1  #region License Information


2  /* HeuristicLab


3  * Copyright (C) 20022016 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 


22  using System.IO;


23  using HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm;


24  using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;


25  using HeuristicLab.Persistence.Default.Xml;


26  using HeuristicLab.Problems.DataAnalysis.Symbolic;


27  using HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis;


28  using HeuristicLab.Selection;


29  using Microsoft.VisualStudio.TestTools.UnitTesting;


30 


31  namespace HeuristicLab.Tests {


32  [TestClass]


33  public class GPTimeSeriesSampleTest {


34  private const string SampleFileName = "OSGP_TimeSeries";


35 


36  [TestMethod]


37  [TestCategory("Samples.Create")]


38  [TestProperty("Time", "medium")]


39  public void CreateGpTimeSeriesSampleTest() {


40  var ga = CreateGpTimeSeriesSample();


41  string path = Path.Combine(SamplesUtils.SamplesDirectory, SampleFileName + SamplesUtils.SampleFileExtension);


42  XmlGenerator.Serialize(ga, path);


43  }


44  [TestMethod]


45  [TestCategory("Samples.Execute")]


46  [TestProperty("Time", "long")]


47  public void RunGpTimeSeriesSampleTest() {


48  var osga = CreateGpTimeSeriesSample();


49  osga.SetSeedRandomly.Value = false;


50  SamplesUtils.RunAlgorithm(osga);


51 


52  Assert.AreEqual(0.020952753415199643, SamplesUtils.GetDoubleResult(osga, "BestQuality"), 1E8);


53  Assert.AreEqual(0.023220938866319357, SamplesUtils.GetDoubleResult(osga, "CurrentAverageQuality"), 1E8);


54  Assert.AreEqual(0.023716788824595391, SamplesUtils.GetDoubleResult(osga, "CurrentWorstQuality"), 1E8);


55  Assert.AreEqual(48200, SamplesUtils.GetIntResult(osga, "EvaluatedSolutions"));


56  }


57 


58  public static OffspringSelectionGeneticAlgorithm CreateGpTimeSeriesSample() {


59  var problem = new SymbolicTimeSeriesPrognosisSingleObjectiveProblem();


60  problem.Name = "Symbolic time series prognosis problem (Mackey Glass t=17)";


61  problem.ProblemData.Name = "Mackey Glass t=17";


62  problem.MaximumSymbolicExpressionTreeLength.Value = 125;


63  problem.MaximumSymbolicExpressionTreeDepth.Value = 12;


64  problem.EvaluatorParameter.Value.HorizonParameter.Value.Value = 10;


65 


66  foreach (var symbol in problem.SymbolicExpressionTreeGrammar.Symbols) {


67  if (symbol is Exponential  symbol is Logarithm) {


68  symbol.Enabled = false;


69  } else if (symbol is AutoregressiveTargetVariable) {


70  symbol.Enabled = true;


71  var autoRegressiveSymbol = symbol as AutoregressiveTargetVariable;


72  autoRegressiveSymbol.MinLag = 30;


73  autoRegressiveSymbol.MaxLag = 1;


74  }


75  }


76 


77  var osga = new OffspringSelectionGeneticAlgorithm();


78  osga.Name = "Genetic Programming  Time Series Prediction (MackeyGlass17)";


79  osga.Description = "A genetic programming algorithm for creating a timeseries model for the MackeyGlass17 time series.";


80  osga.Problem = problem;


81  SamplesUtils.ConfigureOsGeneticAlgorithmParameters<GenderSpecificSelector, SubtreeCrossover, MultiSymbolicExpressionTreeManipulator>


82  (osga, popSize: 100, elites: 1, maxGens: 25, mutationRate: 0.15);


83  osga.MaximumSelectionPressure.Value = 100;


84  return osga;


85 


86  }


87  }


88  }

