#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2012 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.Linq;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
using HeuristicLab.Random;
using Microsoft.VisualStudio.TestTools.UnitTesting;

namespace HeuristicLab.Encodings.SymbolicExpressionTreeEncoding_3._4.Tests {
  [TestClass]
  public class SubroutineDuplicaterTest {
    private const int POPULATION_SIZE = 1000;
    private const int MAX_TREE_LENGTH = 100;
    private const int MAX_TREE_DEPTH = 10;
    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;
      }
    }

    [TestMethod()]
    public void SubroutineDuplicaterDistributionsTest() {
      var trees = new List<ISymbolicExpressionTree>();
      var grammar = Grammars.CreateArithmeticAndAdfGrammar();
      var random = new MersenneTwister();
      for (int i = 0; i < POPULATION_SIZE; i++) {
        ISymbolicExpressionTree tree = null;
        do {
          tree = ProbabilisticTreeCreator.Create(random, grammar, MAX_TREE_LENGTH, MAX_TREE_DEPTH);
          for (int j = random.Next(3); j < 3; j++)
            SubroutineCreater.CreateSubroutine(random, tree, 100, 10, 3, 3);
        } while (!HasOneAdf(tree));
        var success = SubroutineDuplicater.DuplicateSubroutine(random, tree, 3, 3);
        Assert.IsTrue(success);
        Util.IsValid(tree);
        trees.Add(tree);
      }
      Console.WriteLine("SubroutineDuplicater: " + Environment.NewLine +
        Util.GetSizeDistributionString(trees, 105, 5) + Environment.NewLine +
        Util.GetFunctionDistributionString(trees) + Environment.NewLine +
        Util.GetNumberOfSubtreesDistributionString(trees) + Environment.NewLine +
        Util.GetTerminalDistributionString(trees) + Environment.NewLine
        );
    }

    private bool HasOneAdf(ISymbolicExpressionTree tree) {
      return tree.Root.Subtrees.Count() == 2;
    }
  }
}