#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2011 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.Data;
using HeuristicLab.Encodings.PermutationEncoding;
using HeuristicLab.Random;
using Microsoft.VisualStudio.TestTools.UnitTesting;

namespace HeuristicLab.Problems.QuadraticAssignment.Tests_33 {

  /// <summary>
  ///This is a test class for the QAP move evaluators
  ///</summary>
  [TestClass()]
  public class QAPSwapMoveEvaluatorTest {

    private TestContext testContextInstance;
    /// <summary>
    ///Gets or sets the test context which provides
    ///information about and functionality for the current test run.
    ///</summary>
    public TestContext TestContext {
      get { return testContextInstance; }
      set { testContextInstance = value; }
    }

    #region Additional test attributes
    // 
    //You can use the following additional attributes as you write your tests:
    //
    //Use ClassInitialize to run code before running the first test in the class
    //[ClassInitialize()]
    //public static void MyClassInitialize(TestContext testContext)
    //{
    //}
    //
    //Use ClassCleanup to run code after all tests in a class have run
    //[ClassCleanup()]
    //public static void MyClassCleanup()
    //{
    //}
    //
    //Use TestInitialize to run code before running each test
    //[TestInitialize()]
    //public void MyTestInitialize()
    //{
    //}
    //
    //Use TestCleanup to run code after each test has run
    //[TestCleanup()]
    //public void MyTestCleanup()
    //{
    //}
    //
    #endregion

    [TestMethod]
    public void SwapMoveEvaluatorTest() {
      DoubleMatrix distances = new DoubleMatrix(
        new double[,] { { 0, 1, 2, 3 },
                        { 1, 0, 3, 4 },
                        { 2, 3, 0, 5 },
                        { 3, 4, 5, 0 } });
      DoubleMatrix weights = new DoubleMatrix(
        new double[,] { { 0, 1, 0, 0 },
                        { 1, 0, 2, 0 },
                        { 0, 2, 0, 1 },
                        { 0, 0, 1, 0 } });
      Permutation assignment = new Permutation(PermutationTypes.Absolute,
        new int[] { 0, 1, 2, 3 });
      MersenneTwister random = new MersenneTwister();
      for (int i = 0; i < 500; i++) {
        int index1 = random.Next(4);
        int index2 = random.Next(4);
        double before = QAPEvaluator.Apply(assignment, weights, distances);
        Swap2Manipulator.Apply(assignment, index1, index2);
        double after = QAPEvaluator.Apply(assignment, weights, distances);
        // evaluate swap back
        double move = QAPSwapMoveEvaluator.Apply(assignment, new SwapMove(index1, index2, assignment), weights, distances);
        Assert.IsTrue(move.IsAlmost(before - after));
      }
    }

    [TestMethod]
    public void InversionMoveEvaluatorTest() {
      DoubleMatrix distances = new DoubleMatrix(
        new double[,] { { 0, 1, 2, 3 },
                        { 1, 0, 3, 4 },
                        { 2, 3, 0, 5 },
                        { 3, 4, 5, 0 } });
      DoubleMatrix weights = new DoubleMatrix(
        new double[,] { { 0, 1, 0, 0 },
                        { 1, 0, 2, 0 },
                        { 0, 2, 0, 1 },
                        { 0, 0, 1, 0 } });
      Permutation assignment = new Permutation(PermutationTypes.Absolute,
        new int[] { 0, 1, 2, 3 });
      MersenneTwister random = new MersenneTwister();
      for (int i = 0; i < 500; i++) {
        int index1 = random.Next(4);
        int index2 = random.Next(4);
        double before = QAPEvaluator.Apply(assignment, weights, distances);
        // invert
        InversionManipulator.Apply(assignment, Math.Min(index1, index2), Math.Max(index1, index2));
        double after = QAPEvaluator.Apply(assignment, weights, distances);
        // evaluate invert back
        double move = QAPInversionMoveEvaluator.Apply(assignment, new InversionMove(index1, index2, assignment), weights, distances);
        Assert.IsTrue(move.IsAlmost(before - after));
      }
    }

    [TestMethod]
    public void TranslocationMoveEvaluatorTest() {
      DoubleMatrix distances = new DoubleMatrix(
        new double[,] { { 0, 1, 2, 3 },
                        { 1, 0, 3, 4 },
                        { 2, 3, 0, 5 },
                        { 3, 4, 5, 0 } });
      DoubleMatrix weights = new DoubleMatrix(
        new double[,] { { 0, 1, 0, 0 },
                        { 1, 0, 2, 0 },
                        { 0, 2, 0, 1 },
                        { 0, 0, 1, 0 } });
      Permutation assignment = new Permutation(PermutationTypes.Absolute,
        new int[] { 0, 1, 2, 3 });
      MersenneTwister random = new MersenneTwister();
      for (int i = 0; i < 500; i++) {
        int index1 = random.Next(assignment.Length - 1);
        int index2 = random.Next(index1 + 1, assignment.Length);
        int insertPointLimit = assignment.Length - index2 + index1 - 1;  // get insertion point in remaining part
        int insertPoint;
        if (insertPointLimit > 0)
          insertPoint = random.Next(insertPointLimit);
        else
          insertPoint = 0;
        double before = QAPEvaluator.Apply(assignment, weights, distances);
        // translocate
        Permutation clone = new Cloner().Clone(assignment);
        TranslocationManipulator.Apply(assignment, index1, index2, insertPoint);
        double after = QAPEvaluator.Apply(assignment, weights, distances);
        // evaluate translocate move
        double move = QAPTranslocationMoveEvaluator.Apply(clone, new TranslocationMove(index1, index2, insertPoint, assignment), weights, distances);
        Assert.IsTrue(move.IsAlmost(after - before));
      }
    }

  }
}