[8464] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[16565] | 3 | * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[8464] | 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 HeuristicLab.Common;
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| 24 | using HeuristicLab.Core;
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[8612] | 25 | using HeuristicLab.Data;
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[8982] | 26 | using HeuristicLab.Parameters;
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[16565] | 27 | using HEAL.Attic;
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[8464] | 28 |
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| 29 | namespace HeuristicLab.Algorithms.DataAnalysis {
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[16565] | 30 | [StorableType("C6AEEC11-1F8D-40D1-8D8A-DCCCE886E46C")]
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[8464] | 31 | [Item(Name = "CovarianceNoise",
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| 32 | Description = "Noise covariance function for Gaussian processes.")]
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[8612] | 33 | public sealed class CovarianceNoise : ParameterizedNamedItem, ICovarianceFunction {
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| 34 | public IValueParameter<DoubleValue> ScaleParameter {
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[8982] | 35 | get { return (IValueParameter<DoubleValue>)Parameters["Scale"]; }
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[8612] | 36 | }
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[10489] | 37 | private bool HasFixedScaleParameter {
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| 38 | get { return ScaleParameter.Value != null; }
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| 39 | }
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[8464] | 40 |
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| 41 | [StorableConstructor]
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[16565] | 42 | private CovarianceNoise(StorableConstructorFlag _) : base(_) {
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[8464] | 43 | }
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| 44 |
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[8612] | 45 | private CovarianceNoise(CovarianceNoise original, Cloner cloner)
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[8464] | 46 | : base(original, cloner) {
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| 47 | }
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| 48 |
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| 49 | public CovarianceNoise()
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| 50 | : base() {
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[8612] | 51 | Name = ItemName;
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| 52 | Description = ItemDescription;
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| 53 |
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[8982] | 54 | Parameters.Add(new OptionalValueParameter<DoubleValue>("Scale", "The scale of noise."));
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[8464] | 55 | }
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| 56 |
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| 57 | public override IDeepCloneable Clone(Cloner cloner) {
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| 58 | return new CovarianceNoise(this, cloner);
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| 59 | }
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| 60 |
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[8982] | 61 | public int GetNumberOfParameters(int numberOfVariables) {
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[10489] | 62 | return HasFixedScaleParameter ? 0 : 1;
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[8612] | 63 | }
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| 64 |
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[8982] | 65 | public void SetParameter(double[] p) {
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| 66 | double scale;
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| 67 | GetParameterValues(p, out scale);
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| 68 | ScaleParameter.Value = new DoubleValue(scale);
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[8612] | 69 | }
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| 70 |
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[8982] | 71 | private void GetParameterValues(double[] p, out double scale) {
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| 72 | int c = 0;
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| 73 | // gather parameter values
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[10489] | 74 | if (HasFixedScaleParameter) {
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[8982] | 75 | scale = ScaleParameter.Value.Value;
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[8612] | 76 | } else {
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[8982] | 77 | scale = Math.Exp(2 * p[c]);
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| 78 | c++;
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[8612] | 79 | }
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[8982] | 80 | if (p.Length != c) throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovarianceNoise", "p");
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[8464] | 81 | }
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| 82 |
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[13721] | 83 | public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, int[] columnIndices) {
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[8982] | 84 | double scale;
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| 85 | GetParameterValues(p, out scale);
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[10489] | 86 | var fixedScale = HasFixedScaleParameter;
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[8982] | 87 | // create functions
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| 88 | var cov = new ParameterizedCovarianceFunction();
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| 89 | cov.Covariance = (x, i, j) => i == j ? scale : 0.0;
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[13721] | 90 | cov.CrossCovariance = (x, xt, i, j) => Util.SqrDist(x, i, xt, j, columnIndices, 1.0) < 1e-9 ? scale : 0.0;
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[10489] | 91 | if (fixedScale)
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[13784] | 92 | cov.CovarianceGradient = (x, i, j) => new double[0];
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[10489] | 93 | else
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[13784] | 94 | cov.CovarianceGradient = (x, i, j) => new double[1] { i == j ? 2.0 * scale : 0.0 };
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[8982] | 95 | return cov;
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[8464] | 96 | }
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| 97 | }
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| 98 | }
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