[8401] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[11171] | 3 | * Copyright (C) 2002-2014 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[8401] | 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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[8484] | 23 | using System.Collections.Generic;
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[8982] | 24 | using System.Linq.Expressions;
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[8323] | 25 | using HeuristicLab.Common;
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| 26 | using HeuristicLab.Core;
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[8612] | 27 | using HeuristicLab.Data;
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[8982] | 28 | using HeuristicLab.Parameters;
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[8323] | 29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 30 |
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[8371] | 31 | namespace HeuristicLab.Algorithms.DataAnalysis {
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[8323] | 32 | [StorableClass]
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[8615] | 33 | [Item(Name = "CovarianceSquaredExponentialIso",
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[8323] | 34 | Description = "Isotropic squared exponential covariance function for Gaussian processes.")]
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[8615] | 35 | public sealed class CovarianceSquaredExponentialIso : ParameterizedNamedItem, ICovarianceFunction {
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[8982] | 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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[8612] | 39 |
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[8982] | 40 | public IValueParameter<DoubleValue> InverseLengthParameter {
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| 41 | get { return (IValueParameter<DoubleValue>)Parameters["InverseLength"]; }
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| 42 | }
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[8323] | 43 |
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[10489] | 44 | private bool HasFixedInverseLengthParameter {
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| 45 | get { return InverseLengthParameter.Value != null; }
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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 |
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[8323] | 51 | [StorableConstructor]
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[8615] | 52 | private CovarianceSquaredExponentialIso(bool deserializing)
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[8323] | 53 | : base(deserializing) {
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| 54 | }
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| 55 |
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[8615] | 56 | private CovarianceSquaredExponentialIso(CovarianceSquaredExponentialIso original, Cloner cloner)
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[8323] | 57 | : base(original, cloner) {
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| 58 | }
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| 59 |
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[8615] | 60 | public CovarianceSquaredExponentialIso()
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[8323] | 61 | : base() {
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[8612] | 62 | Name = ItemName;
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| 63 | Description = ItemDescription;
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| 64 |
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[8982] | 65 | Parameters.Add(new OptionalValueParameter<DoubleValue>("Scale", "The scale parameter of the isometric squared exponential covariance function."));
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| 66 | Parameters.Add(new OptionalValueParameter<DoubleValue>("InverseLength", "The inverse length parameter of the isometric squared exponential covariance function."));
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[8323] | 67 | }
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| 68 |
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| 69 | public override IDeepCloneable Clone(Cloner cloner) {
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[8615] | 70 | return new CovarianceSquaredExponentialIso(this, cloner);
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[8323] | 71 | }
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| 72 |
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[8982] | 73 | public int GetNumberOfParameters(int numberOfVariables) {
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| 74 | return
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[10489] | 75 | (HasFixedScaleParameter ? 0 : 1) +
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| 76 | (HasFixedInverseLengthParameter ? 0 : 1);
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[8612] | 77 | }
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| 78 |
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[8982] | 79 | public void SetParameter(double[] p) {
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| 80 | double scale, inverseLength;
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| 81 | GetParameterValues(p, out scale, out inverseLength);
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| 82 | ScaleParameter.Value = new DoubleValue(scale);
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| 83 | InverseLengthParameter.Value = new DoubleValue(inverseLength);
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[8612] | 84 | }
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| 85 |
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[8323] | 86 |
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[8982] | 87 | private void GetParameterValues(double[] p, out double scale, out double inverseLength) {
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| 88 | // gather parameter values
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| 89 | int c = 0;
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[10489] | 90 | if (HasFixedInverseLengthParameter) {
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[8982] | 91 | inverseLength = InverseLengthParameter.Value.Value;
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| 92 | } else {
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| 93 | inverseLength = 1.0 / Math.Exp(p[c]);
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| 94 | c++;
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[8612] | 95 | }
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[8982] | 96 |
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[10489] | 97 | if (HasFixedScaleParameter) {
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[8982] | 98 | scale = ScaleParameter.Value.Value;
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| 99 | } else {
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| 100 | scale = Math.Exp(2 * p[c]);
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| 101 | c++;
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[8612] | 102 | }
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[8982] | 103 | if (p.Length != c) throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovarianceSquaredExponentialIso", "p");
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[8416] | 104 | }
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[8323] | 105 |
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[8982] | 106 | public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, IEnumerable<int> columnIndices) {
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| 107 | double inverseLength, scale;
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| 108 | GetParameterValues(p, out scale, out inverseLength);
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[10489] | 109 | var fixedInverseLength = HasFixedInverseLengthParameter;
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| 110 | var fixedScale = HasFixedScaleParameter;
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[8982] | 111 | // create functions
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| 112 | var cov = new ParameterizedCovarianceFunction();
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| 113 | cov.Covariance = (x, i, j) => {
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| 114 | double d = i == j
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| 115 | ? 0.0
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| 116 | : Util.SqrDist(x, i, 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.CrossCovariance = (x, xt, i, j) => {
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| 120 | double d = Util.SqrDist(x, i, xt, j, inverseLength, columnIndices);
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| 121 | return scale * Math.Exp(-d / 2.0);
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| 122 | };
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[10489] | 123 | cov.CovarianceGradient = (x, i, j) => GetGradient(x, i, j, scale, inverseLength, columnIndices,
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| 124 | fixedInverseLength, fixedScale);
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[8982] | 125 | return cov;
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[8323] | 126 | }
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| 127 |
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[9108] | 128 | // order of returned gradients must match the order in GetParameterValues!
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[10489] | 129 | private static IEnumerable<double> GetGradient(double[,] x, int i, int j, double sf2, double inverseLength, IEnumerable<int> columnIndices,
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| 130 | bool fixedInverseLength, bool fixedScale) {
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[8484] | 131 | double d = i == j
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| 132 | ? 0.0
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[8678] | 133 | : Util.SqrDist(x, i, j, inverseLength, columnIndices);
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[8484] | 134 | double g = Math.Exp(-d / 2.0);
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[10489] | 135 | if (!fixedInverseLength) yield return sf2 * g * d;
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| 136 | if (!fixedScale) yield return 2.0 * sf2 * g;
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[8323] | 137 | }
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| 138 | }
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| 139 | }
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