source: branches/HeuristicLab.Analysis.AlgorithmBehavior/AlgorithmBehaviorUnitTests/ConvexHullTest.cs @ 11166

#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 <http://www.gnu.org/licenses/>.
 */
#endregion

using System;
using System.Linq;
using HeuristicLab.Analysis.AlgorithmBehavior.Analyzers;
using HeuristicLab.Common;
using Microsoft.VisualStudio.TestTools.UnitTesting;

namespace AlgorithmBehaviorUnitTests {
  [TestClass]
  public class ConvexHullTest {
    [TestMethod]
    public void TestConvexHullAlgorithms() {
      int nrOfSamples = 50;
      int dimension = 4;
      double[][] inputs = CreateRandomData(nrOfSamples, dimension);

      var lpResult = LPHull.Calculate(inputs);
      var qhResult = QhullWrapper.Calculate(inputs.ToList());

      foreach (var qhr in qhResult) {
        bool found = false;
        foreach (var lpr in lpResult) {
          int i = 0;
          for (i = 0; i < lpr.Count(); i++) {
            if (!qhr[i].IsAlmost(lpr[i])) {
              break;
            }
          }
          if (i == lpr.Count()) {
            found = true;
            break;
          }
        }
        Assert.IsTrue(found);
      }
    }

    public static double[][] CreateRandomData(int n, int m) {
      double[][] result = new double[n][];
      Random rand = new Random();

      for (int i = 0; i < n; i++) {
        result[i] = new double[m];
        for (int j = 0; j < m; j++) {
          result[i][j] = (double)rand.Next(1, 60);
        }
      }
      return result;
    }
  }
}