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source: branches/ALPS/HeuristicLab.Tests/HeuristicLab-3.3/Samples/PsoSchwefelSampleTest.cs @ 11655

Last change on this file since 11655 was 11450, checked in by bburlacu, 10 years ago

#2211: Separated samples class into separate test classes. Added scripts unit tests (grid search classification/regression).

File size: 5.6 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2014 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;
23using System.IO;
24using System.Linq;
25using HeuristicLab.Algorithms.ParticleSwarmOptimization;
26using HeuristicLab.Data;
27using HeuristicLab.Encodings.RealVectorEncoding;
28using HeuristicLab.Optimization.Operators;
29using HeuristicLab.Persistence.Default.Xml;
30using HeuristicLab.Problems.TestFunctions;
31using Microsoft.VisualStudio.TestTools.UnitTesting;
32
33namespace HeuristicLab.Tests {
34  /// <summary>
35  /// Summary description for PsoSchwefelSampleTest
36  /// </summary>
37  [TestClass]
38  public class PsoSchwefelSampleTest {
39    private const string samplesDirectory = SamplesUtils.Directory;
40    [ClassInitialize]
41    public static void MyClassInitialize(TestContext testContext) {
42      if (!Directory.Exists(samplesDirectory))
43        Directory.CreateDirectory(samplesDirectory);
44    }
45
46    [TestMethod]
47    [TestCategory("Samples.Create")]
48    [TestProperty("Time", "medium")]
49    public void CreatePsoSchwefelSampleTest() {
50      var pso = CreatePsoSchwefelSample();
51      XmlGenerator.Serialize(pso, @"Samples\PSO_Schwefel.hl");
52    }
53    [TestMethod]
54    [TestCategory("Samples.Execute")]
55    [TestProperty("Time", "medium")]
56    public void RunPsoSchwefelSampleTest() {
57      var pso = CreatePsoSchwefelSample();
58      pso.SetSeedRandomly.Value = false;
59      SamplesUtils.RunAlgorithm(pso);
60      if (!Environment.Is64BitProcess) {
61        Assert.AreEqual(118.44027985932837, SamplesUtils.GetDoubleResult(pso, "BestQuality"));
62        Assert.AreEqual(140.71570105946438, SamplesUtils.GetDoubleResult(pso, "CurrentAverageQuality"));
63        Assert.AreEqual(220.956806502853, SamplesUtils.GetDoubleResult(pso, "CurrentWorstQuality"));
64        Assert.AreEqual(1000, SamplesUtils.GetIntResult(pso, "Iterations"));
65      } else {
66        Assert.AreEqual(118.43958282879345, SamplesUtils.GetDoubleResult(pso, "BestQuality"));
67        Assert.AreEqual(139.43946864779372, SamplesUtils.GetDoubleResult(pso, "CurrentAverageQuality"));
68        Assert.AreEqual(217.14654589055152, SamplesUtils.GetDoubleResult(pso, "CurrentWorstQuality"));
69        Assert.AreEqual(1000, SamplesUtils.GetIntResult(pso, "Iterations"));
70      }
71    }
72
73    private ParticleSwarmOptimization CreatePsoSchwefelSample() {
74      ParticleSwarmOptimization pso = new ParticleSwarmOptimization();
75      #region Problem Configuration
76      var problem = new SingleObjectiveTestFunctionProblem();
77      problem.BestKnownQuality.Value = 0.0;
78      problem.BestKnownSolutionParameter.Value = new RealVector(new double[] { 420.968746, 420.968746 });
79      problem.Bounds = new DoubleMatrix(new double[,] { { -500, 500 } });
80      problem.EvaluatorParameter.Value = new SchwefelEvaluator();
81      problem.Maximization.Value = false;
82      problem.ProblemSize.Value = 2;
83      problem.SolutionCreatorParameter.Value = new UniformRandomRealVectorCreator();
84      #endregion
85      #region Algorithm Configuration
86      pso.Name = "Particle Swarm Optimization - Schwefel";
87      pso.Description = "A particle swarm optimization algorithm which solves the 2-dimensional Schwefel test function (based on the description in Pedersen, M.E.H. (2010). PhD thesis. University of Southampton)";
88      pso.Problem = problem;
89      pso.Inertia.Value = 10;
90      pso.MaxIterations.Value = 1000;
91      pso.NeighborBestAttraction.Value = 0.5;
92      pso.PersonalBestAttraction.Value = -0.01;
93      pso.SwarmSize.Value = 50;
94
95      var inertiaUpdater = pso.InertiaUpdaterParameter.ValidValues
96        .OfType<ExponentialDiscreteDoubleValueModifier>()
97        .Single();
98      inertiaUpdater.StartValueParameter.Value = new DoubleValue(10);
99      inertiaUpdater.EndValueParameter.Value = new DoubleValue(1);
100      pso.InertiaUpdater = inertiaUpdater;
101
102      pso.ParticleCreator = pso.ParticleCreatorParameter.ValidValues
103        .OfType<RealVectorParticleCreator>()
104        .Single();
105      var swarmUpdater = pso.SwarmUpdaterParameter.ValidValues
106        .OfType<RealVectorSwarmUpdater>()
107        .Single();
108      swarmUpdater.VelocityBoundsIndexParameter.ActualName = "Iterations";
109      swarmUpdater.VelocityBoundsParameter.Value = new DoubleMatrix(new double[,] { { -10, 10 } });
110      swarmUpdater.VelocityBoundsStartValueParameter.Value = new DoubleValue(10.0);
111      swarmUpdater.VelocityBoundsEndValueParameter.Value = new DoubleValue(1.0);
112      swarmUpdater.VelocityBoundsScalingOperatorParameter.Value = swarmUpdater.VelocityBoundsScalingOperatorParameter.ValidValues
113        .OfType<ExponentialDiscreteDoubleValueModifier>()
114        .Single();
115
116      pso.TopologyInitializer = null;
117      pso.TopologyUpdater = null;
118      pso.SwarmUpdater = swarmUpdater;
119      pso.Seed.Value = 0;
120      pso.SetSeedRandomly.Value = true;
121      #endregion
122      pso.Engine = new ParallelEngine.ParallelEngine();
123      return pso;
124    }
125  }
126}
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