#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 System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Analysis {
  [Item("PopulationDiversityMDSAnalyzer", "Transforms the population similarity HeatMap into coordinates by making use of multidimensional scaling.")]
  [StorableClass]
  public class PopulationDiversityMDSAnalyzer : SingleSuccessorOperator, IAnalyzer {
    public ILookupParameter<ResultCollection> ResultsParameter {
      get { return (ILookupParameter<ResultCollection>)Parameters["Results"]; }
    }
    public ILookupParameter<ResultCollection> PopulationDiversityAnalyzerResultsParameter {
      get { return (ILookupParameter<ResultCollection>)Parameters["PopulationDiversityAnalyzer Results"]; }
    }
    public ILookupParameter<HeatMap> SolutionSimilaritiesParameter {
      get { return (ILookupParameter<HeatMap>)Parameters["Solution Similarities"]; }
    }
    /*public ILookupParameter<CoordinatesHistroy> CoordinatesHistoryParameter {
      get { return (ILookupParameter<CoordinatesHistroy>)Parameters["CoordinatesHistory"]; }
    }*/

    [StorableConstructor]
    protected PopulationDiversityMDSAnalyzer(bool deserializing) : base(deserializing) { }
    protected PopulationDiversityMDSAnalyzer(PopulationDiversityMDSAnalyzer original, Cloner cloner) : base(original, cloner) { }
    public PopulationDiversityMDSAnalyzer() {
      Parameters.Add(new LookupParameter<ResultCollection>("Results", "The results collection in which the population diversity analyzer injects its result collection."));
      Parameters.Add(new LookupParameter<ResultCollection>("PopulationDiversityAnalyzer Results", "The result collection in which the diversity analyzer injects its results."));
      Parameters.Add(new LookupParameter<HeatMap>("Solution Similarities", "The HeatMap that stores the solution similarities."));
      //Parameters.Add(new LookupParameter<CoordinatesHistroy>("CoordinatesHistory", "The history of the assigned coordinates."));
    }

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

    public override IOperation Apply() {
      ResultCollection results = ResultsParameter.ActualValue;
      ResultCollection popDivResults = (results[PopulationDiversityAnalyzerResultsParameter.ActualName] as IResult).Value as ResultCollection;
      if (popDivResults == null) throw new InvalidOperationException("Results collection of population diversity analyzer cannot be found.");
      HeatMap similarites = (popDivResults[SolutionSimilaritiesParameter.ActualName] as IResult).Value as HeatMap;
      if (similarites == null) throw new InvalidOperationException("HeatMap cannot be found in the results collection of the population diversity analyzer.");
      if (similarites.Rows != similarites.Columns) throw new InvalidOperationException("HeatMap is not a square matrix.");

      CoordinatesHistory history = null;
      if (popDivResults.ContainsKey("MDS"))
        history = popDivResults["MDS"].Value as CoordinatesHistory;
      else {
        history = new CoordinatesHistory();
        popDivResults.Add(new Result("MDS", history));
      }
      int dimension = similarites.Rows;
      DoubleMatrix distances = new DoubleMatrix(dimension, dimension);
      for (int i = 0; i < dimension; i++) {
        for (int j = 0; j < dimension; j++) {
          if (i == j) continue;
          distances[i, j] = 1.0 - similarites[i, j];
        }
      }
      double stress;
      DoubleMatrix coordinates = null;
      if (history.Count == 0) {
        coordinates = MultidimensionalScaling.MetricByDistance(distances, out stress);
      } else coordinates = MultidimensionalScaling.MetricByDistance(distances, out stress, history.Last().Clone() as DoubleMatrix);
      history.Add(coordinates);

      return base.Apply();
    }
  }
}