#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2008 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;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using HeuristicLab.Core;
using System.Xml;
using System.Diagnostics;
using HeuristicLab.DataAnalysis;
using HeuristicLab.Operators;
using HeuristicLab.Random;
using HeuristicLab.Selection;
using HeuristicLab.Logging;
using HeuristicLab.Data;
using HeuristicLab.Operators.Programmable;

namespace HeuristicLab.GP.StructureIdentification {
  public class StandardGP : ItemBase, IEditable {
    private IntData maxGenerations = new IntData();
    public int MaxGenerations {
      get { return maxGenerations.Data; }
      set { maxGenerations.Data = value; }
    }

    private IntData tournamentSize = new IntData();
    public int TournamentSize {
      get { return tournamentSize.Data; }
      set { tournamentSize.Data = value; }
    }
    private DoubleData mutationRate = new DoubleData();
    public double MutationRate {
      get { return mutationRate.Data; }
      set { mutationRate.Data = value; }
    }
    private IntData parents = new IntData();
    private IntData populationSize = new IntData();
    public int PopulationSize {
      get { return populationSize.Data; }
      set {
        populationSize.Data = value;
        parents.Data = value * 2;
      }
    }

    private BoolData setSeedRandomly = new BoolData();
    public bool SetSeedRandomly {
      get { return setSeedRandomly.Data; }
      set { setSeedRandomly.Data = value; }
    }

    private IntData seed = new IntData();
    public int Seed {
      get { return seed.Data; }
      set { seed.Data = value; }
    }

    public IOperator ProblemInjector {
      get { return algorithm.SubOperators[0]; }
      set {
        value.Name = "ProblemInjector";
        algorithm.RemoveSubOperator(0);
        algorithm.AddSubOperator(value, 0);
      }
    }

    private IntData elites = new IntData();
    public int Elites {
      get { return elites.Data; }
      set { elites.Data = value; }
    }

    private int maxTreeSize = 50;
    public int MaxTreeSize {
      get { return maxTreeSize; }
      set { maxTreeSize = value; }
    }

    private int maxTreeHeight = 8;
    public int MaxTreeHeight {
      get { return maxTreeHeight; }
      set { maxTreeHeight = value; }
    }
    private double punishmentFactor = 10.0;
    private bool useEstimatedTargetValue = false;
    private double fullTreeShakingFactor = 0.1;
    private double onepointShakingFactor = 1.0;
    private IOperator algorithm;

    private SequentialEngine.SequentialEngine engine;
    public IEngine Engine {
      get { return engine; }
    }

    public StandardGP() {
      PopulationSize = 10000;
      MaxGenerations = 100;
      TournamentSize = 7;
      MutationRate = 0.15;
      Elites = 1;
      MaxTreeSize = 100;
      MaxTreeHeight = 10;
      engine = new SequentialEngine.SequentialEngine();
      CombinedOperator algo = CreateAlgorithm();
      engine.OperatorGraph.AddOperator(algo);
      engine.OperatorGraph.InitialOperator = algo;
    }

    private CombinedOperator CreateAlgorithm() {
      CombinedOperator algo = new CombinedOperator();
      algo.Name = "StandardGP";
      SequentialProcessor seq = new SequentialProcessor();
      EmptyOperator problemInjectorPlaceholder = new EmptyOperator();
      RandomInjector randomInjector = new RandomInjector();
      randomInjector.GetVariable("SetSeedRandomly").Value = setSeedRandomly;
      randomInjector.GetVariable("Seed").Value = seed;
      randomInjector.Name = "Random Injector";
      VariableInjector globalInjector = CreateGlobalInjector();
      CombinedOperator initialization = CreateInitialization();
      initialization.Name = "Initialization";
      FunctionLibraryInjector funLibInjector = new FunctionLibraryInjector();
      CombinedOperator mainLoop = CreateMainLoop();
      mainLoop.Name = "Main loop";

      ProbabilisticTreeCreator treeCreator = new ProbabilisticTreeCreator();
      treeCreator.Name = "Tree generator";
      treeCreator.GetVariableInfo("OperatorLibrary").ActualName = "FunctionLibrary";
      treeCreator.GetVariableInfo("MinTreeSize").Local = true;
      treeCreator.AddVariable(new HeuristicLab.Core.Variable("MinTreeSize", new IntData(3)));
      MeanSquaredErrorEvaluator evaluator = new MeanSquaredErrorEvaluator();
      evaluator.GetVariableInfo("MSE").ActualName = "Quality";
      evaluator.GetVariableInfo("SamplesStart").ActualName = "TrainingSamplesStart";
      evaluator.GetVariableInfo("SamplesEnd").ActualName = "TrainingSamplesEnd";
      evaluator.Name = "Evaluator";
      StandardCrossOver crossover = new StandardCrossOver();
      crossover.Name = "Crossover";
      crossover.GetVariableInfo("OperatorLibrary").ActualName = "FunctionLibrary";
      CombinedOperator manipulator = CreateManipulator();
      manipulator.Name = "Manipulator";
      TournamentSelector selector = new TournamentSelector();
      selector.Name = "Selector";
      selector.GetVariableInfo("Selected").ActualName = "Parents";
      selector.GetVariableInfo("GroupSize").Local = false;
      selector.RemoveVariable("GroupSize");
      selector.GetVariableInfo("GroupSize").ActualName = "TournamentSize";
      LeftReducer cleanUp = new LeftReducer();

      seq.AddSubOperator(problemInjectorPlaceholder);
      seq.AddSubOperator(randomInjector);
      seq.AddSubOperator(globalInjector);
      seq.AddSubOperator(funLibInjector);
      seq.AddSubOperator(initialization);
      seq.AddSubOperator(mainLoop);
      seq.AddSubOperator(cleanUp);

      initialization.AddSubOperator(treeCreator);
      initialization.AddSubOperator(evaluator);

      mainLoop.AddSubOperator(selector);
      mainLoop.AddSubOperator(crossover);
      mainLoop.AddSubOperator(manipulator);
      mainLoop.AddSubOperator(evaluator);
      algo.OperatorGraph.AddOperator(seq);
      algo.OperatorGraph.InitialOperator = seq;
      this.algorithm = seq;
      return algo;
    }

    private VariableInjector CreateGlobalInjector() {
      VariableInjector injector = new VariableInjector();
      injector.Name = "Global Injector";
      injector.AddVariable(new HeuristicLab.Core.Variable("Generations", new IntData(0)));
      injector.AddVariable(new HeuristicLab.Core.Variable("MaxGenerations", maxGenerations));
      injector.AddVariable(new HeuristicLab.Core.Variable("MutationRate", mutationRate));
      injector.AddVariable(new HeuristicLab.Core.Variable("PopulationSize", populationSize));
      injector.AddVariable(new HeuristicLab.Core.Variable("Parents", parents));
      injector.AddVariable(new HeuristicLab.Core.Variable("Elites", elites));
      injector.AddVariable(new HeuristicLab.Core.Variable("TournamentSize", tournamentSize));
      injector.AddVariable(new HeuristicLab.Core.Variable("Maximization", new BoolData(false)));
      injector.AddVariable(new HeuristicLab.Core.Variable("MaxTreeHeight", new IntData(maxTreeHeight)));
      injector.AddVariable(new HeuristicLab.Core.Variable("MaxTreeSize", new IntData(maxTreeSize)));
      injector.AddVariable(new HeuristicLab.Core.Variable("EvaluatedSolutions", new IntData(0)));
      injector.AddVariable(new HeuristicLab.Core.Variable("TotalEvaluatedNodes", new DoubleData(0)));
      injector.AddVariable(new HeuristicLab.Core.Variable("PunishmentFactor", new DoubleData(punishmentFactor)));
      injector.AddVariable(new HeuristicLab.Core.Variable("UseEstimatedTargetValue", new BoolData(useEstimatedTargetValue)));
      return injector;
    }

    private CombinedOperator CreateManipulator() {
      CombinedOperator manipulator = new CombinedOperator();
      StochasticMultiBranch multibranch = new StochasticMultiBranch();
      FullTreeShaker fullTreeShaker = new FullTreeShaker();
      fullTreeShaker.GetVariableInfo("OperatorLibrary").ActualName = "FunctionLibrary";
      fullTreeShaker.GetVariableInfo("ShakingFactor").Local = true;
      fullTreeShaker.AddVariable(new HeuristicLab.Core.Variable("ShakingFactor", new DoubleData(fullTreeShakingFactor)));

      OnePointShaker onepointShaker = new OnePointShaker();
      onepointShaker.GetVariableInfo("OperatorLibrary").ActualName = "FunctionLibrary";
      onepointShaker.GetVariableInfo("ShakingFactor").Local = true;
      onepointShaker.AddVariable(new HeuristicLab.Core.Variable("ShakingFactor", new DoubleData(onepointShakingFactor)));
      ChangeNodeTypeManipulation changeNodeTypeManipulation = new ChangeNodeTypeManipulation();
      changeNodeTypeManipulation.GetVariableInfo("OperatorLibrary").ActualName = "FunctionLibrary";
      CutOutNodeManipulation cutOutNodeManipulation = new CutOutNodeManipulation();
      cutOutNodeManipulation.GetVariableInfo("OperatorLibrary").ActualName = "FunctionLibrary";
      DeleteSubTreeManipulation deleteSubTreeManipulation = new DeleteSubTreeManipulation();
      deleteSubTreeManipulation.GetVariableInfo("OperatorLibrary").ActualName = "FunctionLibrary";
      SubstituteSubTreeManipulation substituteSubTreeManipulation = new SubstituteSubTreeManipulation();
      substituteSubTreeManipulation.GetVariableInfo("OperatorLibrary").ActualName = "FunctionLibrary";

      IOperator[] manipulators = new IOperator[] {
        onepointShaker, fullTreeShaker,
        changeNodeTypeManipulation,
        cutOutNodeManipulation,
        deleteSubTreeManipulation,
        substituteSubTreeManipulation};

      DoubleArrayData probabilities = new DoubleArrayData(new double[manipulators.Length]);
      for (int i = 0; i < manipulators.Length; i++) {
        probabilities.Data[i] = 1.0;
        multibranch.AddSubOperator(manipulators[i]);
      }
      multibranch.GetVariableInfo("Probabilities").Local = true;
      multibranch.AddVariable(new HeuristicLab.Core.Variable("Probabilities", probabilities));

      manipulator.OperatorGraph.AddOperator(multibranch);
      manipulator.OperatorGraph.InitialOperator = multibranch;
      return manipulator;
    }

    private CombinedOperator CreateInitialization() {
      CombinedOperator init = new CombinedOperator();
      SequentialProcessor seq = new SequentialProcessor();
      SubScopesCreater subScopesCreater = new SubScopesCreater();
      subScopesCreater.GetVariableInfo("SubScopes").ActualName = "PopulationSize";
      UniformSequentialSubScopesProcessor subScopesProc = new UniformSequentialSubScopesProcessor();
      SequentialProcessor individualSeq = new SequentialProcessor();
      OperatorExtractor treeCreater = new OperatorExtractor();
      treeCreater.Name = "Tree generator (extr.)";
      treeCreater.GetVariableInfo("Operator").ActualName = "Tree generator";
      OperatorExtractor evaluator = new OperatorExtractor();
      evaluator.Name = "Evaluator (extr.)";
      evaluator.GetVariableInfo("Operator").ActualName = "Evaluator";
      MeanSquaredErrorEvaluator validationEvaluator = new MeanSquaredErrorEvaluator();
      validationEvaluator.GetVariableInfo("MSE").ActualName = "ValidationQuality";
      validationEvaluator.GetVariableInfo("SamplesStart").ActualName = "ValidationSamplesStart";
      validationEvaluator.GetVariableInfo("SamplesEnd").ActualName = "ValidationSamplesEnd";
      Counter evalCounter = new Counter();
      evalCounter.GetVariableInfo("Value").ActualName = "EvaluatedSolutions";
      Sorter sorter = new Sorter();
      sorter.GetVariableInfo("Descending").ActualName = "Maximization";
      sorter.GetVariableInfo("Value").ActualName = "Quality";

      seq.AddSubOperator(subScopesCreater);
      seq.AddSubOperator(subScopesProc);
      seq.AddSubOperator(sorter);

      subScopesProc.AddSubOperator(individualSeq);
      individualSeq.AddSubOperator(treeCreater);
      individualSeq.AddSubOperator(evaluator);
      individualSeq.AddSubOperator(validationEvaluator);
      individualSeq.AddSubOperator(evalCounter);

      init.OperatorGraph.AddOperator(seq);
      init.OperatorGraph.InitialOperator = seq;
      return init;
    }

    private CombinedOperator CreateMainLoop() {
      CombinedOperator main = new CombinedOperator();
      SequentialProcessor seq = new SequentialProcessor();
      CombinedOperator childCreater = CreateChildCreater();
      childCreater.Name = "Create children";
      CombinedOperator replacement = CreateReplacement();
      replacement.Name = "Replacement";
      BestSolutionStorer solutionStorer = CreateBestSolutionStorer();
      BestAverageWorstQualityCalculator qualityCalculator = new BestAverageWorstQualityCalculator();
      BestAverageWorstQualityCalculator validationQualityCalculator = new BestAverageWorstQualityCalculator();
      validationQualityCalculator.Name = "ValidationQualityCalculator";
      validationQualityCalculator.GetVariableInfo("BestQuality").ActualName = "BestValidationQuality";
      validationQualityCalculator.GetVariableInfo("AverageQuality").ActualName = "AverageValidationQuality";
      validationQualityCalculator.GetVariableInfo("WorstQuality").ActualName = "WorstValidationQuality";
      DataCollector collector = new DataCollector();
      ItemList<StringData> names = collector.GetVariable("VariableNames").GetValue<ItemList<StringData>>();
      names.Add(new StringData("BestQuality"));
      names.Add(new StringData("AverageQuality"));
      names.Add(new StringData("WorstQuality"));
      names.Add(new StringData("BestValidationQuality"));
      names.Add(new StringData("AverageValidationQuality"));
      names.Add(new StringData("WorstValidationQuality"));
      LinechartInjector lineChartInjector = new LinechartInjector();
      lineChartInjector.GetVariableInfo("Linechart").ActualName = "Quality Linechart";
      lineChartInjector.GetVariable("NumberOfLines").GetValue<IntData>().Data = 6;
      QualityLogger qualityLogger = new QualityLogger();
      QualityLogger validationQualityLogger = new QualityLogger();
      validationQualityCalculator.Name = "ValidationQualityLogger";
      validationQualityLogger.GetVariableInfo("Quality").ActualName = "ValidationQuality";
      validationQualityLogger.GetVariableInfo("QualityLog").ActualName = "ValidationQualityLog";
      Counter counter = new Counter();
      counter.GetVariableInfo("Value").ActualName = "Generations";
      LessThanComparator comparator = new LessThanComparator();
      comparator.GetVariableInfo("LeftSide").ActualName = "Generations";
      comparator.GetVariableInfo("RightSide").ActualName = "MaxGenerations";
      comparator.GetVariableInfo("Result").ActualName = "GenerationsCondition";
      ConditionalBranch cond = new ConditionalBranch();
      cond.GetVariableInfo("Condition").ActualName = "GenerationsCondition";

      seq.AddSubOperator(childCreater);
      seq.AddSubOperator(replacement);
      seq.AddSubOperator(solutionStorer);
      seq.AddSubOperator(qualityCalculator);
      seq.AddSubOperator(validationQualityCalculator);
      seq.AddSubOperator(collector);
      seq.AddSubOperator(lineChartInjector);
      seq.AddSubOperator(qualityLogger);
      seq.AddSubOperator(validationQualityLogger);
      seq.AddSubOperator(counter);
      seq.AddSubOperator(comparator);
      seq.AddSubOperator(cond);
      cond.AddSubOperator(seq);

      main.OperatorGraph.AddOperator(seq);
      main.OperatorGraph.InitialOperator = seq;
      return main;
    }

    private BestSolutionStorer CreateBestSolutionStorer() {
      BestSolutionStorer solutionStorer = new BestSolutionStorer();
      solutionStorer.GetVariableInfo("Quality").ActualName = "ValidationQuality";
      solutionStorer.GetVariableInfo("BestSolution").ActualName = "BestValidationSolution";
      SequentialProcessor bestSolutionProcessor = new SequentialProcessor();
      MeanAbsolutePercentageErrorEvaluator trainingMapeEvaluator = new MeanAbsolutePercentageErrorEvaluator();
      trainingMapeEvaluator.Name = "TrainingMapeEvaluator";
      trainingMapeEvaluator.GetVariableInfo("MAPE").ActualName = "TrainingMAPE";
      trainingMapeEvaluator.GetVariableInfo("SamplesStart").ActualName = "TrainingSamplesStart";
      trainingMapeEvaluator.GetVariableInfo("SamplesEnd").ActualName = "TrainingSamplesEnd";
      MeanAbsolutePercentageErrorEvaluator validationMapeEvaluator = new MeanAbsolutePercentageErrorEvaluator();
      validationMapeEvaluator.Name = "ValidationMapeEvaluator";
      validationMapeEvaluator.GetVariableInfo("MAPE").ActualName = "ValidationMAPE";
      validationMapeEvaluator.GetVariableInfo("SamplesStart").ActualName = "ValidationSamplesStart";
      validationMapeEvaluator.GetVariableInfo("SamplesEnd").ActualName = "ValidationSamplesEnd";
      ProgrammableOperator progOperator = new ProgrammableOperator();
      progOperator.RemoveVariableInfo("Result");
      progOperator.AddVariableInfo(new HeuristicLab.Core.VariableInfo("EvaluatedSolutions", "", typeof(IntData), VariableKind.In));
      progOperator.Code = @"
int evalSolutions = EvaluatedSolutions.Data;
scope.AddVariable(new Variable(""EvaluatedSolutions"", new IntData(evalSolutions)));
";
      solutionStorer.AddSubOperator(bestSolutionProcessor);
      bestSolutionProcessor.AddSubOperator(trainingMapeEvaluator);
      bestSolutionProcessor.AddSubOperator(validationMapeEvaluator);
      bestSolutionProcessor.AddSubOperator(progOperator);
      return solutionStorer;
    }

    private CombinedOperator CreateReplacement() {
      CombinedOperator replacement = new CombinedOperator();
      SequentialProcessor seq = new SequentialProcessor();
      SequentialSubScopesProcessor seqScopeProc = new SequentialSubScopesProcessor();
      SequentialProcessor selectedProc = new SequentialProcessor();
      LeftSelector leftSelector = new LeftSelector();
      leftSelector.GetVariableInfo("Selected").ActualName = "Elites";
      RightReducer rightReducer = new RightReducer();

      SequentialProcessor remainingProc = new SequentialProcessor();
      RightSelector rightSelector = new RightSelector();
      rightSelector.GetVariableInfo("Selected").ActualName = "Elites";
      LeftReducer leftReducer = new LeftReducer();
      MergingReducer mergingReducer = new MergingReducer();
      Sorter sorter = new Sorter();
      sorter.GetVariableInfo("Descending").ActualName = "Maximization";
      sorter.GetVariableInfo("Value").ActualName = "Quality";

      seq.AddSubOperator(seqScopeProc);
      seqScopeProc.AddSubOperator(selectedProc);
      selectedProc.AddSubOperator(leftSelector);
      selectedProc.AddSubOperator(rightReducer);

      seqScopeProc.AddSubOperator(remainingProc);
      remainingProc.AddSubOperator(rightSelector);
      remainingProc.AddSubOperator(leftReducer);
      seq.AddSubOperator(mergingReducer);
      seq.AddSubOperator(sorter);
      replacement.OperatorGraph.AddOperator(seq);
      replacement.OperatorGraph.InitialOperator = seq;
      return replacement;
    }

    private CombinedOperator CreateChildCreater() {
      CombinedOperator childCreater = new CombinedOperator();
      SequentialProcessor seq = new SequentialProcessor();
      OperatorExtractor selector = new OperatorExtractor();
      selector.Name = "Selector (extr.)";
      selector.GetVariableInfo("Operator").ActualName = "Selector";
      SequentialSubScopesProcessor seqScopesProc = new SequentialSubScopesProcessor();
      EmptyOperator emptyOpt = new EmptyOperator();
      SequentialProcessor selectedProc = new SequentialProcessor();
      OperatorExtractor crossover = new OperatorExtractor();
      crossover.Name = "Crossover (extr.)";
      crossover.GetVariableInfo("Operator").ActualName = "Crossover";
      UniformSequentialSubScopesProcessor individualProc = new UniformSequentialSubScopesProcessor();
      SequentialProcessor individualSeqProc = new SequentialProcessor();
      StochasticBranch cond = new StochasticBranch();
      cond.GetVariableInfo("Probability").ActualName = "MutationRate";
      OperatorExtractor manipulator = new OperatorExtractor();
      manipulator.Name = "Manipulator (extr.)";
      manipulator.GetVariableInfo("Operator").ActualName = "Manipulator";
      OperatorExtractor evaluator = new OperatorExtractor();
      evaluator.Name = "Evaluator (extr.)";
      evaluator.GetVariableInfo("Operator").ActualName = "Evaluator";
      MeanSquaredErrorEvaluator validationEvaluator = new MeanSquaredErrorEvaluator();
      validationEvaluator.GetVariableInfo("MSE").ActualName = "ValidationQuality";
      validationEvaluator.GetVariableInfo("SamplesStart").ActualName = "ValidationSamplesStart";
      validationEvaluator.GetVariableInfo("SamplesEnd").ActualName = "ValidationSamplesEnd";
      Counter evalCounter = new Counter();
      evalCounter.GetVariableInfo("Value").ActualName = "EvaluatedSolutions";

      Sorter sorter = new Sorter();
      sorter.GetVariableInfo("Descending").ActualName = "Maximization";
      sorter.GetVariableInfo("Value").ActualName = "Quality";


      seq.AddSubOperator(selector);
      seq.AddSubOperator(seqScopesProc);
      seqScopesProc.AddSubOperator(emptyOpt);
      seqScopesProc.AddSubOperator(selectedProc);
      selectedProc.AddSubOperator(crossover);
      selectedProc.AddSubOperator(individualProc);
      individualProc.AddSubOperator(individualSeqProc);
      individualSeqProc.AddSubOperator(cond);
      cond.AddSubOperator(manipulator);
      individualSeqProc.AddSubOperator(evaluator);
      individualSeqProc.AddSubOperator(validationEvaluator);
      individualSeqProc.AddSubOperator(evalCounter);
      selectedProc.AddSubOperator(sorter);

      childCreater.OperatorGraph.AddOperator(seq);
      childCreater.OperatorGraph.InitialOperator = seq;
      return childCreater;
    }

    public IEditor CreateEditor() {
      return new StandardGpEditor(this);
    }

    public override IView CreateView() {
      return new StandardGpEditor(this);
    }

    public override object Clone(IDictionary<Guid, object> clonedObjects) {
      StandardGP clone = new StandardGP();
      clonedObjects.Add(Guid, clone);
      clone.engine = (SequentialEngine.SequentialEngine)Auxiliary.Clone(Engine, clonedObjects);
      return clone;
    }
    #region SetReferences Method
    private void SetReferences() {
      // SGA
      CombinedOperator co1 = (CombinedOperator)Engine.OperatorGraph.InitialOperator;
      // SequentialProcessor in SGA
      algorithm = (SequentialProcessor)co1.OperatorGraph.InitialOperator;
      // RandomInjector
      RandomInjector ri = (RandomInjector)algorithm.SubOperators[1];
      setSeedRandomly = ri.GetVariable("SetSeedRandomly").GetValue<BoolData>();
      seed = ri.GetVariable("Seed").GetValue<IntData>();
      // VariableInjector
      VariableInjector vi = (VariableInjector)algorithm.SubOperators[2];
      populationSize = vi.GetVariable("PopulationSize").GetValue<IntData>();
      parents = vi.GetVariable("Parents").GetValue<IntData>();
      maxGenerations = vi.GetVariable("MaxGenerations").GetValue<IntData>();
      mutationRate = vi.GetVariable("MutationRate").GetValue<DoubleData>();
      elites = vi.GetVariable("Elites").GetValue<IntData>();
    }
    #endregion

    #region Persistence Methods
    public override XmlNode GetXmlNode(string name, XmlDocument document, IDictionary<Guid, IStorable> persistedObjects) {
      XmlNode node = base.GetXmlNode(name, document, persistedObjects);
      node.AppendChild(PersistenceManager.Persist("Engine", Engine, document, persistedObjects));
      return node;
    }
    public override void Populate(XmlNode node, IDictionary<Guid, IStorable> restoredObjects) {
      base.Populate(node, restoredObjects);
      engine = (SequentialEngine.SequentialEngine)PersistenceManager.Restore(node.SelectSingleNode("Engine"), restoredObjects);
      SetReferences();
    }
    #endregion
  }
}