | namespace HeuristicLab.Algorithms.DataAnalysis {
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| 32 | [StorableClass]
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| 33 | [Item(Name = "CovariancePeriodic", Description = "Periodic covariance function for Gaussian processes.")]
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[8612] | 34 | public sealed class CovariancePeriodic : ParameterizedNamedItem, ICovarianceFunction {
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| 35 |
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[8582] | 36 | public IValueParameter<DoubleValue> ScaleParameter {
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[8982] | 37 | get { return (IValueParameter<DoubleValue>)Parameters["Scale"]; }
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[8582] | 38 | }
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[8612] | 39 |
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[8582] | 40 | public IValueParameter<DoubleValue> InverseLengthParameter {
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[8982] | 41 | get { return (IValueParameter<DoubleValue>)Parameters["InverseLength"]; }
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[8582] | 42 | }
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[8612] | 43 |
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[8582] | 44 | public IValueParameter<DoubleValue> PeriodParameter {
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[8982] | 45 | get { return (IValueParameter<DoubleValue>)Parameters["Period"]; }
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[8582] | 46 | }
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| 47 |
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[10530] | 48 | private bool HasFixedScaleParameter {
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| 49 | get { return ScaleParameter.Value != null; }
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| 50 | }
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| 51 | private bool HasFixedInverseLengthParameter {
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| 52 | get { return InverseLengthParameter.Value != null; }
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| 53 | }
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| 54 | private bool HasFixedPeriodParameter {
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| 55 | get { return PeriodParameter.Value != null; }
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| 56 | }
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[8582] | 57 |
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[10530] | 58 |
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[8417] | 59 | [StorableConstructor]
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[8612] | 60 | private CovariancePeriodic(bool deserializing) : base(deserializing) { }
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| 61 | private CovariancePeriodic(CovariancePeriodic original, Cloner cloner)
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[8417] | 62 | : base(original, cloner) {
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| 63 | }
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[8582] | 64 |
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[8417] | 65 | public CovariancePeriodic()
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| 66 | : base() {
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[8612] | 67 | Name = ItemName;
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| 68 | Description = ItemDescription;
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[8678] | 69 |
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[8982] | 70 | Parameters.Add(new OptionalValueParameter<DoubleValue>("Scale", "The scale of the periodic covariance function."));
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| 71 | Parameters.Add(new OptionalValueParameter<DoubleValue>("InverseLength", "The inverse length parameter for the periodic covariance function."));
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| 72 | Parameters.Add(new OptionalValueParameter<DoubleValue>("Period", "The period parameter for the periodic covariance function."));
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[8417] | 73 | }
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[8323] | 74 |
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[8417] | 75 | public override IDeepCloneable Clone(Cloner cloner) {
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| 76 | return new CovariancePeriodic(this, cloner);
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[8323] | 77 | }
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| 78 |
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[8982] | 79 | public int GetNumberOfParameters(int numberOfVariables) {
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[10530] | 80 | return (HasFixedScaleParameter ? 0 : 1) +
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| 81 | (HasFixedPeriodParameter ? 0 : 1) +
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| 82 | (HasFixedInverseLengthParameter ? 0 : 1);
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[8323] | 83 | }
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| 84 |
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[8982] | 85 | public void SetParameter(double[] p) {
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| 86 | double scale, inverseLength, period;
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| 87 | GetParameterValues(p, out scale, out period, out inverseLength);
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| 88 | ScaleParameter.Value = new DoubleValue(scale);
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| 89 | PeriodParameter.Value = new DoubleValue(period);
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| 90 | InverseLengthParameter.Value = new DoubleValue(inverseLength);
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[8582] | 91 | }
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| 92 |
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[8982] | 93 |
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[10530] | 94 | private void GetParameterValues(double[]
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[9108] | 95 | p, out double scale, out double period, out double inverseLength) {
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[8982] | 96 | // gather parameter values
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| 97 | int c = 0;
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[10530] | 98 | if (HasFixedInverseLengthParameter) {
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[8982] | 99 | inverseLength = InverseLengthParameter.Value.Value;
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| 100 | } else {
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| 101 | inverseLength = 1.0 / Math.Exp(p[c]);
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| 102 | c++;
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[8582] | 103 | }
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[10530] | 104 | if (HasFixedPeriodParameter) {
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[8982] | 105 | period = PeriodParameter.Value.Value;
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| 106 | } else {
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| 107 | period = Math.Exp(p[c]);
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| 108 | c++;
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[8582] | 109 | }
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[10530] | 110 | if (HasFixedScaleParameter) {
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[8982] | 111 | scale = ScaleParameter.Value.Value;
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| 112 | } else {
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| 113 | scale = Math.Exp(2 * p[c]);
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| 114 | c++;
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[8582] | 115 | }
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[8982] | 116 | 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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[8582] | 117 | }
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| 118 |
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[8982] | 119 | public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, IEnumerable<int> columnIndices) {
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| 120 | double inverseLength, period, scale;
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| 121 | GetParameterValues(p, out scale, out period, out inverseLength);
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[10530] | 122 | var fixedInverseLength = HasFixedInverseLengthParameter;
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| 123 | var fixedPeriod = HasFixedPeriodParameter;
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| 124 | var fixedScale = HasFixedScaleParameter;
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[8982] | 125 | // create functions
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| 126 | var cov = new ParameterizedCovarianceFunction();
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| 127 | cov.Covariance = (x, i, j) => {
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| 128 | double k = i == j ? 0.0 : GetDistance(x, x, i, j, columnIndices);
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| 129 | k = Math.PI * k / period;
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| 130 | k = Math.Sin(k) * inverseLength;
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| 131 | k = k * k;
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[8323] | 132 |
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[8982] | 133 | return scale * Math.Exp(-2.0 * k);
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| 134 | };
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| 135 | cov.CrossCovariance = (x, xt, i, j) => {
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| 136 | double k = GetDistance(x, xt, i, j, columnIndices);
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| 137 | k = Math.PI * k / period;
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| 138 | k = Math.Sin(k) * inverseLength;
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| 139 | k = k * k;
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| 140 |
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| 141 | return scale * Math.Exp(-2.0 * k);
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| 142 | };
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[10530] | 143 | cov.CovarianceGradient = (x, i, j) => GetGradient(x, i, j, columnIndices, scale, period, inverseLength, fixedInverseLength, fixedPeriod, fixedScale);
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[8982] | 144 | return cov;
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[8323] | 145 | }
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| 146 |
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[8982] | 147 |
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[10530] | 148 | private static IEnumerable<double> GetGradient(double[,] x, int i, int j, IEnumerable<int> columnIndices, double scale, double period, double inverseLength,
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| 149 | bool fixedInverseLength, bool fixedPeriod, bool fixedScale) {
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[9211] | 150 | double k = i == j ? 0.0 : Math.PI * GetDistance(x, x, i, j, columnIndices) / period;
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| 151 | double gradient = Math.Sin(k) * inverseLength;
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[8484] | 152 | gradient *= gradient;
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[10530] | 153 | if (!fixedInverseLength) yield return 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 | yield return 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 | yield return 2.0 * scale * Math.Exp(-2 * gradient);
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[9211] | 160 |
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[8484] | 161 | }
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| 162 |
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[8982] | 163 | private static double GetDistance(double[,] x, double[,] xt, int i, int j, IEnumerable<int> columnIndices) {
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[8678] | 164 | return Math.Sqrt(Util.SqrDist(x, i, xt, j, 1, columnIndices));
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[8323] | 165 | }
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| 166 | }
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| 167 | }
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