1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2016 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.Linq;
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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 HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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29 | using HeuristicLab.PluginInfrastructure;
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30 | using HeuristicLab.Problems.DataAnalysis;
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31 |
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32 | namespace HeuristicLab.Algorithms.DataAnalysis {
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33 | /// <summary>
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34 | ///Gaussian process regression data analysis algorithm.
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35 | /// </summary>
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36 | [Item("Gaussian Process Regression", "Gaussian process regression data analysis algorithm.")]
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37 | [Creatable(CreatableAttribute.Categories.DataAnalysisRegression, Priority = 160)]
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38 | [StorableClass]
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39 | public sealed class GaussianProcessRegression : GaussianProcessBase, IStorableContent {
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40 | public string Filename { get; set; }
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41 |
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42 | public override Type ProblemType {
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43 | get { return typeof(IRegressionProblem); }
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44 | }
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45 | public new IRegressionProblem Problem {
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46 | get { return (IRegressionProblem) base.Problem; }
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47 | set { base.Problem = value; }
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48 | }
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49 |
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50 | private const string ModelParameterName = "Model";
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51 | private const string CreateSolutionParameterName = "CreateSolution";
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52 |
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53 |
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54 | #region parameter properties
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55 | public IConstrainedValueParameter<IGaussianProcessRegressionModelCreator> GaussianProcessModelCreatorParameter {
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56 | get { return (IConstrainedValueParameter<IGaussianProcessRegressionModelCreator>) Parameters[ModelCreatorParameterName]; }
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57 | }
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58 | public IFixedValueParameter<GaussianProcessRegressionSolutionCreator> GaussianProcessSolutionCreatorParameter {
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59 | get { return (IFixedValueParameter<GaussianProcessRegressionSolutionCreator>) Parameters[SolutionCreatorParameterName]; }
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60 | }
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61 | public IFixedValueParameter<BoolValue> CreateSolutionParameter {
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62 | get { return (IFixedValueParameter<BoolValue>) Parameters[CreateSolutionParameterName]; }
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63 | }
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64 | #endregion
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65 | #region properties
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66 | public bool CreateSolution {
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67 | get { return CreateSolutionParameter.Value.Value; }
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68 | set { CreateSolutionParameter.Value.Value = value; }
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69 | }
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70 | #endregion
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71 |
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72 | [StorableConstructor]
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73 | private GaussianProcessRegression(bool deserializing) : base(deserializing) { }
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74 | private GaussianProcessRegression(GaussianProcessRegression original, Cloner cloner)
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75 | : base(original, cloner) {
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76 | RegisterEventHandlers();
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77 | }
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78 | public GaussianProcessRegression()
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79 | : base(new RegressionProblem()) {
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80 | this.name = ItemName;
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81 | this.description = ItemDescription;
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82 |
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83 | var modelCreators = ApplicationManager.Manager.GetInstances<IGaussianProcessRegressionModelCreator>();
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84 | var defaultModelCreator = modelCreators.First(c => c is GaussianProcessRegressionModelCreator);
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85 |
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86 | // GP regression and classification algorithms only differ in the model and solution creators,
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87 | // thus we use a common base class and use operator parameters to implement the specific versions.
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88 | // Different model creators can be implemented,
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89 | // but the solution creator is implemented in a generic fashion already and we don't allow derived solution creators
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90 | Parameters.Add(new ConstrainedValueParameter<IGaussianProcessRegressionModelCreator>(ModelCreatorParameterName, "The operator to create the Gaussian process model.",
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91 | new ItemSet<IGaussianProcessRegressionModelCreator>(modelCreators), defaultModelCreator));
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92 | // the solution creator cannot be changed
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93 | Parameters.Add(new FixedValueParameter<GaussianProcessRegressionSolutionCreator>(SolutionCreatorParameterName, "The solution creator for the algorithm",
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94 | new GaussianProcessRegressionSolutionCreator()));
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95 | Parameters[SolutionCreatorParameterName].Hidden = true;
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96 | // TODO: it would be better to deactivate the solution creator when this parameter is changed
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97 | Parameters.Add(new FixedValueParameter<BoolValue>(CreateSolutionParameterName, "Flag that indicates if a solution should be produced at the end of the run", new BoolValue(true)));
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98 | Parameters[CreateSolutionParameterName].Hidden = true;
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99 |
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100 | ParameterizedModelCreators();
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101 | ParameterizeSolutionCreator(GaussianProcessSolutionCreatorParameter.Value);
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102 | RegisterEventHandlers();
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103 | }
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104 |
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105 |
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106 | [StorableHook(HookType.AfterDeserialization)]
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107 | private void AfterDeserialization() {
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108 | // BackwardsCompatibility3.3
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109 | #region Backwards compatible code, remove with 3.4
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110 | if (!Parameters.ContainsKey(CreateSolutionParameterName)) {
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111 | Parameters.Add(new FixedValueParameter<BoolValue>(CreateSolutionParameterName, "Flag that indicates if a solution should be produced at the end of the run", new BoolValue(true)));
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112 | Parameters[CreateSolutionParameterName].Hidden = true;
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113 | }
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114 | #endregion
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115 | RegisterEventHandlers();
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116 | }
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117 |
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118 | public override IDeepCloneable Clone(Cloner cloner) {
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119 | return new GaussianProcessRegression(this, cloner);
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120 | }
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121 |
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122 | #region events
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123 | private void RegisterEventHandlers() {
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124 | GaussianProcessModelCreatorParameter.ValueChanged += ModelCreatorParameter_ValueChanged;
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125 | }
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126 |
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127 | private void ModelCreatorParameter_ValueChanged(object sender, EventArgs e) {
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128 | ParameterizedModelCreator(GaussianProcessModelCreatorParameter.Value);
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129 | }
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130 | #endregion
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131 |
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132 | private void ParameterizedModelCreators() {
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133 | foreach (var creator in GaussianProcessModelCreatorParameter.ValidValues) {
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134 | ParameterizedModelCreator(creator);
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135 | }
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136 | }
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137 |
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138 | private void ParameterizedModelCreator(IGaussianProcessRegressionModelCreator modelCreator) {
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139 | modelCreator.ProblemDataParameter.ActualName = Problem.ProblemDataParameter.Name;
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140 | modelCreator.MeanFunctionParameter.ActualName = MeanFunctionParameterName;
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141 | modelCreator.CovarianceFunctionParameter.ActualName = CovarianceFunctionParameterName;
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142 |
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143 | // parameter names fixed by the algorithm
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144 | modelCreator.ModelParameter.ActualName = ModelParameterName;
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145 | modelCreator.HyperparameterParameter.ActualName = HyperparameterParameterName;
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146 | modelCreator.HyperparameterGradientsParameter.ActualName = HyperparameterGradientsParameterName;
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147 | modelCreator.NegativeLogLikelihoodParameter.ActualName = NegativeLogLikelihoodParameterName;
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148 | }
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149 |
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150 | private void ParameterizeSolutionCreator(GaussianProcessRegressionSolutionCreator solutionCreator) {
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151 | solutionCreator.ModelParameter.ActualName = ModelParameterName;
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152 | solutionCreator.ProblemDataParameter.ActualName = Problem.ProblemDataParameter.Name;
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153 | }
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154 | }
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155 | } |
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