Changeset 9363 for branches/OaaS/HeuristicLab.Tests/HeuristicLab-3.3/SamplesTest.cs

Timestamp:

04/16/13 13:13:41 (11 years ago)

Author:

spimming

Message:

#1888:

• Merged revisions from trunk

Location:

branches/OaaS

Files:

• . (modified) (2 props)
• HeuristicLab.Tests (modified) (2 props)
• HeuristicLab.Tests/HeuristicLab-3.3/SamplesTest.cs (modified) (16 diffs)

branches/OaaS

@@ -21 +21 @@
 protoc.exe
 _ReSharper.HeuristicLab 3.3 Tests
+Google.ProtocolBuffers-2.4.1.473.dll
 packages

@@ -21 +21 @@
 protoc.exe
 _ReSharper.HeuristicLab 3.3 Tests
+Google.ProtocolBuffers-2.4.1.473.dll
 packages

branches/OaaS/HeuristicLab.Tests

@@ -4 +4 @@
 *.vs10x
 _ReSharper.HeuristicLab 3.3 Tests
+*.user
+*.suo

@@ -4 +4 @@
 *.vs10x
 _ReSharper.HeuristicLab 3.3 Tests
+*.user
+*.suo

branches/OaaS/HeuristicLab.Tests/HeuristicLab-3.3/SamplesTest.cs

@@ -23 +23 @@
 using System.Linq;
 using System.Threading;
+using HeuristicLab.Algorithms.DataAnalysis;
 using HeuristicLab.Algorithms.EvolutionStrategy;
 using HeuristicLab.Algorithms.GeneticAlgorithm;
 using HeuristicLab.Algorithms.LocalSearch;
 using HeuristicLab.Algorithms.ParticleSwarmOptimization;
+using HeuristicLab.Algorithms.RAPGA;
+using HeuristicLab.Algorithms.ScatterSearch;
 using HeuristicLab.Algorithms.SimulatedAnnealing;
 using HeuristicLab.Algorithms.TabuSearch;
@@ -34 +37 @@
 using HeuristicLab.Encodings.PermutationEncoding;
 using HeuristicLab.Encodings.RealVectorEncoding;
+using HeuristicLab.Encodings.ScheduleEncoding.JobSequenceMatrix;
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
 using HeuristicLab.Optimization;
@@ -49 +53 @@
 using HeuristicLab.Problems.Instances.VehicleRouting;
 using HeuristicLab.Problems.Knapsack;
+using HeuristicLab.Problems.Scheduling;
 using HeuristicLab.Problems.TestFunctions;
 using HeuristicLab.Problems.TravelingSalesman;
@@ -56 +61 @@
 using HeuristicLab.Problems.VehicleRouting.ProblemInstances;
 using HeuristicLab.Selection;
+using HeuristicLab.SequentialEngine;
 using Microsoft.VisualStudio.TestTools.UnitTesting;
 
@@ -97 +103 @@
       ConfigureGeneticAlgorithmParameters<ProportionalSelector, OrderCrossover2, InversionManipulator>(
         ga, 100, 1, 1000, 0.05);
-
-      ga.Analyzer.Operators.SetItemCheckedState(ga.Analyzer.Operators
-        .OfType<TSPAlleleFrequencyAnalyzer>()
-        .Single(), false);
-      ga.Analyzer.Operators.SetItemCheckedState(ga.Analyzer.Operators
-        .OfType<TSPPopulationDiversityAnalyzer>()
-        .Single(), false);
       #endregion
       return ga;
@@ -132 +131 @@
 
       SolomonFormatInstanceProvider instanceProvider = new SolomonInstanceProvider();
-      IVRPData data = instanceProvider.Import("C101.txt", "C101.opt.txt");
+      CVRPTWData data = instanceProvider.Import("C101.txt", "C101.opt.txt") as CVRPTWData;
       vrpProblem.Load(data);
       vrpProblem.Name = "C101 VRP (imported from Solomon)";
@@ -190 +189 @@
       ga.SetSeedRandomly.Value = false;
       RunAlgorithm(ga);
-      Assert.AreEqual(67, GetDoubleResult(ga, "BestQuality"));
-      Assert.AreEqual(45.813, GetDoubleResult(ga, "CurrentAverageQuality"));
+      Assert.AreEqual(81, GetDoubleResult(ga, "BestQuality"));
+      Assert.AreEqual(48.19, GetDoubleResult(ga, "CurrentAverageQuality"));
       Assert.AreEqual(0, GetDoubleResult(ga, "CurrentWorstQuality"));
       Assert.AreEqual(50950, GetIntResult(ga, "EvaluatedSolutions"));
@@ -241 +240 @@
       ga.SetSeedRandomly.Value = false;
       RunAlgorithm(ga);
-      Assert.AreEqual(0.78855594192122458, GetDoubleResult(ga, "BestQuality"), 1E-8);
-      Assert.AreEqual(0.61395271071681523, GetDoubleResult(ga, "CurrentAverageQuality"), 1E-8);
+      Assert.AreEqual(0.858344291534625, GetDoubleResult(ga, "BestQuality"), 1E-8);
+      Assert.AreEqual(0.56758466520692641, GetDoubleResult(ga, "CurrentAverageQuality"), 1E-8);
       Assert.AreEqual(0, GetDoubleResult(ga, "CurrentWorstQuality"), 1E-8);
       Assert.AreEqual(50950, GetIntResult(ga, "EvaluatedSolutions"));
@@ -252 +251 @@
       SymbolicRegressionSingleObjectiveProblem symbRegProblem = new SymbolicRegressionSingleObjectiveProblem();
       symbRegProblem.Name = "Tower Symbolic Regression Problem";
-      symbRegProblem.Description = "Tower Dataset (downloaded from: http://vanillamodeling.com/realproblems.html)";
+      symbRegProblem.Description = "Tower Dataset (downloaded from: http://www.symbolicregression.com/?q=towerProblem)";
       RegressionRealWorldInstanceProvider provider = new RegressionRealWorldInstanceProvider();
-      var instance = provider.GetDataDescriptors().Where(x => x.Name.Equals("TowerData")).Single();
+      var instance = provider.GetDataDescriptors().Where(x => x.Name.Equals("Tower")).Single();
       var towerProblemData = (RegressionProblemData)provider.LoadData(instance);
       towerProblemData.TargetVariableParameter.Value = towerProblemData.TargetVariableParameter.ValidValues
@@ -273 +272 @@
         towerProblemData.InputVariables.Single(x => x.Value == "towerResponse"), false);
       towerProblemData.TrainingPartition.Start = 0;
-      towerProblemData.TrainingPartition.End = 4000;
-      towerProblemData.TestPartition.Start = 4000;
+      towerProblemData.TrainingPartition.End = 3136;
+      towerProblemData.TestPartition.Start = 3136;
       towerProblemData.TestPartition.End = 4999;
       towerProblemData.Name = "Data imported from towerData.txt";
@@ -301 +300 @@
       symbRegProblem.BestKnownQuality.Value = 0.97;
       symbRegProblem.FitnessCalculationPartition.Start = 0;
-      symbRegProblem.FitnessCalculationPartition.End = 2800;
-      symbRegProblem.ValidationPartition.Start = 2800;
-      symbRegProblem.ValidationPartition.End = 4000;
+      symbRegProblem.FitnessCalculationPartition.End = 2300;
+      symbRegProblem.ValidationPartition.Start = 2300;
+      symbRegProblem.ValidationPartition.End = 3136;
       symbRegProblem.RelativeNumberOfEvaluatedSamples.Value = 1;
       symbRegProblem.MaximumSymbolicExpressionTreeLength.Value = 150;
@@ -346 +345 @@
       ga.SetSeedRandomly.Value = false;
       RunAlgorithm(ga);
-      Assert.AreEqual(0.13775264138895371, GetDoubleResult(ga, "BestQuality"), 1E-8);
-      Assert.AreEqual(14.232802217120254, GetDoubleResult(ga, "CurrentAverageQuality"), 1E-8);
-      Assert.AreEqual(104.24339008411457, GetDoubleResult(ga, "CurrentWorstQuality"), 1E-8);
+      Assert.AreEqual(0.14458636369766503, GetDoubleResult(ga, "BestQuality"), 1E-8);
+      Assert.AreEqual(2.5613992769560352, GetDoubleResult(ga, "CurrentAverageQuality"), 1E-8);
+      Assert.AreEqual(100.62175156249987, GetDoubleResult(ga, "CurrentWorstQuality"), 1E-8);
       Assert.AreEqual(100900, GetIntResult(ga, "EvaluatedSolutions"));
+      var bestTrainingSolution = (IClassificationSolution)ga.Results["Best training solution"].Value;
+      Assert.AreEqual(0.80625, bestTrainingSolution.TrainingAccuracy, 1E-8);
+      Assert.AreEqual(0.782608695652174, bestTrainingSolution.TestAccuracy, 1E-8);
     }
 
@@ -358 +360 @@
       symbClassProblem.Name = "Mammography Classification Problem";
       symbClassProblem.Description = "Mammography dataset imported from the UCI machine learning repository (http://archive.ics.uci.edu/ml/datasets/Mammographic+Mass)";
-      ClassificationRealWorldInstanceProvider provider = new ClassificationRealWorldInstanceProvider();
-      var instance = provider.GetDataDescriptors().Where(x => x.Name.Equals("Mammography")).Single();
+      UCIInstanceProvider provider = new UCIInstanceProvider();
+      var instance = provider.GetDataDescriptors().Where(x => x.Name.Equals("Mammography, M. Elter, 2007")).Single();
       var mammoData = (ClassificationProblemData)provider.LoadData(instance);
       mammoData.TargetVariableParameter.Value = mammoData.TargetVariableParameter.ValidValues
@@ -555 +557 @@
         UnidirectionalRingMigrator, BestSelector, WorstReplacer>(
         ga, 100, 1, 1000, 0.05, 5, 50, 0.25);
-
-      ga.Analyzer.Operators.SetItemCheckedState(ga.Analyzer.Operators
-        .OfType<TSPAlleleFrequencyAnalyzer>()
-        .Single(), false);
-      ga.Analyzer.Operators.SetItemCheckedState(ga.Analyzer.Operators
-        .OfType<TSPPopulationDiversityAnalyzer>()
-        .Single(), false);
       #endregion
       return ga;
@@ -836 +831 @@
       ts.TabuTenure.Value = 60;
 
-      ts.Analyzer.Operators.SetItemCheckedState(ts.Analyzer.Operators
-        .OfType<TSPAlleleFrequencyAnalyzer>()
-        .Single(), false);
-      ts.Analyzer.Operators.SetItemCheckedState(ts.Analyzer.Operators
-        .OfType<TSPPopulationDiversityAnalyzer>()
-        .Single(), false);
       #endregion
       ts.Engine = new ParallelEngine();
@@ -920 +909 @@
         .Single(), false);
       vns.ShakingOperator = shakingOperator;
-      vns.Analyzer.Operators.SetItemCheckedState(vns.Analyzer.Operators
-        .OfType<TSPAlleleFrequencyAnalyzer>()
-        .Single(), false);
-      vns.Analyzer.Operators.SetItemCheckedState(vns.Analyzer.Operators
-        .OfType<TSPPopulationDiversityAnalyzer>()
-        .Single(), false);
       #endregion
       vns.Engine = new ParallelEngine();
       return vns;
+    }
+    #endregion
+    #endregion
+
+
+    #region Gaussian Process Regression
+    [TestMethod]
+    public void CreateGaussianProcessRegressionSampleTest() {
+      var vns = CreateGaussianProcessRegressionSample();
+      XmlGenerator.Serialize(vns, "../../GaussianProcessRegression.hl");
+    }
+    [TestMethod]
+    public void RunGaussianProcessRegressionSample() {
+      var gpr = CreateGaussianProcessRegressionSample();
+      gpr.SetSeedRandomly = false;
+      gpr.Seed = 1618551877;
+      RunAlgorithm(gpr);
+      Assert.AreEqual(-940.48768748097029, GetDoubleResult(gpr, "NegativeLogLikelihood"));
+      Assert.AreEqual(0.99561947047986976, GetDoubleResult(gpr, "Training R²"));
+    }
+
+    private GaussianProcessRegression CreateGaussianProcessRegressionSample() {
+      var gpr = new GaussianProcessRegression();
+      var provider = new VariousInstanceProvider();
+      var instance = provider.GetDataDescriptors().Where(x => x.Name.Contains("Spatial co-evolution")).Single();
+      var regProblem = new RegressionProblem();
+      regProblem.Load(provider.LoadData(instance));
+      #region Algorithm Configuration
+      gpr.Name = "Gaussian Process Regression";
+      gpr.Description = "A Gaussian process regression algorithm applied to the spatial co-evolution benchmark problem.";
+      gpr.Problem = regProblem;
+
+      gpr.CovarianceFunction = new CovarianceSquaredExponentialIso();
+      gpr.MeanFunction = new MeanConst();
+      gpr.MinimizationIterations = 20;
+      gpr.Seed = 0;
+      gpr.SetSeedRandomly = true;
+      #endregion
+      gpr.Engine = new ParallelEngine();
+      return gpr;
+    }
+    #endregion
+
+    #region Scatter Search
+    #region VRP
+    [TestMethod]
+    public void CreateScatterSearchVRPSampleTest() {
+      var ss = CreateScatterSearchVRPSample();
+      XmlGenerator.Serialize(ss, "../../SS_VRP.hl");
+    }
+
+    [TestMethod]
+    public void RunScatterSearchVRPSampleTest() {
+      var ss = CreateScatterSearchVRPSample();
+      ss.SetSeedRandomly.Value = false;
+      RunAlgorithm(ss);
+      Assert.AreEqual(828.93686694283383, GetDoubleResult(ss, "BestQuality"));
+      Assert.AreEqual(868.63623986983077, GetDoubleResult(ss, "CurrentAverageQuality"));
+      Assert.AreEqual(1048.8333559209832, GetDoubleResult(ss, "CurrentWorstQuality"));
+      Assert.AreEqual(262622, GetIntResult(ss, "EvaluatedSolutions"));
+    }
+
+    private ScatterSearch CreateScatterSearchVRPSample() {
+      #region Problem Configuration
+      var provider = new SolomonInstanceProvider();
+      var instance = provider.GetDataDescriptors().Single(x => x.Name == "C101");
+      VehicleRoutingProblem vrpProblem = new VehicleRoutingProblem();
+      vrpProblem.Load(provider.LoadData(instance));
+      #endregion
+
+      #region Algorithm Configuration
+      ScatterSearch ss = new ScatterSearch();
+      ss.Engine = new SequentialEngine();
+      ss.Name = "Scatter Search - VRP";
+      ss.Description = "A scatter search algorithm which solves the \"C101\" vehicle routing problem (imported from Solomon)";
+      ss.Problem = vrpProblem;
+
+      var improver = ss.Problem.Operators.OfType<VRPIntraRouteImprovementOperator>().First();
+      improver.ImprovementAttemptsParameter.Value.Value = 15;
+      improver.SampleSizeParameter.Value.Value = 10;
+      ss.Improver = improver;
+
+      var pathRelinker = ss.Problem.Operators.OfType<VRPPathRelinker>().First();
+      pathRelinker.IterationsParameter.Value.Value = 25;
+      ss.PathRelinker = pathRelinker;
+
+      var similarityCalculator = ss.SimilarityCalculatorParameter.ValidValues.OfType<VRPSimilarityCalculator>().First();
+      ss.SimilarityCalculator = similarityCalculator;
+
+      ss.MaximumIterations.Value = 2;
+      ss.PopulationSize.Value = 20;
+      ss.ReferenceSetSize.Value = 10;
+      ss.Seed.Value = 0;
+      return ss;
+      #endregion
+    }
+    #endregion
+    #endregion
+
+    #region RAPGA
+    #region Scheduling
+    [TestMethod]
+    public void CreateRAPGASchedulingSampleTest() {
+      var ss = CreateRAPGASchedulingSample();
+      XmlGenerator.Serialize(ss, "../../RAPGA_JSSP.hl");
+    }
+
+    [TestMethod]
+    public void RunRAPGASchedulingSampleTest() {
+      var rapga = CreateRAPGASchedulingSample();
+      rapga.SetSeedRandomly.Value = false;
+      RunAlgorithm(rapga);
+      Assert.AreEqual(988.00, GetDoubleResult(rapga, "BestQuality"));
+      Assert.AreEqual(988.00, GetDoubleResult(rapga, "CurrentAverageQuality"));
+      Assert.AreEqual(988.00, GetDoubleResult(rapga, "CurrentWorstQuality"));
+      Assert.AreEqual(27100, GetIntResult(rapga, "EvaluatedSolutions"));
+    }
+
+    private RAPGA CreateRAPGASchedulingSample() {
+      #region Problem Configuration
+      JobShopSchedulingProblem problem = new JobShopSchedulingProblem();
+      #endregion
+
+      #region Algorithm Configuration
+      RAPGA rapga = new RAPGA();
+      rapga.Engine = new SequentialEngine();
+      rapga.Name = "RAPGA - Job Shop Scheduling";
+      rapga.Description = "A relevant alleles preserving genetic algorithm which solves a job shop scheduling problem";
+      rapga.Problem = problem;
+      rapga.Mutator = rapga.MutatorParameter.ValidValues.OfType<JSMSwapManipulator>().First();
+      rapga.Seed.Value = 0;
+      return rapga;
+      #endregion
     }
     #endregion

@@ -21 +21 @@
 protoc.exe
 _ReSharper.HeuristicLab 3.3 Tests
+Google.ProtocolBuffers-2.4.1.473.dll
 packages

@@ -4 +4 @@
 *.vs10x
 _ReSharper.HeuristicLab 3.3 Tests
+*.user
+*.suo