#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2010 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.Drawing;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Encodings.PermutationEncoding;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Analysis.FitnessLandscape {

  [Item("PermutationFitnessDistanceCorrelationAnalyzer", "An operator that analyzes the correlation between fitness and distance to the best know solution for permutation encoding")]
  [StorableClass]
  public class PermutationFitnessDistanceCorrelationAnalyzer : FitnessDistanceCorrelationAnalyzer, IPermutationOperator {

    #region Parameters
    public ScopeTreeLookupParameter<Permutation> PermutationParameter {
      get { return (ScopeTreeLookupParameter<Permutation>)Parameters["Permutation"]; }
    }
    public LookupParameter<Permutation> BestKnownSolution {
      get { return (LookupParameter<Permutation>)Parameters["BestKnownSolution"]; }
    }
    #endregion

    [StorableConstructor]
    protected PermutationFitnessDistanceCorrelationAnalyzer(bool deserializing) : base(deserializing) { }
    protected PermutationFitnessDistanceCorrelationAnalyzer(PermutationFitnessDistanceCorrelationAnalyzer original, Cloner cloner) : base(original, cloner) { }

    public PermutationFitnessDistanceCorrelationAnalyzer() {
      Parameters.Add(new ScopeTreeLookupParameter<Permutation>("Permutation", "The permutation encoded solution"));
      Parameters.Add(new LookupParameter<Permutation>("BestKnownSolution", "The best known solution"));
    }

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

    private static Point GetEdge(Permutation a, int index) {
      switch (a.PermutationType) {
        case PermutationTypes.RelativeDirected:
          return new Point(a[index], a[(index + 1) % a.Length]);
        case PermutationTypes.RelativeUndirected:
          return new Point(
            Math.Min(a[index], a[(index + 1) % a.Length]),
            Math.Max(a[index], a[(index + 1) % a.Length]));
        default:
          throw new ArgumentException("cannot derive edge from non-relative permutation type");
      }
    }

    public static double Distance(Permutation a, Permutation b) {
      if (a.PermutationType != b.PermutationType)
        throw new ArgumentException(
          "Cannot calculate distance between different permuatation types: " +
          a.PermutationType + " and " + b.PermutationType);
      if (a.PermutationType == PermutationTypes.Absolute) {
        int nEqual = 0;
        for (int i = 0; i < Math.Min(a.Length, b.Length); i++) {
          if (a[i] == b[i])
            nEqual++;
        }
        return Math.Max(a.Length, b.Length) - nEqual;
      } else {
        HashSet<Point> edges = new HashSet<Point>();
        for (int i = 0; i < a.Length; i++)
          edges.Add(GetEdge(a, i));
        int nCommonEdges = 0;
        for (int i = 0; i < b.Length; i++) {
          if (edges.Contains(GetEdge(b, i)))
            nCommonEdges++;
        }
        return Math.Max(a.Length, b.Length) - nCommonEdges;
      }
    }

    protected override IEnumerable<double> GetDistancesToBestKnownSolution() {
      if (PermutationParameter.ActualName == null)
        return new double[0];
      Permutation bestKnownValue = BestKnownSolution.ActualValue;
      if (bestKnownValue == null)
        return PermutationParameter.ActualValue.Select(v => 0d);
      return PermutationParameter.ActualValue.Select(v => Distance(v, bestKnownValue));
    }
  }
}