#region License Information /* HeuristicLab * Copyright (C) 2002-2010 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.Data; using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding; using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.ArchitectureManipulators; using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Creators; using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Crossovers; using HeuristicLab.Random; using Microsoft.VisualStudio.TestTools.UnitTesting; namespace HeuristicLab.Encodings.SymbolicExpressionTreeEncoding_3._3.Tests { [TestClass] public class AllArchitectureAlteringOperatorsTest { private const int POPULATION_SIZE = 1000; private const int N_ITERATIONS = 20; private const int MAX_TREE_SIZE = 100; private const int MAX_TREE_HEIGHT = 10; 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 AllArchitectureAlteringOperatorsDistributionTest() { var trees = new List(); var newTrees = new List(); var grammar = Grammars.CreateArithmeticAndAdfGrammar(); var random = new MersenneTwister(31415); int failedEvents = 0; IntValue maxTreeSize = new IntValue(100); IntValue maxTreeHeigth = new IntValue(10); IntValue maxDefuns = new IntValue(3); IntValue maxArgs = new IntValue(3); for (int i = 0; i < POPULATION_SIZE; i++) { var tree = ProbabilisticTreeCreator.Create(random, grammar, MAX_TREE_SIZE, MAX_TREE_HEIGHT, 3, 3); Util.IsValid(tree); trees.Add(tree); } Stopwatch stopwatch = new Stopwatch(); stopwatch.Start(); var combinedAAOperator = new MultiSymbolicExpressionTreeArchitectureManipulator(); for (int g = 0; g < N_ITERATIONS; g++) { for (int i = 0; i < POPULATION_SIZE; i++) { if (random.NextDouble() < 0.5) { // manipulate var selectedTree = (SymbolicExpressionTree)trees.SelectRandom(random).Clone(); var op = combinedAAOperator.Operators.SelectRandom(random); bool success = false; op.ModifyArchitecture(random, selectedTree, grammar, maxTreeSize, maxTreeHeigth, maxDefuns, maxArgs, out success); if (!success) failedEvents++; Util.IsValid(selectedTree); newTrees.Add(selectedTree); } else { // crossover var par0 = (SymbolicExpressionTree)trees.SelectRandom(random).Clone(); var par1 = (SymbolicExpressionTree)trees.SelectRandom(random).Clone(); bool success; newTrees.Add(SubtreeCrossover.Cross(random, par0, par1, 0.9, 100, 10, out success)); if (!success) failedEvents++; } } trees = newTrees; } stopwatch.Stop(); var msPerOperation = stopwatch.ElapsedMilliseconds / (double)POPULATION_SIZE / (double)N_ITERATIONS; Assert.Inconclusive("AllArchitectureAlteringOperators: " + Environment.NewLine + "Failed events: " + failedEvents / (double)POPULATION_SIZE / N_ITERATIONS * 100 + " %" + Environment.NewLine + "Operations / s: ~" + Math.Round(1000.0 / (msPerOperation)) + "operations / s)" + Environment.NewLine + Util.GetSizeDistributionString(trees, 200, 5) + Environment.NewLine + Util.GetFunctionDistributionString(trees) + Environment.NewLine + Util.GetNumberOfSubTreesDistributionString(trees) + Environment.NewLine + Util.GetTerminalDistributionString(trees) + Environment.NewLine ); } } }