#region License Information /* HeuristicLab * Copyright (C) 2002-2013 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 . */ #endregion using System; using System.Collections.Generic; using System.Diagnostics; using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding; using HeuristicLab.Random; using Microsoft.VisualStudio.TestTools.UnitTesting; namespace HeuristicLab.Encodings.SymbolicExpressionTreeEncoding_34.Tests { [TestClass] public class SubtreeCrossoverTest { private const int POPULATION_SIZE = 1000; private TestContext testContextInstance; /// ///Gets or sets the test context which provides ///information about and functionality for the current test run. /// public TestContext TestContext { get { return testContextInstance; } set { testContextInstance = value; } } [TestMethod()] public void SubtreeCrossoverDistributionsTest() { int generations = 5; var trees = new List(); var grammar = Grammars.CreateArithmeticAndAdfGrammar(); var random = new MersenneTwister(31415); double msPerCrossoverEvent; for (int i = 0; i < POPULATION_SIZE; i++) { trees.Add(ProbabilisticTreeCreator.Create(random, grammar, 100, 10)); for (int j = random.Next(3); j < 3; j++) SubroutineCreater.CreateSubroutine(random, trees[i], 100, 10, 3, 3); } Stopwatch stopwatch = new Stopwatch(); stopwatch.Start(); for (int gCount = 0; gCount < generations; gCount++) { for (int i = 0; i < POPULATION_SIZE; i++) { var par0 = (ISymbolicExpressionTree)trees.SelectRandom(random).Clone(); var par1 = (ISymbolicExpressionTree)trees.SelectRandom(random).Clone(); SubtreeCrossover.Cross(random, par0, par1, 0.9, 100, 10); } } stopwatch.Stop(); foreach (var tree in trees) Util.IsValid(tree); msPerCrossoverEvent = stopwatch.ElapsedMilliseconds / (double)POPULATION_SIZE / (double)generations; Console.WriteLine("SubtreeCrossover: " + Environment.NewLine + msPerCrossoverEvent + " ms per crossover event (~" + Math.Round(1000.0 / (msPerCrossoverEvent)) + "crossovers / s)" + Environment.NewLine + Util.GetSizeDistributionString(trees, 105, 5) + Environment.NewLine + Util.GetFunctionDistributionString(trees) + Environment.NewLine + Util.GetNumberOfSubtreesDistributionString(trees) + Environment.NewLine + Util.GetTerminalDistributionString(trees) + Environment.NewLine ); //mkommend: commented due to performance issues on the builder //Assert.IsTrue(Math.Round(1000.0 / (msPerCrossoverEvent)) > 2000); // must achieve more than 2000 x-overs/s } } }