#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2013 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 HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Problems.Robocode {
  [StorableClass]
  [Item("Best Tank program Analyzer",
        "Analyzer that stores the best tank program.")]
  public class BestSolutionAnalyzer : SingleSuccessorOperator,
    ISymbolicExpressionTreeAnalyzer {
    #region parameter names
    private const string QualityParameterName = "Quality";
    private const string SymbolicExpressionTreeParameterName =
      "TankProgram";
    private const string MovesParameterName = "Moves";
    private const string ShotsParameterName = "Shots";
    private const string BestSolutionParameterName = "Best solution";
    private const string ResultsParameterName = "Results";
    private const string RobocodePathParamaterName = "Path";
    private const string CoevolutionParameterName = "Coevolution";
    #endregion


    #region parameters
    public IScopeTreeLookupParameter<DoubleValue> QualityParameter {
      get {
        return (IScopeTreeLookupParameter<DoubleValue>)
                  Parameters[QualityParameterName];
      }
    }
    public IScopeTreeLookupParameter<ISymbolicExpressionTree> SymbolicExpressionTreeParameter {
      get {
        return (IScopeTreeLookupParameter<ISymbolicExpressionTree>)
                  Parameters[SymbolicExpressionTreeParameterName];
      }
    }
    //public ILookupParameter<IntValue> MovesParameter
    //{
    //    get
    //    {
    //        return (ILookupParameter<IntValue>)
    //                  Parameters[MovesParameterName];
    //    }
    //}
    //public ILookupParameter<IntValue> ShotsParameter
    //{
    //    get
    //    {
    //        return (ILookupParameter<IntValue>)
    //                  Parameters[ShotsParameterName];
    //    }
    //}
    public ILookupParameter<Solution> BestSolutionParameter {
      get {
        return (ILookupParameter<Solution>)
                  Parameters[BestSolutionParameterName];
      }
    }
    public ILookupParameter<ResultCollection> ResultParameter {
      get {
        return (ILookupParameter<ResultCollection>)
                  Parameters[ResultsParameterName];
      }
    }
    public ILookupParameter<StringValue> RobocodePathParameter {
      get {
        return (ILookupParameter<StringValue>)
            Parameters[RobocodePathParamaterName];
      }
    }
    public ILookupParameter<BoolValue> CoevolutionParameter {
      get {
        return (ILookupParameter<BoolValue>)
            Parameters[CoevolutionParameterName];
      }
    }
    #endregion

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

    public BestSolutionAnalyzer() {
      Parameters.Add(
        new ScopeTreeLookupParameter<DoubleValue>(
          QualityParameterName,
          "The solution quality of the tank program."));
      Parameters.Add(
        new ScopeTreeLookupParameter<ISymbolicExpressionTree>(
          SymbolicExpressionTreeParameterName,
          "The tank program to evaluate represented " +
          "as symbolic expression tree."));
      Parameters.Add(
        new LookupParameter<Solution>(
          BestSolutionParameterName, "The best tank program."));
      //Parameters.Add(
      //  new LookupParameter<IntValue>(
      //    MovesParameterName, "The number of moves made."));
      //Parameters.Add(
      //  new LookupParameter<IntValue>(
      //    ShotsParameterName, "The shots made."));
      Parameters.Add(
        new LookupParameter<ResultCollection>(
          ResultsParameterName, "The result collection of the algorithm."));
      Parameters.Add(
        new LookupParameter<StringValue>(
          RobocodePathParamaterName,
          "Path of the Robocode installation."));
      Parameters.Add(
          new LookupParameter<BoolValue>(
              CoevolutionParameterName,
              "Use Coevolution"));
    }

    public override IOperation Apply() {
      // get an array of all trees
      // and an array of all qualities
      var trees = SymbolicExpressionTreeParameter.ActualValue;
      var qualities = QualityParameter.ActualValue;

      // find the tree with the best quality
      double maxQuality = double.NegativeInfinity;
      ISymbolicExpressionTree bestTree = null;
      for (int i = 0; i < qualities.Length; i++) {
        if (qualities[i].Value > maxQuality) {
          maxQuality = qualities[i].Value;
          bestTree = trees[i];
        }
      }

      var coevolution = CoevolutionParameter.ActualValue.Value;
      double actualQuality = 0;

      if (coevolution)
        actualQuality = Interpreter.EvaluateTankProgram(bestTree, null, RobocodePathParameter.ActualValue.Value);

      // create a solution instance
      //int shots = ShotsParameter.ActualValue.Value;
      //int moves = MovesParameter.ActualValue.Value;
      var bestSolution = new Solution(bestTree, RobocodePathParameter.ActualValue.Value);//, moves, shots);
      // store the new solution in the best solution parameter
      BestSolutionParameter.ActualValue = bestSolution;

      // also add the best solution as a result to the result collection
      // or alternatively update the existing result
      var resultCollection = ResultParameter.ActualValue;
      if (!resultCollection.ContainsKey(BestSolutionParameterName)) {
        resultCollection.Add(
          new Result(BestSolutionParameterName,
                     "The best tank program", bestSolution));
        //if(coevolution)
        //    resultCollection.Add(
        //        new Result("Actual Quality",
        //            "The actual quality of the best program", new DoubleValue(actualQuality)));
      } else {
        resultCollection[BestSolutionParameterName].Value = bestSolution;
      }

      if (coevolution) {
        if (!resultCollection.ContainsKey("Actual Quality")) {
          resultCollection.Add(
              new Result("Actual Quality",
                  "The actual quality of the best program", new DoubleValue(actualQuality)));
        } else {
          resultCollection["Actual Quality"].Value = new DoubleValue(actualQuality);
        }
      }

      // important return base.Apply() to make sure the 
      // next operator is queued for execution
      return base.Apply();
    }

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

    // override this property to indicate that this analyzer
    // should be enabled by default in the algorithm
    public bool EnabledByDefault {
      get { return true; }
    }
  }
}