#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2015 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.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
using HeuristicLab.EvolutionTracking;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
  [Item("SymbolicDataAnalysisGenealogyAnalyzer", "Genealogy analyzer for symbolic data analysis problems")]
  [StorableClass]
  public class SymbolicDataAnalysisGenealogyAnalyzer : GenealogyAnalyzer<ISymbolicExpressionTree> {
    private const string EvaluatorParameterName = "Evaluator";
    private const string ProblemDataParameterName = "ProblemData";
    private const string InterpreterParameterName = "SymbolicExpressionTreeInterpreter";
    private const string EstimationLimitsParameterName = "EstimationLimits";
    private const string ApplyLinearScalingParameterName = "ApplyLinearScaling";

    #region parameters
    public ILookupParameter<ISingleObjectiveEvaluator> EvaluatorParameter {
      get {
        return (ILookupParameter<ISingleObjectiveEvaluator>)Parameters[EvaluatorParameterName];
      }
    }

    public ILookupParameter<IDataAnalysisProblemData> ProblemDataParameter {
      get {
        return (ILookupParameter<IDataAnalysisProblemData>)Parameters[ProblemDataParameterName];
      }
    }

    public ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter> InterpreterParameter {
      get {
        return (ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>)Parameters[InterpreterParameterName];
      }
    }

    public ILookupParameter<DoubleLimit> EstimationLimitsParameter {
      get { return (ILookupParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; }
    }

    public ILookupParameter<BoolValue> ApplyLinearScalingParameter {
      get { return (ILookupParameter<BoolValue>)Parameters[ApplyLinearScalingParameterName]; }
    }
    #endregion

    public SymbolicDataAnalysisGenealogyAnalyzer() {
      Parameters.Add(new LookupParameter<ISingleObjectiveEvaluator>(EvaluatorParameterName));
      Parameters.Add(new LookupParameter<IDataAnalysisProblemData>(ProblemDataParameterName));
      Parameters.Add(new LookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>(InterpreterParameterName));
      Parameters.Add(new LookupParameter<DoubleLimit>(EstimationLimitsParameterName));
      Parameters.Add(new LookupParameter<BoolValue>(ApplyLinearScalingParameterName));
    }

    public SymbolicDataAnalysisGenealogyAnalyzer(SymbolicDataAnalysisGenealogyAnalyzer original, Cloner cloner)
      : base(original, cloner) {
    }

    public override IDeepCloneable Clone(Cloner cloner) {
      return new SymbolicDataAnalysisGenealogyAnalyzer(this, cloner);
    }

    [StorableConstructor]
    protected SymbolicDataAnalysisGenealogyAnalyzer(bool deserializing) : base(deserializing) {
    }

    protected override void EvaluateIntermediateChildren() {
      var results = ResultsParameter.ActualValue;
      var graph = (IGenealogyGraph<ISymbolicExpressionTree>)results["PopulationGraph"].Value;
      var population = PopulationParameter.ActualValue;
      var generation = GenerationsParameter.ActualValue.Value;
      var problemData = ProblemDataParameter.ActualValue;

      var vertices = population.Select(graph.GetByContent).Where(x => x.InDegree == 1).Select(x => x.Parents.First());
      var intermediateVertices = vertices.Where(x => x.Rank.IsAlmost(generation - 0.5));

      var classificationProblemData = problemData as IClassificationProblemData;
      var regressionProblemData = problemData as IRegressionProblemData;
      if (classificationProblemData != null) {
        var evaluator = (ISymbolicDataAnalysisSingleObjectiveEvaluator<IClassificationProblemData>)EvaluatorParameter.ActualValue;
        foreach (var v in intermediateVertices) {
          var child = v.Data;
          v.Quality = evaluator.Evaluate(this.ExecutionContext, child, classificationProblemData, classificationProblemData.TrainingIndices);
        }
      } else if (regressionProblemData != null) {
        var evaluator = (ISymbolicDataAnalysisSingleObjectiveEvaluator<IRegressionProblemData>)EvaluatorParameter.ActualValue;
        foreach (var v in intermediateVertices) {
          var child = v.Data;
          v.Quality = evaluator.Evaluate(this.ExecutionContext, child, regressionProblemData, problemData.TrainingIndices);
        }
      }
    }
  }
}