#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;
using Microsoft.VisualStudio.TestTools.UnitTesting;

namespace AlgorithmBehaviorUnitTests {
  [TestClass]
  public class LPConvexHullTest {
    [TestMethod]
    public void TestMethod1() {
      int nrOfSamples = 70;
      int sampleSize = 2;
      double[][] inputs = CreateRandomData(nrOfSamples, sampleSize);
      var convAlgData = ConvertPermutationToVertex(inputs);

      Stopwatch watch = new Stopwatch();
      watch.Start();
      var result2 = LPHull.Calculate(inputs);
      watch.Stop();
      Console.WriteLine("LPHull: " + watch.ElapsedMilliseconds);
      watch.Restart();
      var result1 = ConvexHull.Create(convAlgData).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;
    }

    private List<DefaultVertex> ConvertPermutationToVertex(double[][] data) {
      List<DefaultVertex> result = new List<DefaultVertex>();
      for (int i = 0; i < data.Count(); i++) {
        double[] d = data[i];
        for (int j = 0; j < d.Length; j++) {
          DefaultVertex vertex = new DefaultVertex();
          vertex.Position = d.Select(x => x).ToArray();
          result.Add(vertex);
        }
      }
      return result;
    }

    private 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;
    }
  }
}