source: branches/Enhanced OSALPS/HeuristicLab.Algorithms.ALPS/3.3/ContinuousMatingPoolCreator.cs @ 15432

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2016 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;
using System.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Algorithms.ALPS {
  [Item("ContinuousMatingPoolCreator", "An operator which creates mating pools based on a set of sub-populations. For each sub-population, the individuals from the previous sub-population are copied into the current sub-population.")]
  [StorableClass]
  public sealed class ContinuousMatingPoolCreator : SingleSuccessorOperator, IMatingPoolCreator {
    public IValueLookupParameter<DoubleArray> RangesParameter {
      get { return (IValueLookupParameter<DoubleArray>)Parameters["Ranges"]; }
    }

    public IScopeTreeLookupParameter<DoubleValue> QualityParameter {
      get { return (IScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
    }
    public IValueLookupParameter<BoolValue> MaximizationParameter {
      get { return (IValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
    }


    #region Constructor, Cloning & Persistence
    public ContinuousMatingPoolCreator()
      : base() {
      Parameters.Add(new ValueLookupParameter<DoubleArray>("Ranges", "The range of sub-populations used for creating a mating pool. (1 = current + previous sub-population)"));
      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The quality value contained in each sub-scope which is used for selection."));
      Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the current problem is a maximization problem, otherwise false."));
    }

    private ContinuousMatingPoolCreator(ContinuousMatingPoolCreator original, Cloner cloner)
      : base(original, cloner) { }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new ContinuousMatingPoolCreator(this, cloner);
    }

    [StorableConstructor]
    private ContinuousMatingPoolCreator(bool deserializing)
      : base(deserializing) { }
    #endregion

    /// <summary>
    /// Copies the subscopes of the n previous scopes into the current scope. (default n = 1)
    /// <pre>
    ///          __ scope __              __ scope __
    ///         /     |     \            /     |     \
    ///       Pop1   Pop2   Pop3  =>   Pop1   Pop2   Pop3
    ///       /|\    /|\    /|\         /|\   /|\    /|\
    ///       ABC    DEF    GHI         ABC   DEF    GHI
    ///                                       ABC    DEF
    /// </pre>
    /// </summary>
    /// <returns>The next operation.</returns>
    public override IOperation Apply() {
      var subScopes = ExecutionContext.Scope.SubScopes;
      var ranges = RangesParameter.ActualValue;
      var qualityName = QualityParameter.TranslatedName;
      bool maximization = MaximizationParameter.ActualValue.Value;

      for (int targetIndex = subScopes.Count - 1; targetIndex > 0; targetIndex--) {
        var targetScope = subScopes[targetIndex];
        var range = ranges.Length == 1 ? ranges[0] : ranges[targetIndex];
        for (int n = 1; (n <= (range + 1)) && (targetIndex - n >= 0); n++) {
          var prevScope = subScopes[targetIndex - n];
          IEnumerable<IScope> individuals = prevScope.SubScopes
            .OrderBy(i => ((DoubleValue)i.Variables[qualityName].Value).Value);
          if (maximization) individuals = individuals.Reverse();
          individuals = individuals.Take((int)(Math.Min(range + 1 - n, 1.0) * prevScope.SubScopes.Count));
          foreach (var individual in individuals) {
            targetScope.SubScopes.Add((IScope)individual.Clone());
          }
        }
      }

      return base.Apply();
    }
  }
}