#region License Information /* HeuristicLab * Copyright (C) 2002-2008 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 HeuristicLab.GP.StructureIdentification; using Microsoft.VisualStudio.TestTools.UnitTesting; using HeuristicLab.GP.Interfaces; using System.IO; using HeuristicLab.DataAnalysis; using System; using HeuristicLab.Random; using System.Collections.Generic; using HeuristicLab.GP.Operators; using System.Diagnostics; using HeuristicLab.Core; namespace HeuristicLab.GP.Test { [TestClass()] public class TournamentPruningTest { 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 TournamentPruningPruneTest() { IRandom random = new MersenneTwister(); Dataset ds = new Dataset(new double[,] { { 1.0, 1.0, 1.0 }, { 2.0, 2.0, 2.0 }, { 3.0, 1.0, 2.0 } }); ds.SetVariableName(0, "y"); ds.SetVariableName(1, "a"); ds.SetVariableName(2, "b"); var importer = new SymbolicExpressionImporter(); HL3TreeEvaluator evaluator = new HL3TreeEvaluator(); IFunctionTree prunedTree = null; prunedTree = TournamentPruning.Prune(random, importer.Import("(+ 1.5 3.5)"), 3, ds, "y", 0, 2, evaluator, 1.0, 1.0); prunedTree = TournamentPruning.Prune(random, importer.Import("(+ (variable 2.0 a 0) (+ 1.5 3.5))"), 3, ds, "y", 0, 2, evaluator, 1.0, 1.0); prunedTree = TournamentPruning.Prune(random, importer.Import("(+ (variable 2.0 a 0) (variable 0.00001 a 0))"), 3, ds, "y", 0, 2, evaluator, 1.0, 1.0); prunedTree = TournamentPruning.Prune(random, importer.Import("(+ (variable 1.0 a 0) (variable 1.0 b 0))"), 3, ds, "y", 0, 2, evaluator, 1.0, 1.0); } } }