#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 HeuristicLab.Random;
using HeuristicLab.Tests;
using Microsoft.VisualStudio.TestTools.UnitTesting;

namespace HeuristicLab.Encodings.LinearLinkageEncoding.Tests {
  [TestClass()]
  public class GroupCrossoverTest {
    [TestMethod()]
    [TestCategory("Encodings.LinearLinkage")]
    [TestProperty("Time", "short")]
    public void EqualParentsTest() {
      var random = new FastRandom(0);
      var parent = LinearLinkage.SingleElementGroups(10);
      var child = GroupCrossover.Apply(random, parent, parent);
      Assert.IsTrue(Auxiliary.LinearLinkageIsEqualByPosition(parent, child));

      parent = RandomLinearLinkageCreator.Apply(random, 10);
      child = GroupCrossover.Apply(random, parent, parent);
      Assert.IsTrue(Auxiliary.LinearLinkageIsEqualByPosition(parent, child));
    }

    // Example from paper:
    // Multi-objective Genetic Algorithms for grouping problems. Korkmaz, E.E. Applied Intelligence (2010) 33: 179. 
    [TestMethod()]
    [TestCategory("Encodings.LinearLinkage")]
    [TestProperty("Time", "short")]
    public void ExampleFromPaperTest() {
      var parent1 = LinearLinkage.FromEndLinks(new[] { 3, 4, 3, 3, 4 });

      var parent2 = LinearLinkage.FromEndLinks(new[] { 2, 2, 2, 4, 4 });

      CheckGroupCrossover(parent1, parent2, new[] { 3, 4, 2, 3, 4 }, new[] { 0.0, 0.0, 0.0, 0.0 }); // (i)
      CheckGroupCrossover(parent1, parent2, new[] { 2, 4, 2, 3, 4 }, new[] { 0.0, 0.0, 0.0, 0.9 }); // (iv)
      CheckGroupCrossover(parent1, parent2, new[] { 3, 2, 2, 3, 4 }, new[] { 0.0, 0.0, 0.9, 0.0 }); // (iii)
      CheckGroupCrossover(parent1, parent2, new[] { 2, 2, 2, 3, 4 }, new[] { 0.0, 0.0, 0.9, 0.9 }); // (ii)
      CheckGroupCrossover(parent1, parent2, new[] { 3, 4, 3, 3, 4 }, new[] { 0.0, 0.9 });
      CheckGroupCrossover(parent1, parent2, new[] { 2, 4, 2, 4, 4 }, new[] { 0.9, 0.0, 0.0 });
      CheckGroupCrossover(parent1, parent2, new[] { 2, 2, 2, 4, 4 }, new[] { 0.9, 0.0, 0.9 });
      CheckGroupCrossover(parent1, parent2, new[] { 4, 4, 4, 4, 4 }, new[] { 0.9, 0.9, 0.0, 0.0 });
      CheckGroupCrossover(parent1, parent2, new[] { 4, 4, 4, 4, 4 }, new[] { 0.9, 0.9, 0.0, 0.9 });
      CheckGroupCrossover(parent1, parent2, new[] { 2, 4, 2, 4, 4 }, new[] { 0.9, 0.9, 0.9, 0.0 });
      CheckGroupCrossover(parent1, parent2, new[] { 4, 4, 2, 4, 4 }, new[] { 0.9, 0.9, 0.9, 0.9 });
    }

    private void CheckGroupCrossover(LinearLinkage parent1, LinearLinkage parent2, int[] expectedllee, double[] randomNumbers) {
      var expected = LinearLinkage.FromEndLinks(expectedllee);
      var random = new TestRandom() { DoubleNumbers = randomNumbers };
      var child = GroupCrossover.Apply(random, parent1, parent2);
      Assert.IsTrue(Auxiliary.LinearLinkageIsEqualByPosition(expected, child), "Expected [{0}] but was [{1}]!", string.Join(", ", expected), string.Join(", ", child));
    }
  }
}