[11051] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[12012] | 3 | * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[11051] | 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using System.IO;
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| 23 | using HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm;
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| 24 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 25 | using HeuristicLab.Persistence.Default.Xml;
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| 26 | using HeuristicLab.Problems.DataAnalysis.Symbolic;
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| 27 | using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
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| 28 | using HeuristicLab.Problems.Instances.DataAnalysis;
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| 29 | using HeuristicLab.Selection;
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| 30 | using Microsoft.VisualStudio.TestTools.UnitTesting;
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| 31 |
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| 32 | namespace HeuristicLab.Tests {
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| 33 | [TestClass]
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| 34 | public class GPMultiplexerSampleTest {
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[11514] | 35 | private const string SampleFileName = "GP_Multiplexer";
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[11051] | 36 |
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| 37 | [TestMethod]
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| 38 | [TestCategory("Samples.Create")]
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| 39 | [TestProperty("Time", "medium")]
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| 40 | public void CreateGpMultiplexerSampleTest() {
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| 41 | var ga = CreateGpMultiplexerSample();
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[11514] | 42 | string path = Path.Combine(SamplesUtils.SamplesDirectory, SampleFileName + SamplesUtils.SampleFileExtension);
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[11051] | 43 | XmlGenerator.Serialize(ga, path);
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| 44 | }
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| 45 | [TestMethod]
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| 46 | [TestCategory("Samples.Execute")]
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| 47 | [TestProperty("Time", "long")]
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| 48 | public void RunGpMultiplexerSampleTest() {
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| 49 | var osga = CreateGpMultiplexerSample();
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| 50 | osga.SetSeedRandomly.Value = false;
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| 51 | SamplesUtils.RunAlgorithm(osga);
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| 52 |
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| 53 | Assert.AreEqual(0.125, SamplesUtils.GetDoubleResult(osga, "BestQuality"), 1E-8);
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| 54 | Assert.AreEqual(0.237275390625, SamplesUtils.GetDoubleResult(osga, "CurrentAverageQuality"), 1E-8);
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| 55 | Assert.AreEqual(1.181640625, SamplesUtils.GetDoubleResult(osga, "CurrentWorstQuality"), 1E-8);
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| 56 | Assert.AreEqual(105500, SamplesUtils.GetIntResult(osga, "EvaluatedSolutions"));
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| 57 | }
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| 58 |
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| 59 | public static OffspringSelectionGeneticAlgorithm CreateGpMultiplexerSample() {
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| 60 | var instanceProvider = new RegressionCSVInstanceProvider();
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| 61 | var regressionImportType = new RegressionImportType();
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| 62 | regressionImportType.TargetVariable = "output";
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| 63 | regressionImportType.TrainingPercentage = 100;
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| 64 | var dataAnalysisCSVFormat = new DataAnalysisCSVFormat();
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| 65 | dataAnalysisCSVFormat.Separator = ',';
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| 66 | dataAnalysisCSVFormat.VariableNamesAvailable = true;
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| 67 |
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| 68 | var problemData = instanceProvider.ImportData(@"Test Resources\Multiplexer11.csv", regressionImportType, dataAnalysisCSVFormat);
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| 69 | problemData.Name = "11-Multiplexer";
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| 70 |
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| 71 | var problem = new SymbolicRegressionSingleObjectiveProblem();
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| 72 | problem.Name = "11-Multiplexer Problem";
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| 73 | problem.ProblemData = problemData;
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| 74 | problem.MaximumSymbolicExpressionTreeLength.Value = 50;
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| 75 | problem.MaximumSymbolicExpressionTreeDepth.Value = 50;
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| 76 | problem.EvaluatorParameter.Value = new SymbolicRegressionSingleObjectiveMeanSquaredErrorEvaluator();
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| 77 | problem.ApplyLinearScaling.Value = false;
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| 78 |
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| 79 |
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| 80 | var grammar = new FullFunctionalExpressionGrammar();
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| 81 | problem.SymbolicExpressionTreeGrammar = grammar;
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| 82 | foreach (var symbol in grammar.Symbols) {
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| 83 | if (symbol is ProgramRootSymbol) symbol.Enabled = true;
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| 84 | else if (symbol is StartSymbol) symbol.Enabled = true;
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| 85 | else if (symbol is IfThenElse) symbol.Enabled = true;
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| 86 | else if (symbol is And) symbol.Enabled = true;
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| 87 | else if (symbol is Or) symbol.Enabled = true;
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| 88 | else if (symbol is Xor) symbol.Enabled = true;
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| 89 | else if (symbol.GetType() == typeof(Variable)) {
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| 90 | //necessary as there are multiple classes derived from Variable (e.g., VariableCondition)
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| 91 | symbol.Enabled = true;
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| 92 | var variableSymbol = (Variable)symbol;
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| 93 | variableSymbol.MultiplicativeWeightManipulatorSigma = 0.0;
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| 94 | variableSymbol.WeightManipulatorSigma = 0.0;
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| 95 | variableSymbol.WeightSigma = 0.0;
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| 96 | } else symbol.Enabled = false;
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| 97 | }
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| 98 |
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| 99 | var osga = new OffspringSelectionGeneticAlgorithm();
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| 100 | osga.Name = "Genetic Programming - Multiplexer 11 problem";
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| 101 | osga.Description = "A genetic programming algorithm that solves the 11-bit multiplexer problem.";
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| 102 | osga.Problem = problem;
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| 103 | SamplesUtils.ConfigureOsGeneticAlgorithmParameters<GenderSpecificSelector, SubtreeCrossover, MultiSymbolicExpressionTreeManipulator>
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| 104 | (osga, popSize: 100, elites: 1, maxGens: 50, mutationRate: 0.25);
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| 105 | osga.MaximumSelectionPressure.Value = 200;
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| 106 | return osga;
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| 107 |
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| 108 | }
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| 109 | }
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| 110 | }
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