Index: trunk/sources/HeuristicLab.Tests/HeuristicLab-3.3/Samples/GPTimeSeriesSampleTest.cs
===================================================================
--- trunk/sources/HeuristicLab.Tests/HeuristicLab-3.3/Samples/GPTimeSeriesSampleTest.cs	(revision 11091)
+++ trunk/sources/HeuristicLab.Tests/HeuristicLab-3.3/Samples/GPTimeSeriesSampleTest.cs	(revision 11091)
@@ -0,0 +1,93 @@
+﻿#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2014 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ *
+ * This file is part of HeuristicLab.
+ *
+ * HeuristicLab is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * HeuristicLab is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
+ */
+#endregion
+
+using System.IO;
+using HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm;
+using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
+using HeuristicLab.Persistence.Default.Xml;
+using HeuristicLab.Problems.DataAnalysis.Symbolic;
+using HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis;
+using HeuristicLab.Selection;
+using Microsoft.VisualStudio.TestTools.UnitTesting;
+
+namespace HeuristicLab.Tests {
+  [TestClass]
+  public class GPTimeSeriesSampleTest {
+    private const string samplesDirectory = SamplesUtils.Directory;
+    [ClassInitialize]
+    public static void MyClassInitialize(TestContext testContext) {
+      if (!Directory.Exists(samplesDirectory))
+        Directory.CreateDirectory(samplesDirectory);
+    }
+
+    [TestMethod]
+    [TestCategory("Samples.Create")]
+    [TestProperty("Time", "medium")]
+    public void CreateGpTimeSeriesSampleTest() {
+      var ga = CreateGpTimeSeriesSample();
+      var path = Path.Combine(samplesDirectory, "OSGP_TimeSeries.hl");
+      XmlGenerator.Serialize(ga, path);
+    }
+    [TestMethod]
+    [TestCategory("Samples.Execute")]
+    [TestProperty("Time", "long")]
+    public void RunGpTimeSeriesSampleTest() {
+      var osga = CreateGpTimeSeriesSample();
+      osga.SetSeedRandomly.Value = false;
+      SamplesUtils.RunAlgorithm(osga);
+
+      Assert.AreEqual(0.020952753415199643, SamplesUtils.GetDoubleResult(osga, "BestQuality"), 1E-8);
+      Assert.AreEqual(0.023220938866319357, SamplesUtils.GetDoubleResult(osga, "CurrentAverageQuality"), 1E-8);
+      Assert.AreEqual(0.023716788824595391, SamplesUtils.GetDoubleResult(osga, "CurrentWorstQuality"), 1E-8);
+      Assert.AreEqual(48200, SamplesUtils.GetIntResult(osga, "EvaluatedSolutions"));
+    }
+
+    public static OffspringSelectionGeneticAlgorithm CreateGpTimeSeriesSample() {
+      var problem = new SymbolicTimeSeriesPrognosisSingleObjectiveProblem();
+      problem.Name = "Symbolic time series prognosis problem (Mackey Glass t=17)";
+      problem.ProblemData.Name = "Mackey Glass t=17";
+      problem.MaximumSymbolicExpressionTreeLength.Value = 125;
+      problem.MaximumSymbolicExpressionTreeDepth.Value = 12;
+      problem.EvaluatorParameter.Value.HorizonParameter.Value.Value = 10;
+
+      foreach (var symbol in problem.SymbolicExpressionTreeGrammar.Symbols) {
+        if (symbol is Exponential || symbol is Logarithm) {
+          symbol.Enabled = false;
+        } else if (symbol is AutoregressiveTargetVariable) {
+          symbol.Enabled = true;
+          var autoRegressiveSymbol = symbol as AutoregressiveTargetVariable;
+          autoRegressiveSymbol.MinLag = -30;
+          autoRegressiveSymbol.MaxLag = -1;
+        }
+      }
+
+      var osga = new OffspringSelectionGeneticAlgorithm();
+      osga.Name = "Genetic Programming - Time Series Prediction (Mackey-Glass-17)";
+      osga.Description = "A genetic programming algorithm for creating a time-series model for the Mackey-Glass-17 time series.";
+      osga.Problem = problem;
+      SamplesUtils.ConfigureOsGeneticAlgorithmParameters<GenderSpecificSelector, SubtreeCrossover, MultiSymbolicExpressionTreeManipulator>
+        (osga, popSize: 100, elites: 1, maxGens: 25, mutationRate: 0.15);
+      osga.MaximumSelectionPressure.Value = 100;
+      return osga;
+
+    }
+  }
+}
