#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.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Encodings.ConditionActionEncoding;
using HeuristicLab.Encodings.VariableVector;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.PluginInfrastructure;
using HeuristicLab.Problems.ConditionActionClassification;
using HeuristicLab.Problems.DataAnalysis;

namespace HeuristicLab.Problems.VariableVectorClassification {
  [StorableClass]
  public class VariableVectorClassificationProblem : ConditionActionClassificationProblem<UniformRandomVariableVectorCreator,
                                                            VariableVectorActionComparer,
                                                            VariableVectorClassificationProblemData>, IVariableVectorClassificationProblem {
    public override string ChildName {
      get { return "VariableVector"; }
    }

    #region parameter properties
    private IFixedValueParameter<ItemSet<VariableVectorAction>> PossibleActionsConcreteClassParameter {
      get { return (IFixedValueParameter<ItemSet<VariableVectorAction>>)Parameters["PossibleActionsConcreteClass"]; }
    }
    public override IFixedValueParameter<VariableVectorActionComparer> ClassifierComparerParameter {
      get { return (IFixedValueParameter<VariableVectorActionComparer>)Parameters["ClassifierComparer"]; }
    }
    public IVariableVectorCoveringCreator VariableVectorCoveringCreator {
      get { return (IVariableVectorCoveringCreator)CoveringSolutionCreator; }
    }
    #endregion

    #region properties
    public new VariableVectorClassificationProblemData ProblemData {
      get { return ProblemDataParameter.Value; }
      protected set {
        ProblemDataParameter.Value = value;
        if (value != null) {
          SetProblemDataSettings();
        }
      }
    }

    public ItemSet<VariableVectorAction> PossibleActionsConcreteClass {
      get { return PossibleActionsConcreteClassParameter.Value; }
    }
    public IClassifierComparer ClassifierComparer {
      get { return ClassifierComparerParameter.Value; }
    }
    #endregion

    [StorableConstructor]
    protected VariableVectorClassificationProblem(bool deserializing) : base(deserializing) { }
    protected VariableVectorClassificationProblem(VariableVectorClassificationProblem original, Cloner cloner)
      : base(original, cloner) {
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new VariableVectorClassificationProblem(this, cloner);
    }

    public VariableVectorClassificationProblem() :
      this(new VariableVectorClassificationProblemData(new Dataset(ConditionActionClassificationProblemData.defaultVariableNames, ConditionActionClassificationProblemData.defaultData),
        ConditionActionClassificationProblemData.defaultVariableNames.Take(ConditionActionClassificationProblemData.defaultVariableNames.Length - 1), ConditionActionClassificationProblemData.defaultVariableNames.Last().ToEnumerable()),
        new XCSEvaluator(), new UniformRandomVariableVectorCreator(), new VariableVectorCoveringCreator()) {
    }

    public VariableVectorClassificationProblem(VariableVectorClassificationProblemData problemData, XCSEvaluator evaluator, UniformRandomVariableVectorCreator solutionCreator, IVariableVectorCoveringCreator coveringSolutionCreator)
      : base(problemData, evaluator, solutionCreator, coveringSolutionCreator) {
      Parameters.Add(new FixedValueParameter<VariableVectorActionComparer>("ClassifierComparer", problemData.ConcreteClassifierComparer));
      Parameters.Add(new FixedValueParameter<ItemSet<IAction>>("PossibleActions", new ItemSet<IAction>(ClassifierComparer)));
      Parameters.Add(new FixedValueParameter<ItemSet<VariableVectorAction>>("PossibleActionsConcreteClass", new ItemSet<VariableVectorAction>(ClassifierComparer)));

      SolutionCreator.VariableVectorParameter.ActualName = ChildName;
      SolutionCreator.ChangeSymbolProbabilityParameter.ActualName = ChangeSymbolProbabilityInCoveringParameter.Name;

      SetProblemDataSettings();

      InitializeOperators();
    }

    protected override void SetProblemDataSettings() {
      SolutionCreator.ProblemDataParameter.ActualName = ProblemDataParameter.Name;

      VariableVectorCoveringCreator.ProblemDataParameter.ActualName = ProblemDataParameter.Name;

      SetPossibleActions();
    }

    private void InitializeOperators() {
      Operators.AddRange(ApplicationManager.Manager.GetInstances<IVariableVectorCrossover>());
      Operators.AddRange(AddManipulators());

      ParameterizeOperators();
    }

    protected override void ParameterizeOperators() {
      base.ParameterizeOperators();
      foreach (IVariableVectorCrossover op in Operators.OfType<IVariableVectorCrossover>()) {
        op.ParentsParameter.ActualName = SolutionCreator.VariableVectorParameter.ActualName;
        op.ParentsParameter.Hidden = true;
        op.ChildParameter.ActualName = SolutionCreator.VariableVectorParameter.ActualName;
        op.ChildParameter.Hidden = true;
      }
    }

    private IEnumerable<IManipulator> AddManipulators() {
      var manipulator = new UniformSomePositionManipulator();
      manipulator.ChildParameter.ActualName = ChildName;
      manipulator.FetchedInputParameter.ActualName = ClassifierFetcher.CurrentInputToMatchParameter.ActualName;
      manipulator.PossibleActionsParameter.ActualName = PossibleActionsConcreteClassParameter.Name;
      manipulator.ProblemDataParameter.ActualName = ProblemDataParameter.Name;
      return new List<IManipulator>() { manipulator };
    }

    protected override void SetPossibleActions() {
      var sampleAction = ProblemData.SampleVariableVector.Action;
      var actionKeys = sampleAction.Order;
      var actionsEnumeratorList = sampleAction.VariableDictionary.ToDictionary(x => x.Key, y => y.Value.GetAllPossibleActions().ToList());
      int[] curPos = new int[actionsEnumeratorList.Count];
      //initialize curPos
      for (int i = 0; i < curPos.Length; i++) {
        curPos[i] = 0;
      }
      bool done = false;
      PossibleActions.Clear();
      PossibleActionsConcreteClass.Clear();
      VariableVectorAction curAction;
      int cur;
      while (!done) {
        curAction = sampleAction.GetEmptyCopy();
        cur = 0;
        foreach (var key in actionKeys) {
          curAction.VariableDictionary[key].SetTo(actionsEnumeratorList[key][curPos[cur]]);
          cur++;
        }
        PossibleActions.Add(curAction);
        PossibleActionsConcreteClass.Add(curAction);
        done = MoveNext(actionsEnumeratorList, curPos, actionKeys);
      }
      ThetaMinimalNumberOfActions.Value = PossibleActions.Count;
    }

    private bool MoveNext(Dictionary<string, List<string>> actionsEnumeratorList, int[] curPos, IEnumerable<string> order) {
      int cur = 0;
      bool done = true;
      foreach (var key in order) {
        if (curPos[cur] + 1 < actionsEnumeratorList[key].Count) {
          curPos[cur]++;
          done = false;
          break;
        } else {
          curPos[cur] = 0;
        }
        cur++;
      }
      return done;
    }
  }
}