#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

namespace HeuristicLab.Problems.ProgramSynthesis.Push.Selector {
  using System;
  using System.Collections.Generic;
  using System.Linq;

  using HeuristicLab.Common;
  using HeuristicLab.Core;
  using HeuristicLab.Data;
  using HeuristicLab.Parameters;
  using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
  using HeuristicLab.Problems.ProgramSynthesis.Push.Problem;
  using HeuristicLab.Random;
  using HeuristicLab.Selection;

  /// <summary>
  /// A lexicase selection operator which considers all successful evaluated training cases for selection.
  /// </summary>
  [Item("LexicaseSelector", "A lexicase selection operator which considers all successful evaluated training cases for selection.")]
  [StorableClass]
  public sealed class LexicaseSelector : StochasticSingleObjectiveSelector, ICaseSingleObjectiveSelector {
    public ILookupParameter<ItemArray<DoubleArray>> CaseQualitiesParameter
    {
      get { return (ILookupParameter<ItemArray<DoubleArray>>)Parameters[IntegerVectorPushProblem.CaseQualitiesScopeParameterName]; }
    }

    [StorableConstructor]
    private LexicaseSelector(bool deserializing) : base(deserializing) { }
    private LexicaseSelector(LexicaseSelector original, Cloner cloner) : base(original, cloner) { }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new LexicaseSelector(this, cloner);
    }

    public LexicaseSelector() {
      Parameters.Add(new ScopeTreeLookupParameter<DoubleArray>(
        IntegerVectorPushProblem.CaseQualitiesScopeParameterName,
        "The quality of every single training case for each individual."));
    }


    protected override IScope[] Select(List<IScope> scopes) {
      var count = NumberOfSelectedSubScopesParameter.ActualValue.Value;
      var copy = CopySelectedParameter.Value.Value;
      var random = RandomParameter.ActualValue;
      var maximization = MaximizationParameter.ActualValue.Value;
      var caseQualities = CaseQualitiesParameter.ActualValue.ToList();

      var selected = Apply(
        scopes,
        count,
        copy,
        maximization,
        random,
        caseQualities);

      return selected;
    }

    public static IScope[] Apply(
      List<IScope> scopes,
      int count,
      bool copy,
      bool maximization,
      IRandom random,
      List<DoubleArray> caseQualities) {

      for (var i = 0; i < caseQualities.Count; i++) {
        if (caseQualities[i].Length == 0) {
          scopes.RemoveAt(i);
          caseQualities.RemoveAt(i);
        }
      }

      var qualitiesLength = caseQualities[0].Length;

      if (caseQualities.Any(x => x.Length != qualitiesLength)) {
        throw new ArgumentException("Not all case qualities have the same length");
      }

      var selected = new IScope[count];

      var candidates = new List<int>(caseQualities.Count);
      for (var i = 0; i < caseQualities.Count; i++) candidates.Add(i);

      var orderSource = new List<int>(qualitiesLength);
      for (var i = 0; i < qualitiesLength; i++) orderSource.Add(i);

      for (var i = 0; i < count; i++) {
        var index = LexicaseSelect(
          caseQualities,
          candidates,
          orderSource.Shuffle(random),
          random,
          maximization);

        if (copy) {
          selected[i] = (IScope)scopes[index].Clone();
        } else {
          selected[i] = scopes[index];
          scopes.RemoveAt(index);
          caseQualities.RemoveAt(index);
        }
      }

      return selected;
    }

    private static int LexicaseSelect(
      List<DoubleArray> caseQualities,
      List<int> candidates,
      IEnumerable<int> order,
      IRandom random,
      bool maximization) {

      foreach (var curCase in order) {
        var nextCandidates = new List<int>();

        var best = maximization
          ? double.NegativeInfinity
          : double.PositiveInfinity;

        for (var i = 0; i < candidates.Count; i++) {
          var candidate = candidates[i];
          var caseQuality = caseQualities[candidate][curCase];

          if (caseQuality.IsAlmost(best)) {
            // if the individuals is as good as the best one, add it
            nextCandidates.Add(candidate);
          } else if (
             (maximization && (caseQuality > best)) ||
             (!maximization && (caseQuality < best))) {
            // if the individual is better than the best one, remove all previous candidates and add the new one
            nextCandidates.Clear();
            nextCandidates.Add(candidate);
            // also set the next best quality value
            best = caseQuality;
          }
          // else {do nothing}
        }

        if (nextCandidates.Count == 1) {
          return nextCandidates[0];
        }

        if (nextCandidates.Count < 1) {
          return candidates.SampleRandom(random);
        }

        candidates = nextCandidates;
      }

      return candidates.Count == 1
        ? candidates[0]
        : candidates.SampleRandom(random);
    }
  }
}