1  #region License Information


2  /* HeuristicLab


3  * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)


4  *


5  * This file is part of HeuristicLab.


6  *


7  * HeuristicLab is free software: you can redistribute it and/or modify


8  * it under the terms of the GNU General Public License as published by


9  * the Free Software Foundation, either version 3 of the License, or


10  * (at your option) any later version.


11  *


12  * HeuristicLab is distributed in the hope that it will be useful,


13  * but WITHOUT ANY WARRANTY; without even the implied warranty of


14  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the


15  * GNU General Public License for more details.


16  *


17  * You should have received a copy of the GNU General Public License


18  * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.


19  */


20  #endregion


21 


22  using System;


23  using System.Linq;


24  using HeuristicLab.Common;


25  using HeuristicLab.Core;


26  using HEAL.Attic;


27 


28  namespace HeuristicLab.Algorithms.CMAEvolutionStrategy {


29  [Item("CMA Logweighted Recombinator", "Calculates weighted mean based on a logarithmic decreasing weights.")]


30  [StorableType("83A47E81FF874A28AEB4DE453B55B680")]


31  public class CMALogweightedRecombinator : CMARecombinator {


32 


33  [StorableConstructor]


34  protected CMALogweightedRecombinator(StorableConstructorFlag _) : base(_) { }


35  protected CMALogweightedRecombinator(CMALogweightedRecombinator original, Cloner cloner) : base(original, cloner) { }


36  public CMALogweightedRecombinator() : base() { }


37 


38  public override IDeepCloneable Clone(Cloner cloner) {


39  return new CMALogweightedRecombinator(this, cloner);


40  }


41 


42  protected override double[] GetWeights(int mu) {


43  var weights = new double[mu];


44  for (int i = 0; i < mu; i++) weights[i] = Math.Log((mu + 1.0) / (i + 1.0));


45  var sum = weights.Sum();


46  for (int i = 0; i < mu; i++) weights[i] /= sum;


47  return weights;


48  }


49  }


50  } 
