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source: stable/HeuristicLab.Tests/HeuristicLab-3.3/Samples/GaussianProcessRegressionSampleTest.cs @ 12136

Last change on this file since 12136 was 12009, checked in by ascheibe, 10 years ago

#2212 updated copyright year

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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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 HeuristicLab.Algorithms.DataAnalysis;
25using HeuristicLab.Persistence.Default.Xml;
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    [TestMethod]
36    [TestCategory("Samples.Create")]
37    [TestProperty("Time", "medium")]
38    public void CreateGaussianProcessRegressionSampleTest() {
39      var gpr = CreateGaussianProcessRegressionSample();
40      string path = Path.Combine(SamplesUtils.SamplesDirectory, SampleFileName + SamplesUtils.SampleFileExtension);
41      XmlGenerator.Serialize(gpr, path);
42    }
43
44    [TestMethod]
45    [TestCategory("Samples.Execute")]
46    [TestProperty("Time", "long")]
47    public void RunGaussianProcessRegressionSample() {
48      var gpr = CreateGaussianProcessRegressionSample();
49      gpr.SetSeedRandomly = false;
50      gpr.Seed = 1618551877;
51      SamplesUtils.RunAlgorithm(gpr);
52      Assert.AreEqual(-940.39914958616748, SamplesUtils.GetDoubleResult(gpr, "NegativeLogLikelihood"));
53      Assert.AreEqual(0.995614091354263, SamplesUtils.GetDoubleResult(gpr, "Training R²"));
54    }
55
56    private GaussianProcessRegression CreateGaussianProcessRegressionSample() {
57      var gpr = new GaussianProcessRegression();
58      var provider = new VariousInstanceProvider();
59      var instance = provider.GetDataDescriptors().Where(x => x.Name.Contains("Spatial co-evolution")).Single();
60      var regProblem = new RegressionProblem();
61      regProblem.Load(provider.LoadData(instance));
62
63      #region Algorithm Configuration
64      gpr.Name = "Gaussian Process Regression";
65      gpr.Description = "A Gaussian process regression algorithm which solves the spatial co-evolution benchmark problem";
66      gpr.Problem = regProblem;
67
68      gpr.CovarianceFunction = new CovarianceSquaredExponentialIso();
69      gpr.MeanFunction = new MeanConst();
70      gpr.MinimizationIterations = 20;
71      gpr.Seed = 0;
72      gpr.SetSeedRandomly = true;
73      #endregion
74
75      gpr.Engine = new ParallelEngine.ParallelEngine();
76      return gpr;
77    }
78  }
79}
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