#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2018 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.Collections.Generic;
using System.Linq;
using HEAL.Attic;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Optimization;

namespace HeuristicLab.Problems.Modifiers {
  [StorableType("7C9DECC0-1CA1-4198-835F-CB1CF35D88E8")]
  [Item("SingleObjectiveEndPointProblemModifier", "A dummy problem modifier leading to a single objective basic problem")]
  public class SingleObjectiveEndPointProblemModifier<T> : ProblemModifier where T : class, IEncoding {
    private SingleObjectiveBasicProblem<T> problem;
    [Storable]
    public SingleObjectiveBasicProblem<T> Problem {
      get => problem;
      set {
        problem = value;
        UpdateState();
        //TODO attach to EncodingChanged and MaximizationChanged Events ... (not implemented in BasicProblem yet)
      }
    }

    public override IEncoding Encoding => Problem?.Encoding;
    public override BoolArray Maximization {
      get {
        if (Problem == null) return new BoolArray(new[] { false });
        var dict = new Dictionary<string, IItem>();
        Problem.CollectParameterValues(dict);
        var b = dict.ContainsKey("Maximization") ? ((BoolValue)dict["Maximization"]).Value : problem.Maximization;
        return new BoolArray(new[] { b });
      }
    }

    [StorableConstructor]
    protected SingleObjectiveEndPointProblemModifier(StorableConstructorFlag _) : base(_) { }
    protected SingleObjectiveEndPointProblemModifier(SingleObjectiveEndPointProblemModifier<T> original, Cloner cloner) : base(original, cloner) {
      Problem = cloner.Clone(original?.Problem);
    }
    public SingleObjectiveEndPointProblemModifier() { }

    public override IDeepCloneable Clone(Cloner cloner) {
      return new SingleObjectiveEndPointProblemModifier<T>(this, cloner);
    }

    public override double[] ModifiedEvaluate(Individual individual, IRandom random) {
      return new[] { Problem.Evaluate(individual, random) };
    }

    public override void ModifiedAnalyze(Individual[] individuals, double[][] qualities, ResultCollection results, IRandom random) {
      Problem.Analyze(individuals, qualities.Select(x => x.Single()).ToArray(), results, random);
    }

    public void UpdateState() {
      InvokeEncodingChanged();
      InvokeMaximizationChanged();
    }
  }
}