#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.Diagnostics; using System.Linq; using HeuristicLab.Analysis.AlgorithmBehavior.Analyzers; using MIConvexHull; using Microsoft.VisualStudio.TestTools.UnitTesting; namespace AlgorithmBehaviorUnitTests { [TestClass] public class LPConvexHullTest { [TestMethod] public void TestMethod1() { int nrOfSamples = 70; int sampleSize = 2; double[][] inputs = ConvexHullTest.CreateRandomData(nrOfSamples, sampleSize); Stopwatch watch = new Stopwatch(); watch.Start(); var result2 = LPHull.Calculate(inputs); watch.Stop(); Console.WriteLine("LPHull: " + watch.ElapsedMilliseconds); watch.Restart(); var result1 = ConvexHull.Create(inputs).Points.Select(x => x.Position).ToList(); watch.Stop(); Console.WriteLine("MIConvexHull: " + watch.ElapsedMilliseconds); int k = 0; foreach (var d in result1) { bool found = false; foreach (var e in result2) { int i = 0; for (i = 0; i < e.Count(); i++) { if (d[i] != e[i]) { break; } } if (i == e.Count()) { found = true; k++; break; } } Assert.IsTrue(found); } Console.WriteLine("Ratio: " + k + "/" + result1.Count); Assert.AreEqual(k, result1.Count); } [TestMethod] public void TestExt() { var inputs = CreateDataExtremePoint1().ToList(); double[] alpha = inputs.Last(); bool result = LPHull.EXT(inputs, alpha, inputs.Count() - 1); Assert.IsTrue(result); inputs = CreateDataExtremePoint2().ToList(); alpha = inputs.Last(); result = LPHull.EXT(inputs, alpha, inputs.Count() - 1); Assert.IsTrue(result); inputs = CreateDataNonExtremePoint1().ToList(); alpha = inputs.Last(); result = LPHull.EXT(inputs, alpha, inputs.Count() - 1); Assert.IsFalse(result); inputs = CreateDataOnHull().ToList(); alpha = inputs.Last(); result = LPHull.EXT(inputs, alpha, inputs.Count() - 1); Assert.IsFalse(result); } private double[][] CreateDataExtremePoint1() { double[][] result = new double[5][]; result[0] = new double[] { 0.1, 0.1 }; result[1] = new double[] { 1, 1 }; result[2] = new double[] { 1, 0 }; result[3] = new double[] { 0, 1 }; result[4] = new double[] { 2.0, 1.4 }; return result; } private double[][] CreateDataExtremePoint2() { double[][] result = new double[5][]; result[0] = new double[] { 0.1, 0.1 }; result[1] = new double[] { 1, 1 }; result[2] = new double[] { 1, 0 }; result[3] = new double[] { 0, 1 }; result[4] = new double[] { 1.0, 1.4 }; return result; } private double[][] CreateDataNonExtremePoint1() { double[][] result = new double[5][]; result[0] = new double[] { 0.1, 0.1 }; result[1] = new double[] { 1, 1 }; result[2] = new double[] { 1, 0 }; result[3] = new double[] { 0, 1 }; result[4] = new double[] { 0.8, 0.4 }; return result; } private double[][] CreateDataOnHull() { double[][] result = new double[5][]; result[0] = new double[] { 0.1, 0.1 }; result[1] = new double[] { 1, 1 }; result[2] = new double[] { 1, 0 }; result[3] = new double[] { 0, 1 }; result[4] = new double[] { 1.0, 0.5 }; return result; } } }