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source: stable/HeuristicLab.Tests/HeuristicLab-3.3/Samples/GaussianProcessRegressionSampleTest.cs @ 17105

Last change on this file since 17105 was 17105, checked in by mkommend, 5 years ago

#2520: Merged 16584, 16585,16594,16595, 16625, 16658, 16659, 16672, 16707, 16729, 16792, 16796, 16797, 16799, 16819, 16906, 16907, 16908, 16933, 16945, 16992, 16994, 16995, 16996, 16997, 17014, 17015, 17017, 17020, 17021, 17022, 17023, 17024, 17029, 17086, 17087, 17088, 17089 into stable.

File size: 3.1 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System.IO;
23using System.Linq;
24using HEAL.Attic;
25using HeuristicLab.Algorithms.DataAnalysis;
26using HeuristicLab.Problems.DataAnalysis;
27using HeuristicLab.Problems.Instances.DataAnalysis;
28using Microsoft.VisualStudio.TestTools.UnitTesting;
29
30namespace HeuristicLab.Tests {
31  [TestClass]
32  public class GaussianProcessRegressionSampleTest {
33    private const string SampleFileName = "GPR";
34
35    private static readonly ProtoBufSerializer serializer = new ProtoBufSerializer();
36
37    [TestMethod]
38    [TestCategory("Samples.Create")]
39    [TestProperty("Time", "medium")]
40    public void CreateGaussianProcessRegressionSampleTest() {
41      var gpr = CreateGaussianProcessRegressionSample();
42      string path = Path.Combine(SamplesUtils.SamplesDirectory, SampleFileName + SamplesUtils.SampleFileExtension);
43      serializer.Serialize(gpr, path);
44    }
45
46    [TestMethod]
47    [TestCategory("Samples.Execute")]
48    [TestProperty("Time", "long")]
49    public void RunGaussianProcessRegressionSample() {
50      var gpr = CreateGaussianProcessRegressionSample();
51      gpr.SetSeedRandomly = false;
52      gpr.Seed = 1618551877;
53      SamplesUtils.RunAlgorithm(gpr);
54      Assert.AreEqual(-940.70700288855619, SamplesUtils.GetDoubleResult(gpr, "NegativeLogLikelihood"));
55      Assert.AreEqual(0.99563390794061979, SamplesUtils.GetDoubleResult(gpr, "Training R²"));
56    }
57
58    private GaussianProcessRegression CreateGaussianProcessRegressionSample() {
59      var gpr = new GaussianProcessRegression();
60      var provider = new VariousInstanceProvider();
61      var instance = provider.GetDataDescriptors().Where(x => x.Name.Contains("Spatial co-evolution")).Single();
62      var regProblem = new RegressionProblem();
63      regProblem.Load(provider.LoadData(instance));
64
65      #region Algorithm Configuration
66      gpr.Name = "Gaussian Process Regression";
67      gpr.Description = "A Gaussian process regression algorithm which solves the spatial co-evolution benchmark problem";
68      gpr.Problem = regProblem;
69
70      gpr.CovarianceFunction = new CovarianceSquaredExponentialIso();
71      gpr.MeanFunction = new MeanConst();
72      gpr.MinimizationIterations = 20;
73      gpr.Seed = 0;
74      gpr.SetSeedRandomly = true;
75      #endregion
76
77      gpr.Engine = new ParallelEngine.ParallelEngine();
78      return gpr;
79    }
80  }
81}
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