#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.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 that records the best parameter configuration.
  /// </summary>
  [Item("PopulationAnalyzer", "An analyzer that records the best parameter configuration.")]
  [StorableClass]
  public sealed class PopulationAnalyzer : SingleSuccessorOperator, IAnalyzer {
    public bool EnabledByDefault {
      get { return true; }
    }

    public ScopeTreeLookupParameter<ParameterConfigurationTree> ParameterConfigurationParameter {
      get { return (ScopeTreeLookupParameter<ParameterConfigurationTree>)Parameters["ParameterConfigurationTree"]; }
    }
    public ValueLookupParameter<ResultCollection> ResultsParameter {
      get { return (ValueLookupParameter<ResultCollection>)Parameters["Results"]; }
    }
    public LookupParameter<RunCollection> PopulationParameter {
      get { return (LookupParameter<RunCollection>)Parameters["Population"]; }
    }
    public LookupParameter<BoolValue> MaximizationParameter {
      get { return (LookupParameter<BoolValue>)Parameters["Maximization"]; }
    }

    #region Constructors and Cloning
    public PopulationAnalyzer()
      : base() {
      Parameters.Add(new ScopeTreeLookupParameter<ParameterConfigurationTree>("ParameterConfigurationTree", ""));
      Parameters.Add(new ValueLookupParameter<ResultCollection>("Results", ""));
      Parameters.Add(new LookupParameter<RunCollection>("Population", ""));
      Parameters.Add(new LookupParameter<BoolValue>("Maximization", "Set to false if the problem should be minimized."));
    }

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

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

      int i = 0;
      RunCollection rc = new RunCollection();
      foreach (ParameterConfigurationTree pt in (maximization ? parameterTrees.OrderByDescending(x => x.Quality) : parameterTrees.OrderBy(x => x.Quality))) {
        rc.Add(pt.ToRun(string.Format("Individual {0} ({1})", i, pt.ParameterInfoString), true));
        i++;
      }
      if (PopulationParameter.ActualValue == null) {
        PopulationParameter.ActualValue = rc;
        results.Add(new Result("Population", rc));
      } else {
        PopulationParameter.ActualValue = rc;
        results["Population"].Value = rc;
      }

      return base.Apply();
    }
  }
}