#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2014 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.Encodings.SymbolicExpressionTreeEncoding;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
  [StorableClass]
  [Item("Sliding Window Best Classification Solutions Collection", "A collection of best sliding window solutions for symbolic classification.")]
  public class SlidingWindowBestClassificationSolutionsCollection : SlidingWindowBestSolutionsCollection {
    public new IClassificationProblemData ProblemData {
      get { return (IClassificationProblemData)base.ProblemData; }
      set { base.ProblemData = value; }
    }
    public ISymbolicClassificationModelCreator ModelCreator { get; set; }
    [StorableConstructor]
    protected SlidingWindowBestClassificationSolutionsCollection(bool deserializing) : base(deserializing) { }
    [StorableHook(HookType.AfterDeserialization)]
    private void AfterDeserialization() { }
    public SlidingWindowBestClassificationSolutionsCollection(SlidingWindowBestClassificationSolutionsCollection original, Cloner cloner)
      : base(original, cloner) {
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new SlidingWindowBestClassificationSolutionsCollection(this, cloner);
    }
    public SlidingWindowBestClassificationSolutionsCollection() { }
    public override ISymbolicDataAnalysisModel CreateModel(ISymbolicExpressionTree tree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter,
      double lowerEstimationLimit = double.MinValue, double upperEstimationLimit = double.MaxValue) {
      var model = ModelCreator.CreateSymbolicClassificationModel(tree, interpreter, lowerEstimationLimit, upperEstimationLimit);
      model.RecalculateModelParameters(ProblemData, ProblemData.TrainingIndices);
      return model;
    }
    public override ISymbolicDataAnalysisSolution CreateSolution(ISymbolicDataAnalysisModel model, IDataAnalysisProblemData problemData) {
      return new SymbolicClassificationSolution((ISymbolicClassificationModel)model, (IClassificationProblemData)problemData);
    }
  }
}