[8753] | 1 | using System;
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| 2 | using System.Linq;
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| 3 | using System.Threading;
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| 4 | using HeuristicLab.Algorithms.GeneticAlgorithm;
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| 5 | using HeuristicLab.Problems.DataAnalysis;
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| 6 | using HeuristicLab.Random;
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| 7 | using Microsoft.VisualStudio.TestTools.UnitTesting;
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| 8 |
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| 9 | namespace HeuristicLab.Problems.GaussianProcessTuning.Tests {
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| 10 | [TestClass]
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| 11 | public class UnitTest {
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| 12 | [TestMethod]
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| 13 | public void TestGrammar() {
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| 14 | var g = new Grammar();
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| 15 | var r = new MersenneTwister();
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| 16 | var trees = (from i in Enumerable.Range(0, 1000)
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| 17 | select
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| 18 | HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.ProbabilisticTreeCreator.Create(r, g, 100, 10))
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| 19 | .ToArray();
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| 20 | }
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| 21 |
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| 22 | [TestMethod]
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| 23 | public void TestInterpreter() {
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| 24 | var interpreter = new Interpreter();
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| 25 | var g = new Grammar();
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| 26 | g.Symbols.Single(s => s is MeanMask).Enabled = true;
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| 27 | g.Dimension = 1;
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| 28 | var r = new MersenneTwister(31415);
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| 29 | var problemData = new RegressionProblemData();
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| 30 |
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| 31 | for (int i = 0; i < 1000; i++) {
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| 32 | var t = HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.ProbabilisticTreeCreator.Create(r, g, 50, 7);
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| 33 | Console.WriteLine(interpreter.EvaluateGaussianProcessConfiguration(t, problemData));
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| 34 | }
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| 35 | }
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| 36 |
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| 37 | [TestMethod]
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| 38 | public void TestGeneticAlgorithm() {
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| 39 | var prob = new Problem();
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| 40 | prob.DimensionParameter.Value.Value = 1;
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| 41 | var ga = new GeneticAlgorithm();
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| 42 | ga.Engine = new SequentialEngine.SequentialEngine();
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| 43 | ga.PopulationSize.Value = 100;
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| 44 | ga.MaximumGenerations.Value = 10;
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| 45 | ga.Problem = prob;
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| 46 |
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| 47 | var signal = new AutoResetEvent(false);
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| 48 | Exception ex = null;
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| 49 |
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| 50 | ga.ExceptionOccurred += (sender, args) => {
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| 51 | ex = args.Value;
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| 52 | signal.Set();
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| 53 | };
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| 54 | ga.Stopped += (sender, args) => {
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| 55 | signal.Set();
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| 56 | };
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| 57 |
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| 58 | ga.Prepare();
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| 59 | ga.Start();
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| 60 |
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| 61 | signal.WaitOne();
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| 62 | if (ex != null) throw ex;
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| 63 |
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| 64 | }
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| 65 |
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| 66 | /*
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| 67 | [TestMethod]
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| 68 | public void TestInterpreterPrediction() {
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| 69 | var interpreter = new Interpreter();
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| 70 | var g = new Grammar();
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| 71 | g.Symbols.Single(s => s is MeanMask).Enabled = true;
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| 72 | g.Dimension = 1;
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| 73 | var r = new MersenneTwister(31415);
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| 74 | var problemData = new RegressionProblemData();
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| 75 |
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| 76 | double[] means;
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| 77 | double[] stdDev;
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| 78 | for (int i = 0; i < 10; i++) {
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| 79 | var t = HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.ProbabilisticTreeCreator.Create(r, g, 50, 7);
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| 80 | interpreter.EvaluateGaussianProcessConfiguration(t, problemData, problemData.Dataset, problemData.TestIndices, out means, out stdDev);
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| 81 | }
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| 82 | }
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| 83 | */
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| 84 | }
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| 85 | }
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