source: branches/Persistence Test/HeuristicLab.GP.StructureIdentification.TimeSeries/3.3/OffspringSelectionGPTimeSeriesPrognosis.cs @ 2491

#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 HeuristicLab.Core;
using HeuristicLab.Modeling;
using HeuristicLab.Operators;
using System;
using HeuristicLab.Data;
using HeuristicLab.GP.Algorithms;

namespace HeuristicLab.GP.StructureIdentification.TimeSeries {
  public class OffspringSelectionGPTimeSeriesPrognosis : HeuristicLab.GP.StructureIdentification.OffspringSelectionGPRegression, ITimeSeriesAlgorithm {
    public override string Name {
      get {
        return base.Name + " - time series prognosis";
      }
    }

    public int MinTimeOffset {
      get { return GetVariableInjector().GetVariable("MinTimeOffset").GetValue<IntData>().Data; }
      set { GetVariableInjector().GetVariable("MinTimeOffset").GetValue<IntData>().Data = value; }
    }

    public int MaxTimeOffset {
      get { return GetVariableInjector().GetVariable("MaxTimeOffset").GetValue<IntData>().Data; }
      set { GetVariableInjector().GetVariable("MaxTimeOffset").GetValue<IntData>().Data = value; }
    }

    public bool UseEstimatedTargetValue {
      get { return GetVariableInjector().GetVariable("UseEstimatedTargetValue").GetValue<BoolData>().Data; }
      set { GetVariableInjector().GetVariable("UseEstimatedTargetValue").GetValue<BoolData>().Data = value; }
    }

    protected override IOperator CreateProblemInjector() {
      return DefaultTimeSeriesOperators.CreateProblemInjector();
    }

    protected override IOperator CreateFunctionLibraryInjector() {
      CombinedOperator op = new CombinedOperator();
      op.Name = "FunctionLibraryInjector";
      SequentialProcessor seq = new SequentialProcessor();
      FunctionLibraryInjector funLibInjector = new FunctionLibraryInjector();
      funLibInjector.GetVariable("Differentials").Value = new BoolData(true);
      seq.AddSubOperator(funLibInjector);
      seq.AddSubOperator(new HL3TreeEvaluatorInjector());
      op.OperatorGraph.AddOperator(seq);
      op.OperatorGraph.InitialOperator = seq;
      return op;
    }

    protected override VariableInjector CreateGlobalInjector() {
      VariableInjector injector = base.CreateGlobalInjector();
      injector.AddVariable(new HeuristicLab.Core.Variable("MinTimeOffset", new IntData()));
      injector.AddVariable(new HeuristicLab.Core.Variable("MaxTimeOffset", new IntData()));
      injector.AddVariable(new HeuristicLab.Core.Variable("UseEstimatedTargetValue", new BoolData()));
      return injector;
    }

    protected override IOperator CreateModelAnalyzerOperator() {
      return DefaultTimeSeriesOperators.CreatePostProcessingOperator();
    }

    protected override IAnalyzerModel CreateGPModel() {
      var model = new AnalyzerModel();
      var bestModelScope = Engine.GlobalScope.SubScopes[0];
      model.SetMetaData("SelectionPressure", bestModelScope.GetVariableValue<DoubleData>("SelectionPressure", false).Data);
      DefaultStructureIdentificationOperators.PopulateAnalyzerModel(bestModelScope, model);
      DefaultTimeSeriesOperators.PopulateAnalyzerModel(bestModelScope, model);
      return model;
    }
  }
}