source: branches/HeuristicLab.Analysis.AlgorithmBehavior/PerformanceTests/Program.cs @ 11512

#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.Collections.Generic;
using System.Diagnostics;
using System.Linq;
using HeuristicLab.Analysis.AlgorithmBehavior.Analyzers;
using MIConvexHull;

namespace PerformanceTests {
  class Program {

    static int nrOfPoints = 1000;
    static int dimension = 10;

    static void Main(string[] args) {
      //TestConvexHullPerformance();
      //TestVolumeCalculationPerformance();

      TestMDSPerformance();
    }

    public static void TestMDSPerformance() {
      double[][] orgPoints = new double[nrOfPoints][];
      double[][] orgDm = new double[nrOfPoints][];
      double[][] newPoints = null;
      Stopwatch watch = new Stopwatch();

      AllocArray(orgPoints, dimension);
      AllocArray(orgDm, nrOfPoints);
      SamplePoints(orgPoints);
      CalculateDistanceMatrix(orgDm, orgPoints);

      watch.Start();
      newPoints = DistanceMatrixToPoints.MetricMDS(orgDm, dimension);
      watch.Stop();
      Console.WriteLine("Runtime of MetricMDS (in sec): " + watch.Elapsed.TotalSeconds);

      Console.ReadLine();
    }

    public static void TestConvexHullPerformance() {
      List<double[]> result = null;
      Stopwatch watch = new Stopwatch();

      var data = CreateRandomData(nrOfPoints, dimension);
      var dataList = data.ToList();

      //calculate convex hull with LP
      watch.Start();
      result = LPHull.Calculate(data);
      watch.Stop();
      Console.WriteLine("Runtime of LPHull (in sec): " + watch.Elapsed.TotalSeconds);

      //calculate convex hull with SMO
      watch.Restart();
      result = HyperHull.Calculate(data);
      watch.Stop();
      Console.WriteLine("Runtime of HyperHull (in sec): " + watch.Elapsed.TotalSeconds);

      //calculate convex hull with MIConvexHull
      watch.Restart();
      result = ConvexHull.Create(data).Points.Select(x => x.Position).ToList();
      watch.Stop();
      Console.WriteLine("Runtime of MIConvexHull (in sec): " + watch.Elapsed.TotalSeconds);

      //calculate convex hull with QHull
      watch.Restart();
      result = QhullWrapper.Calculate(dataList);
      watch.Stop();
      Console.WriteLine("Runtime of QHull (in sec): " + watch.Elapsed.TotalSeconds);

      Console.ReadLine();
    }

    public static void TestVolumeCalculationPerformance() {
      var data = CreateRandomData(nrOfPoints, dimension);
      var dataList = data.ToList();
      List<double[]> convexHull = null;
      double volume = 0.0;
      Stopwatch watch = new Stopwatch();


      //calculate volume with LP and then use QHull
      watch.Start();
      convexHull = LPHull.Calculate(data);
      volume = QhullWrapper.CalculateVolume(convexHull);
      watch.Stop();
      Console.WriteLine(Environment.NewLine + "## Runtime of LPHull/QHull (sec): " + watch.Elapsed.TotalSeconds);
      //Console.WriteLine("Volume of convex hull is: " + volume);

      //calculate volume with QHull
      watch.Restart();
      volume = QhullWrapper.CalculateVolume(dataList);
      watch.Stop();
      Console.WriteLine(Environment.NewLine + "## Runtime of QHull (sec): " + watch.Elapsed.TotalSeconds);
      //Console.WriteLine("Volume of convex hull is: " + volume);

      //calculate volume of data with delauny triangulation
      watch.Restart();
      volume = ConvexHullMeasures.CalculateVolume(dataList);
      watch.Stop();
      Console.WriteLine(Environment.NewLine + "## Runtime using all data with delauny (sec): " + watch.Elapsed.TotalSeconds);
      //Console.WriteLine("Volume of convex hull is: " + volume);

      //calculate volume with convex hull (LPHull) and delauny triangulation
      watch.Restart();
      convexHull = LPHull.Calculate(data);
      volume = ConvexHullMeasures.CalculateVolume(convexHull);
      watch.Stop();
      Console.WriteLine(Environment.NewLine + "## Runtime using convex hull and delauny (sec): " + watch.Elapsed.TotalSeconds);
      //Console.WriteLine("Volume of convex hull is: " + volume);

      Console.ReadLine();
    }

    private 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;
    }

    private static void CalculateDistanceMatrix(double[][] dm, double[][] points) {
      for (int i = 0; i < points.Length; i++) {
        for (int j = 0; j < points.Length; j++) {
          dm[i][j] = points[i].EuclideanDistance(points[j]);
        }
      }
    }

    private static void AllocArray(double[][] arr, int size) {
      for (int i = 0; i < arr.Length; i++) {
        arr[i] = new double[size];
      }
    }

    private static void SamplePoints(double[][] points) {
      Random rand = new Random();

      for (int i = 0; i < points.Length; i++) {
        for (int j = 0; j < points[i].Length; j++) {
          points[i][j] = rand.NextDouble() * 100;
        }
      }
    }
  }
}