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

namespace HeuristicLab.Problems.MetaOptimization {
  /// <summary>
  /// An analyzer for the qualities of each defined problem.
  /// </summary>
  [Item("PMOProblemQualitiesAnalyzer", "An analyzer for the qualities of each defined problem.")]
  [StorableClass]
  public sealed class PMOProblemQualitiesAnalyzer : SingleSuccessorOperator, IAnalyzer {
    public bool EnabledByDefault {
      get { return true; }
    }

    public ScopeTreeLookupParameter<ParameterConfigurationTree> ParameterConfigurationParameter {
      get { return (ScopeTreeLookupParameter<ParameterConfigurationTree>)Parameters["ParameterConfigurationTree"]; }
    }
    public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
      get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
    }
    public ValueLookupParameter<ResultCollection> ResultsParameter {
      get { return (ValueLookupParameter<ResultCollection>)Parameters["Results"]; }
    }
    public LookupParameter<ConstrainedItemList<IProblem>> ProblemsParameter {
      get { return (LookupParameter<ConstrainedItemList<IProblem>>)Parameters[MetaOptimizationProblem.ProblemsParameterName]; }
    }
    public LookupParameter<BoolValue> MaximizationParameter {
      get { return (LookupParameter<BoolValue>)Parameters["Maximization"]; }
    }

    #region Constructors and Cloning
    public PMOProblemQualitiesAnalyzer()
      : base() {
      Parameters.Add(new ScopeTreeLookupParameter<ParameterConfigurationTree>("ParameterConfigurationTree", ""));
      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", ""));
      Parameters.Add(new ValueLookupParameter<ResultCollection>("Results", ""));
      Parameters.Add(new LookupParameter<ConstrainedItemList<IProblem>>(MetaOptimizationProblem.ProblemsParameterName));
      Parameters.Add(new LookupParameter<BoolValue>("Maximization", "Set to false if the problem should be minimized."));
    }

    [StorableConstructor]
    private PMOProblemQualitiesAnalyzer(bool deserializing) : base(deserializing) { }
    private PMOProblemQualitiesAnalyzer(PMOProblemQualitiesAnalyzer original, Cloner cloner) : base(original, cloner) { }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new PMOProblemQualitiesAnalyzer(this, cloner);
    }
    #endregion

    public override IOperation Apply() {
      ItemArray<DoubleValue> qualities = QualityParameter.ActualValue;
      ResultCollection results = ResultsParameter.ActualValue;
      ItemArray<ParameterConfigurationTree> parameterTrees = ParameterConfigurationParameter.ActualValue;
      bool maximization = MaximizationParameter.ActualValue.Value;

      int idxBest;
      int idxWorst;
      var sortedQualities = qualities.Select((x, index) => new { index, x.Value }).OrderBy(x => x.Value);
      if (maximization) {
        idxBest = sortedQualities.Last().index;
        idxWorst = sortedQualities.First().index;
      } else {
        idxBest = sortedQualities.First().index;
        idxWorst = sortedQualities.Last().index;
      }

      int problemCount = ProblemsParameter.ActualValue.Count;

      double[][] problemQualities = GetProblemQualities(parameterTrees, problemCount);

      for (int i = 0; i < problemCount; i++) {
        DataTable problemQualitiesDataTable;
        string resultKey = "Problem." + i;
        if (!results.ContainsKey(resultKey)) {
          problemQualitiesDataTable = new DataTable();
          problemQualitiesDataTable.Name = resultKey + " Qualities";
          results.Add(new Result(resultKey, problemQualitiesDataTable));
        } else {
          problemQualitiesDataTable = results[resultKey].Value as DataTable;
        }

        AddValue(problemQualitiesDataTable, parameterTrees[idxBest].AverageQualities[i], "BestQuality", "BestQuality");
        AddValue(problemQualitiesDataTable, problemQualities[i].Average(), "AverageQuality", "BestQuality");
        AddValue(problemQualitiesDataTable, parameterTrees[idxWorst].AverageQualities[i], "WorstQuality", "BestQuality");
      }

      return base.Apply();
    }

    private static double[][] GetProblemQualities(ItemArray<ParameterConfigurationTree> parameterTrees, int problemCount) {
      double[][] problemQualities = new double[problemCount][];
      for (int i = 0; i < problemCount; i++) {
        problemQualities[i] = new double[parameterTrees.Length];
        for (int j = 0; j < parameterTrees.Length; j++) {
          problemQualities[i][j] = parameterTrees[j].AverageQualities[i];
        }
      }
      return problemQualities;
    }

    private static void AddValue(DataTable table, double data, string name, string description) {
      DataRow row;
      table.Rows.TryGetValue(name, out row);
      if (row == null) {
        row = new DataRow(name, description);
        row.Values.Add(data);
        table.Rows.Add(row);
      } else {
        row.Values.Add(data);
      }
    }
  }
}