1 |
|
---|
2 | #region License Information
|
---|
3 | /* HeuristicLab
|
---|
4 | * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
|
---|
5 | *
|
---|
6 | * This file is part of HeuristicLab.
|
---|
7 | *
|
---|
8 | * HeuristicLab is free software: you can redistribute it and/or modify
|
---|
9 | * it under the terms of the GNU General Public License as published by
|
---|
10 | * the Free Software Foundation, either version 3 of the License, or
|
---|
11 | * (at your option) any later version.
|
---|
12 | *
|
---|
13 | * HeuristicLab is distributed in the hope that it will be useful,
|
---|
14 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
|
---|
15 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
---|
16 | * GNU General Public License for more details.
|
---|
17 | *
|
---|
18 | * You should have received a copy of the GNU General Public License
|
---|
19 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
|
---|
20 | */
|
---|
21 | #endregion
|
---|
22 |
|
---|
23 | using System;
|
---|
24 | using System.Linq;
|
---|
25 | using HeuristicLab.Common;
|
---|
26 | using HeuristicLab.Core;
|
---|
27 | using HeuristicLab.Data;
|
---|
28 | using HeuristicLab.Parameters;
|
---|
29 | using HEAL.Attic;
|
---|
30 | using HeuristicLab.PluginInfrastructure;
|
---|
31 | using HeuristicLab.Problems.DataAnalysis;
|
---|
32 |
|
---|
33 | namespace HeuristicLab.Algorithms.DataAnalysis {
|
---|
34 | /// <summary>
|
---|
35 | ///Gaussian process regression data analysis algorithm.
|
---|
36 | /// </summary>
|
---|
37 | [Item("Gaussian Process Regression", "Gaussian process regression data analysis algorithm.")]
|
---|
38 | [Creatable(CreatableAttribute.Categories.DataAnalysisRegression, Priority = 160)]
|
---|
39 | [StorableType("3A1DF0A2-66D1-47BB-8BE4-23003BD34271")]
|
---|
40 | public sealed class GaussianProcessRegression : GaussianProcessBase, IStorableContent, IDataAnalysisAlgorithm<IRegressionProblem> {
|
---|
41 | public string Filename { get; set; }
|
---|
42 |
|
---|
43 | public override Type ProblemType { get { return typeof(IRegressionProblem); } }
|
---|
44 | public new IRegressionProblem Problem {
|
---|
45 | get { return (IRegressionProblem)base.Problem; }
|
---|
46 | set { base.Problem = value; }
|
---|
47 | }
|
---|
48 |
|
---|
49 | private const string ModelParameterName = "Model";
|
---|
50 | private const string CreateSolutionParameterName = "CreateSolution";
|
---|
51 |
|
---|
52 |
|
---|
53 | #region parameter properties
|
---|
54 | public IConstrainedValueParameter<IGaussianProcessRegressionModelCreator> GaussianProcessModelCreatorParameter {
|
---|
55 | get { return (IConstrainedValueParameter<IGaussianProcessRegressionModelCreator>)Parameters[ModelCreatorParameterName]; }
|
---|
56 | }
|
---|
57 | public IFixedValueParameter<GaussianProcessRegressionSolutionCreator> GaussianProcessSolutionCreatorParameter {
|
---|
58 | get { return (IFixedValueParameter<GaussianProcessRegressionSolutionCreator>)Parameters[SolutionCreatorParameterName]; }
|
---|
59 | }
|
---|
60 | public IFixedValueParameter<BoolValue> CreateSolutionParameter {
|
---|
61 | get { return (IFixedValueParameter<BoolValue>)Parameters[CreateSolutionParameterName]; }
|
---|
62 | }
|
---|
63 | #endregion
|
---|
64 | #region properties
|
---|
65 | public bool CreateSolution {
|
---|
66 | get { return CreateSolutionParameter.Value.Value; }
|
---|
67 | set { CreateSolutionParameter.Value.Value = value; }
|
---|
68 | }
|
---|
69 | #endregion
|
---|
70 |
|
---|
71 | [StorableConstructor]
|
---|
72 | private GaussianProcessRegression(StorableConstructorFlag _) : base(_) { }
|
---|
73 | private GaussianProcessRegression(GaussianProcessRegression original, Cloner cloner)
|
---|
74 | : base(original, cloner) {
|
---|
75 | RegisterEventHandlers();
|
---|
76 | }
|
---|
77 | public GaussianProcessRegression()
|
---|
78 | : base(new RegressionProblem()) {
|
---|
79 | this.name = ItemName;
|
---|
80 | this.description = ItemDescription;
|
---|
81 |
|
---|
82 | var modelCreators = ApplicationManager.Manager.GetInstances<IGaussianProcessRegressionModelCreator>();
|
---|
83 | var defaultModelCreator = modelCreators.First(c => c is GaussianProcessRegressionModelCreator);
|
---|
84 |
|
---|
85 | // GP regression and classification algorithms only differ in the model and solution creators,
|
---|
86 | // thus we use a common base class and use operator parameters to implement the specific versions.
|
---|
87 | // Different model creators can be implemented,
|
---|
88 | // but the solution creator is implemented in a generic fashion already and we don't allow derived solution creators
|
---|
89 | Parameters.Add(new ConstrainedValueParameter<IGaussianProcessRegressionModelCreator>(ModelCreatorParameterName, "The operator to create the Gaussian process model.",
|
---|
90 | new ItemSet<IGaussianProcessRegressionModelCreator>(modelCreators), defaultModelCreator));
|
---|
91 | // the solution creator cannot be changed
|
---|
92 | Parameters.Add(new FixedValueParameter<GaussianProcessRegressionSolutionCreator>(SolutionCreatorParameterName, "The solution creator for the algorithm",
|
---|
93 | new GaussianProcessRegressionSolutionCreator()));
|
---|
94 | Parameters[SolutionCreatorParameterName].Hidden = true;
|
---|
95 | // TODO: it would be better to deactivate the solution creator when this parameter is changed
|
---|
96 | Parameters.Add(new FixedValueParameter<BoolValue>(CreateSolutionParameterName, "Flag that indicates if a solution should be produced at the end of the run", new BoolValue(true)));
|
---|
97 | Parameters[CreateSolutionParameterName].Hidden = true;
|
---|
98 |
|
---|
99 | ParameterizedModelCreators();
|
---|
100 | ParameterizeSolutionCreator(GaussianProcessSolutionCreatorParameter.Value);
|
---|
101 | RegisterEventHandlers();
|
---|
102 | }
|
---|
103 |
|
---|
104 |
|
---|
105 | [StorableHook(HookType.AfterDeserialization)]
|
---|
106 | private void AfterDeserialization() {
|
---|
107 | // BackwardsCompatibility3.3
|
---|
108 | #region Backwards compatible code, remove with 3.4
|
---|
109 | if (!Parameters.ContainsKey(CreateSolutionParameterName)) {
|
---|
110 | Parameters.Add(new FixedValueParameter<BoolValue>(CreateSolutionParameterName, "Flag that indicates if a solution should be produced at the end of the run", new BoolValue(true)));
|
---|
111 | Parameters[CreateSolutionParameterName].Hidden = true;
|
---|
112 | }
|
---|
113 | #endregion
|
---|
114 | RegisterEventHandlers();
|
---|
115 | }
|
---|
116 |
|
---|
117 | public override IDeepCloneable Clone(Cloner cloner) {
|
---|
118 | return new GaussianProcessRegression(this, cloner);
|
---|
119 | }
|
---|
120 |
|
---|
121 | #region events
|
---|
122 | private void RegisterEventHandlers() {
|
---|
123 | GaussianProcessModelCreatorParameter.ValueChanged += ModelCreatorParameter_ValueChanged;
|
---|
124 | }
|
---|
125 |
|
---|
126 | private void ModelCreatorParameter_ValueChanged(object sender, EventArgs e) {
|
---|
127 | ParameterizedModelCreator(GaussianProcessModelCreatorParameter.Value);
|
---|
128 | }
|
---|
129 | #endregion
|
---|
130 |
|
---|
131 | private void ParameterizedModelCreators() {
|
---|
132 | foreach (var creator in GaussianProcessModelCreatorParameter.ValidValues) {
|
---|
133 | ParameterizedModelCreator(creator);
|
---|
134 | }
|
---|
135 | }
|
---|
136 |
|
---|
137 | private void ParameterizedModelCreator(IGaussianProcessRegressionModelCreator modelCreator) {
|
---|
138 | modelCreator.ProblemDataParameter.ActualName = Problem.ProblemDataParameter.Name;
|
---|
139 | modelCreator.MeanFunctionParameter.ActualName = MeanFunctionParameterName;
|
---|
140 | modelCreator.CovarianceFunctionParameter.ActualName = CovarianceFunctionParameterName;
|
---|
141 |
|
---|
142 | // parameter names fixed by the algorithm
|
---|
143 | modelCreator.ModelParameter.ActualName = ModelParameterName;
|
---|
144 | modelCreator.HyperparameterParameter.ActualName = HyperparameterParameterName;
|
---|
145 | modelCreator.HyperparameterGradientsParameter.ActualName = HyperparameterGradientsParameterName;
|
---|
146 | modelCreator.NegativeLogLikelihoodParameter.ActualName = NegativeLogLikelihoodParameterName;
|
---|
147 | }
|
---|
148 |
|
---|
149 | private void ParameterizeSolutionCreator(GaussianProcessRegressionSolutionCreator solutionCreator) {
|
---|
150 | solutionCreator.ModelParameter.ActualName = ModelParameterName;
|
---|
151 | solutionCreator.ProblemDataParameter.ActualName = Problem.ProblemDataParameter.Name;
|
---|
152 | }
|
---|
153 | }
|
---|
154 | }
|
---|