1 | using System;
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2 | using System.Linq;
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3 |
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4 | namespace HeuristicLab.Tests.Problem {
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5 | using System.Threading;
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6 |
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7 | using HeuristicLab.Algorithms.GeneticAlgorithm;
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8 | using HeuristicLab.BenchmarkSuite.Problems;
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9 | using HeuristicLab.Data;
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10 | using HeuristicLab.Encodings.IntegerVectorEncoding;
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11 | using HeuristicLab.Optimization;
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12 | using HeuristicLab.ParallelEngine;
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13 | using HeuristicLab.Problems.ProgramSynthesis.Push.Problem.BenchmarkSuite;
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14 | using HeuristicLab.Problems.ProgramSynthesis.Push.Selector;
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15 |
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16 | using Microsoft.VisualStudio.TestTools.UnitTesting;
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17 |
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18 | [TestClass]
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19 | public class DeterministicTests {
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20 |
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21 | [TestMethod]
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22 | [TestCategory("Problem")]
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23 | [TestProperty("Time", "long")]
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24 | public void TestMedian() {
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25 | var ga = GetAlgorithm();
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26 |
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27 | RunAlgorithm(ga);
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28 | }
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29 |
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30 | [TestMethod]
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31 | [TestCategory("Problem")]
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32 | [TestProperty("Time", "long")]
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33 | public void TestSimilarResult() {
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34 | var ga1 = GetAlgorithm();
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35 | var ga2 = GetAlgorithm();
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36 |
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37 | RunAlgorithm(ga1);
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38 | RunAlgorithm(ga2);
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39 |
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40 | var bestQuality1 = GetDoubleResult(ga1, "BestQuality");
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41 | var bestQuality2 = GetDoubleResult(ga2, "BestQuality");
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42 | Assert.AreEqual(bestQuality1, bestQuality2, 0.000001);
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43 |
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44 | //var currentAverageQuality1 = GetDoubleResult(ga1, "CurrentAverageQuality");
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45 | //var currentAverageQuality2 = GetDoubleResult(ga2, "CurrentAverageQuality");
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46 | //Assert.AreEqual(currentAverageQuality1, currentAverageQuality2, 0.01);
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47 |
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48 | var currentWorstQuality1 = GetDoubleResult(ga1, "CurrentWorstQuality");
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49 | var currentWorstQuality2 = GetDoubleResult(ga2, "CurrentWorstQuality");
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50 | Assert.AreEqual(currentWorstQuality1, currentWorstQuality2, 0.000001);
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51 | }
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52 |
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53 | public static IAlgorithm GetAlgorithm() {
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54 | var ga = new GeneticAlgorithm();
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55 |
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56 | var instance = new Median();
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57 | var problemData = instance.CreateProblemData();
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58 | var pushProblem = new IntegerVectorPushBenchmarkSuiteProblem();
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59 |
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60 | pushProblem.Load(problemData);
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61 |
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62 | ga.Problem = pushProblem;
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63 | pushProblem.Encoding.Length = 100;
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64 |
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65 | ga.Crossover = ga.CrossoverParameter.ValidValues.OfType<SinglePointCrossover>().First();
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66 | ga.Selector = ga.SelectorParameter.ValidValues.OfType<LexicaseSelector>().First();
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67 | ga.Mutator = ga.MutatorParameter.ValidValues.OfType<UniformSomePositionsManipulator>().First();
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68 |
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69 | ga.Seed.Value = 1337;
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70 | ga.SetSeedRandomly.Value = false;
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71 | ga.MutationProbability.Value = 0.05;
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72 | ga.PopulationSize.Value = 1000;
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73 | ga.MaximumGenerations.Value = 10;
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74 |
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75 | ga.Engine = new ParallelEngine();
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76 |
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77 | return ga;
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78 | }
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79 |
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80 | public static void RunAlgorithm(IAlgorithm a) {
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81 | var trigger = new EventWaitHandle(false, EventResetMode.ManualReset);
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82 | Exception ex = null;
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83 | a.Stopped += (src, e) => trigger.Set();
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84 | a.ExceptionOccurred += (src, e) => { ex = e.Value; trigger.Set(); };
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85 | a.Prepare();
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86 | a.Start();
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87 | trigger.WaitOne();
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88 |
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89 | Assert.AreEqual(ex, null);
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90 | }
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91 |
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92 | public static double GetDoubleResult(IAlgorithm a, string resultName) {
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93 | return ((DoubleValue)a.Results[resultName].Value).Value;
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94 | }
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95 | }
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96 | }
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