//#region License Information
///* HeuristicLab
// * Copyright (C) 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 HeuristicLab.Common;
//using HeuristicLab.Core;
//using HeuristicLab.Data;
//using HeuristicLab.Encodings.PermutationEncoding;
//using HeuristicLab.Random;
//using Microsoft.VisualStudio.TestTools.UnitTesting;

//namespace HeuristicLab.Problems.PTSP.Tests {
//  /// <summary>
//  ///This is a test class for PTSP move evaluators
//  ///</summary>
//  [TestClass()]
//  public class PTSPMoveEvaluatorTest {
//    private const int ProblemSize = 10;
//    private const int RealizationsSize = 100;
//    private static DoubleMatrix coordinates;
//    private static DistanceMatrix distances;
//    private static Permutation tour;
//    private static MersenneTwister random;
//    private static ItemList<BoolArray> realizations;
//    private static DoubleArray probabilities;

//    [ClassInitialize]
//    public static void MyClassInitialize(TestContext testContext) {
//      random = new MersenneTwister();
//      coordinates = new DoubleMatrix(ProblemSize, 2);
//      distances = new DistanceMatrix(ProblemSize, ProblemSize);
//      for (var i = 0; i < ProblemSize; i++) {
//        coordinates[i, 0] = random.Next(ProblemSize * 10);
//        coordinates[i, 1] = random.Next(ProblemSize * 10);
//      }
//      for (var i = 0; i < ProblemSize - 1; i++) {
//        for (var j = i + 1; j < ProblemSize; j++) {
//          distances[i, j] = Math.Round(Math.Sqrt(Math.Pow(coordinates[i, 0] - coordinates[j, 0], 2) + Math.Pow(coordinates[i, 1] - coordinates[j, 1], 2)));
//          distances[j, i] = distances[i, j];
//        }
//      }

//      probabilities = new DoubleArray(ProblemSize);
//      for (var i = 0; i < ProblemSize; i++) {
//        probabilities[i] = random.NextDouble();
//      }

//      realizations = new ItemList<BoolArray>(RealizationsSize);
//      for (var i = 0; i < RealizationsSize; i++) {
//        var countOnes = 0;
//        var newRealization = new BoolArray(ProblemSize);
//        while (countOnes < 4) { //only generate realizations with at least 4 cities visited
//          countOnes = 0;
//          for (var j = 0; j < ProblemSize; j++) {
//            newRealization[j] = random.NextDouble() < probabilities[j];
//            if (newRealization[j]) countOnes++;
//          }
//        }
//        realizations.Add(newRealization);
//      }

//      tour = new Permutation(PermutationTypes.RelativeUndirected, ProblemSize, random);
//    }

//    [TestMethod]
//    [TestCategory("Problems.ProbabilisticTravelingSalesman")]
//    [TestProperty("Time", "short")]
//    public void InversionMoveEvaluatorTest() {
//      Func<int, int, double> distance = (a, b) => distances[a, b];
//      double variance;
//      var beforeMatrix = EstimatedProbabilisticTravelingSalesmanProblem.Evaluate(tour, distance, realizations, out variance);

//      for (var i = 0; i < 500; i++) {
//        var move = StochasticInversionSingleMoveGenerator.Apply(tour, random);
//        var moveMatrix = PTSPEstimatedInversionMoveEvaluator.EvaluateMove(tour, move, distance, realizations);
//        InversionManipulator.Apply(tour, move.Index1, move.Index2);
//        var afterMatrix = EstimatedProbabilisticTravelingSalesmanProblem.Evaluate(tour, distance, realizations, out variance);

//        Assert.IsTrue(Math.Abs(moveMatrix).IsAlmost(Math.Abs(afterMatrix - beforeMatrix)),
//          string.Format(@"Inversion move is calculated with quality {0}, but actual difference is {4}.
//The move would invert the tour {1} between values {2} and {3}.",
//          moveMatrix, tour, tour[move.Index1], tour[move.Index2], Math.Abs(afterMatrix - beforeMatrix)));

//        beforeMatrix = afterMatrix;
//      }
//    }

//    [TestMethod]
//    [TestCategory("Problems.ProbabilisticTravelingSalesman")]
//    [TestProperty("Time", "short")]
//    public void InsertionMoveEvaluatorTest() {
//      Func<int, int, double> distance = (a, b) => distances[a, b];
//      double variance;
//      var beforeMatrix = EstimatedProbabilisticTravelingSalesmanProblem.Evaluate(tour, distance, realizations, out variance);
//      for (var i = 0; i < 500; i++) {
//        var move = StochasticTranslocationSingleMoveGenerator.Apply(tour, random);
//        var moveMatrix = PTSPEstimatedInsertionMoveEvaluator.EvaluateMove(tour, move, distance, realizations);
//        TranslocationManipulator.Apply(tour, move.Index1, move.Index1, move.Index3);
//        var afterMatrix = EstimatedProbabilisticTravelingSalesmanProblem.Evaluate(tour, distance, realizations, out variance);

//        Assert.IsTrue(Math.Abs(moveMatrix).IsAlmost(Math.Abs(afterMatrix - beforeMatrix)),
//          string.Format(@"Insertion move is calculated with quality {0}, but actual difference is {4}.
//The move would invert the tour {1} between values {2} and {3}.",
//          moveMatrix, tour, tour[move.Index1], tour[move.Index2], Math.Abs(afterMatrix - beforeMatrix)));

//        beforeMatrix = afterMatrix;
//      }
//    }
//  }
//}