source: branches/PerformanceComparison/HeuristicLab.Analysis.FitnessLandscape/3.3/Algorithms/LocalAnalysis.cs @ 13583

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2010 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.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Optimization.Operators;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Random;
using System;
using System.Linq;

namespace HeuristicLab.Analysis.FitnessLandscape {
  [Item("Local Analysis", "A local analysis algorithm.")]
  [StorableClass]
  public abstract class LocalAnalysis<T> : HeuristicOptimizationEngineAlgorithm, IStorableContent where T : class, IOperator, new() {
    public string Filename { get; set; }

    #region Problem Properties
    public override Type ProblemType {
      get { return typeof(ISingleObjectiveHeuristicOptimizationProblem); }
    }
    public new ISingleObjectiveHeuristicOptimizationProblem Problem {
      get { return (ISingleObjectiveHeuristicOptimizationProblem)base.Problem; }
      set { base.Problem = value; }
    }
    #endregion

    #region Parameter Properties
    public IFixedValueParameter<IntValue> SeedParameter {
      get { return (IFixedValueParameter<IntValue>)Parameters["Seed"]; }
    }
    public IFixedValueParameter<BoolValue> SetSeedRandomlyParameter {
      get { return (IFixedValueParameter<BoolValue>)Parameters["SetSeedRandomly"]; }
    }
    public IConstrainedValueParameter<IManipulator> MutatorParameter {
      get { return (IConstrainedValueParameter<IManipulator>)Parameters["Mutator"]; }
    }
    public IFixedValueParameter<IntValue> MaximumIterationsParameter {
      get { return (IFixedValueParameter<IntValue>)Parameters["MaximumIterations"]; }
    }
    public IValueParameter<MultiAnalyzer> AnalyzerParameter {
      get { return (IValueParameter<MultiAnalyzer>)Parameters["Analyzer"]; }
    }
    public IFixedValueParameter<T> SelectorParameter {
      get { return (IFixedValueParameter<T>)Parameters["Selector"]; }
    }
    #endregion

    #region Properties
    protected RandomCreator RandomCreator {
      get { return (RandomCreator)OperatorGraph.InitialOperator; }
    }
    protected VariableCreator VariableCreator {
      get { return (VariableCreator)RandomCreator.Successor; }
    }
    protected SolutionsCreator SolutionsCreator {
      get { return (SolutionsCreator)VariableCreator.Successor; }
    }
    protected LocalAnalysisMainLoop MainLoop {
      get { return (LocalAnalysisMainLoop)SolutionsCreator.Successor; }
    }

    [Storable]
    private QualityTrailMultiAnalyzer qualityTrailAnalyzer;
    #endregion

    [StorableConstructor]
    protected LocalAnalysis(bool deserializing) : base(deserializing) { }
    protected LocalAnalysis(LocalAnalysis<T> original, Cloner cloner)
      : base(original, cloner) {
      qualityTrailAnalyzer = cloner.Clone(original.qualityTrailAnalyzer);
      RegisterEventHandlers();
    }
    protected LocalAnalysis(T selector)
      : base() {
      Parameters.Add(new FixedValueParameter<IntValue>("Seed", "The random seed used to initialize the new pseudo random number generator.", new IntValue(0)));
      Parameters.Add(new FixedValueParameter<BoolValue>("SetSeedRandomly", "True if the random seed should be set to a random value, otherwise false.", new BoolValue(true)));
      Parameters.Add(new ConstrainedValueParameter<IManipulator>("Mutator", "Mutation operator."));
      Parameters.Add(new FixedValueParameter<IntValue>("MaximumIterations", "The maximum number of generations which should be processed.", new IntValue(10000)));
      Parameters.Add(new ValueParameter<MultiAnalyzer>("Analyzer", "The operator used to analyze the solution and moves.", new MultiAnalyzer()));
      Parameters.Add(new FixedValueParameter<T>("Selector", "Selection operator.", selector));

      RandomCreator randomCreator = new RandomCreator();
      VariableCreator variableCreator = new VariableCreator();
      SolutionsCreator solutionsCreator = new SolutionsCreator();
      LocalAnalysisMainLoop laMainLoop = new LocalAnalysisMainLoop();
      OperatorGraph.InitialOperator = randomCreator;

      randomCreator.RandomParameter.ActualName = "Random";
      randomCreator.SeedParameter.ActualName = SeedParameter.Name;
      randomCreator.SeedParameter.Value = null;
      randomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameter.Name;
      randomCreator.SetSeedRandomlyParameter.Value = null;
      randomCreator.Successor = variableCreator;

      variableCreator.Successor = solutionsCreator;

      solutionsCreator.NumberOfSolutions = new IntValue(1);
      solutionsCreator.Successor = laMainLoop;

      laMainLoop.MutatorParameter.ActualName = MutatorParameter.Name;
      laMainLoop.SelectorParameter.ActualName = SelectorParameter.Name;
      laMainLoop.MaximumIterationsParameter.ActualName = MaximumIterationsParameter.Name;
      laMainLoop.RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
      laMainLoop.ResultsParameter.ActualName = "Results";
      laMainLoop.AnalyzerParameter.ActualName = AnalyzerParameter.Name;

      qualityTrailAnalyzer = new QualityTrailMultiAnalyzer();
      qualityTrailAnalyzer.UpdateIntervalParameter.Value = null;
      qualityTrailAnalyzer.UpdateIntervalParameter.ActualName = "MaximumIterations";
      AnalyzerParameter.Value.Operators.Add(qualityTrailAnalyzer, true);

      RegisterEventHandlers();
    }

    public override void Prepare() {
      if (Problem != null) base.Prepare();
    }

    #region Events
    protected override void OnProblemChanged() {
      base.OnProblemChanged();
      UpdateMutators();
      Parameterize();
      Problem.Evaluator.QualityParameter.ActualNameChanged += Evaluator_QualityParameter_ActualNameChanged;
    }
    protected override void Problem_SolutionCreatorChanged(object sender, EventArgs e) {
      base.Problem_SolutionCreatorChanged(sender, e);
      Parameterize();
    }
    protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
      base.Problem_EvaluatorChanged(sender, e);
      Parameterize();
      Problem.Evaluator.QualityParameter.ActualNameChanged += Evaluator_QualityParameter_ActualNameChanged;
    }
    protected override void Problem_OperatorsChanged(object sender, EventArgs e) {
      UpdateMutators();
      Parameterize();
      base.Problem_OperatorsChanged(sender, e);
    }
    private void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) {
      Parameterize();
    }
    #endregion

    #region Helpers
    private void RegisterEventHandlers() {
      if (Problem != null) {
        Problem.Evaluator.QualityParameter.ActualNameChanged += Evaluator_QualityParameter_ActualNameChanged;
      }
    }

    private void UpdateMutators() {
      var selected = MutatorParameter.Value;
      MutatorParameter.ValidValues.Clear();
      foreach (var m in Problem.Operators.OfType<IManipulator>()) {
        MutatorParameter.ValidValues.Add(m);
        if (selected != null && selected.GetType() == m.GetType()) MutatorParameter.Value = m;
      }
    }

    protected virtual void Parameterize() {
      if (Problem == null) return;

      MainLoop.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
      MainLoop.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
      MainLoop.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
      foreach (var sOp in Problem.Operators.OfType<IStochasticOperator>()) {
        sOp.RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
      }
      foreach (var iOp in Problem.Operators.OfType<IIterationBasedOperator>()) {
        iOp.IterationsParameter.ActualName = "Iterations";
        iOp.MaximumIterationsParameter.ActualName = MaximumIterationsParameter.Name;
      }
      var sEval = Problem.Evaluator as IStochasticOperator;
      if (sEval != null) sEval.RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
      var sCrea = Problem.SolutionCreator as IStochasticOperator;
      if (sCrea != null) sCrea.RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
      var sSel = SelectorParameter.Value as IStochasticOperator;
      if (sSel != null) sSel.RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
      var sel = SelectorParameter.Value as ISelector;
      if (sel != null) {
        sel.NumberOfSelectedSubScopesParameter.Value = new IntValue(1);
        sel.CopySelected = new BoolValue(false);
        var sos = sel as ISingleObjectiveSelector;
        if (sos != null) {
          sos.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
          sos.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
        }
      }
    }
    #endregion
  }
}