#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2016 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.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Optimization;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Problems.QuadraticAssignment;
using System;
using System.Collections.Generic;
using System.Linq;

namespace HeuristicLab.Analysis.FitnessLandscape {
  [Item("QAP Characteristic Calculator", "")]
  [StorableClass]
  public sealed class QAPCharacteristicCalculator : CharacteristicCalculator {

    [StorableConstructor]
    private QAPCharacteristicCalculator(bool deserializing) : base(deserializing) { }
    private QAPCharacteristicCalculator(QAPCharacteristicCalculator original, Cloner cloner) : base(original, cloner) { }
    public QAPCharacteristicCalculator() {
      characteristics.AddRange(new[] { "Dimension",
        "FlowDominance", "DistanceDominance",
        "FlowAsymmetry", "DistanceAsymmetry",
        "FlowSparsity", "DistanceSparsity",
        "FlowSkewness", "DistanceSkewness",
        "FlowDisparity", "DistanceDisparity" }.Select(x => new StringValue(x)).ToList());
    }

    public override IDeepCloneable Clone(Cloner cloner) {
      return new QAPCharacteristicCalculator(this, cloner);
    }

    public override bool CanCalculate() {
      return Problem is QuadraticAssignmentProblem;
    }

    public override IEnumerable<IResult> Calculate() {
      var qap = Problem as QuadraticAssignmentProblem;
      if (qap == null) throw new ArgumentException("Instance is not of type QuadraticAssignmentProblem");
      foreach (var chara in characteristics.CheckedItems.Select(x => x.Value.Value)) {
        if (chara == "Dimension")
          yield return new Result(chara, new IntValue(qap.Weights.Rows));
        if (chara == "FlowDominance")
          yield return new Result(chara, new DoubleValue(DoubleMatrixCharacteristicCalculator.CoeffVariation(qap.Weights)));
        if (chara == "DistanceDominance")
          yield return new Result(chara, new DoubleValue(DoubleMatrixCharacteristicCalculator.CoeffVariation(qap.Distances)));
        if (chara == "FlowAsymmetry")
          yield return new Result(chara, new DoubleValue(DoubleMatrixCharacteristicCalculator.Asymmetry(qap.Weights)));
        if (chara == "DistanceAsymmetry")
          yield return new Result(chara, new DoubleValue(DoubleMatrixCharacteristicCalculator.Asymmetry(qap.Distances)));
        if (chara == "FlowSparsity")
          yield return new Result(chara, new DoubleValue(DoubleMatrixCharacteristicCalculator.Sparsity(qap.Weights)));
        if (chara == "DistanceSparsity")
          yield return new Result(chara, new DoubleValue(DoubleMatrixCharacteristicCalculator.Sparsity(qap.Distances)));
        if (chara == "FlowSkewness")
          yield return new Result(chara, new DoubleValue(DoubleMatrixCharacteristicCalculator.Skewness(qap.Weights)));
        if (chara == "DistanceSkewness")
          yield return new Result(chara, new DoubleValue(DoubleMatrixCharacteristicCalculator.Skewness(qap.Distances)));
        if (chara == "FlowDisparity")
          yield return new Result(chara, new DoubleValue(DoubleMatrixCharacteristicCalculator.Disparity(qap.Weights)));
        if (chara == "DistanceDisparity")
          yield return new Result(chara, new DoubleValue(DoubleMatrixCharacteristicCalculator.Disparity(qap.Distances)));
      }
    }
  }
}