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

namespace HeuristicLab.Analysis.FitnessLandscape {

  [StorableClass]
  public abstract class FitnessDistanceCorrelationAnalyzer : AlgorithmOperator, IAnalyzer {
    public bool EnabledByDefault {
      get { return false; }
    }

    #region Parameters
    public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
      get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
    }
    public ValueLookupParameter<ScatterPlot> FDCParameter {
      get { return (ValueLookupParameter<ScatterPlot>)Parameters["FDC"]; }
    }
    public ValueLookupParameter<VariableCollection> ResultsParameter {
      get { return (ValueLookupParameter<VariableCollection>)Parameters["Results"]; }
    }
    #endregion

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

    public FitnessDistanceCorrelationAnalyzer() {
      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The quality of the solution"));
      Parameters.Add(new ValueLookupParameter<ScatterPlot>("FDC", "The data table the stores all observed fitness/distance values"));
      Parameters.Add(new ValueLookupParameter<VariableCollection>("Results", "The collection of all results of this algorithm"));

      var resultsCollector = new ResultsCollector();
      resultsCollector.CollectedValues.Add(new LookupParameter<ScatterPlot>(FDCParameter.Name));

      OperatorGraph.InitialOperator = resultsCollector;
      resultsCollector.Successor = null;
    }

    protected abstract IEnumerable<double> GetDistancesToBestKnownSolution();

    public override IOperation Apply() {
      ScatterPlot plot = FDCParameter.ActualValue;
      if (plot == null) {
        plot = new ScatterPlot();
        plot.Name = "Fitness Distance Correlation";
        plot.XAxisName = "Quality";
        plot.YAxisName = "Distance";
        FDCParameter.ActualValue = plot;
      }
      plot.Add(EnumerateFDC().ToList());
      return base.Apply();
    }

    private IEnumerable<PointF> EnumerateFDC() {
      var qualities = QualityParameter.ActualValue.Select(d => d.Value).ToList();
      var distances = GetDistancesToBestKnownSolution().ToList();
      if (qualities.Count == distances.Count) {
        var qIt = qualities.GetEnumerator();
        var dIt = distances.GetEnumerator();
        while (qIt.MoveNext() && dIt.MoveNext()) {
          yield return new PointF((float)qIt.Current, (float)dIt.Current);
        }
      }
    }
  }
}