1 | #region License Information |
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2 | /* HeuristicLab |
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3 | * Copyright (C) 2002-2013 Heuristic and Evolutionary Algorithms Laboratory (HEAL) |
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4 | * |
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5 | * This file is part of HeuristicLab. |
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6 | * |
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7 | * HeuristicLab is free software: you can redistribute it and/or modify |
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8 | * it under the terms of the GNU General Public License as published by |
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9 | * the Free Software Foundation, either version 3 of the License, or |
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10 | * (at your option) any later version. |
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11 | * |
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12 | * HeuristicLab is distributed in the hope that it will be useful, |
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13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of |
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14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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15 | * GNU General Public License for more details. |
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16 | * |
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17 | * You should have received a copy of the GNU General Public License |
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18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>. |
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19 | */ |
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20 | #endregion |
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21 | |
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22 | using System; |
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23 | using System.Linq; |
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24 | using HeuristicLab.Common; |
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25 | using HeuristicLab.Core; |
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26 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; |
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27 | |
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28 | namespace HeuristicLab.Algorithms.CMAEvolutionStrategy { |
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29 | [Item("CMA Log-weighted Recombinator", "Calculates weighted mean based on a logarithmic decreasing weights.")] |
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30 | [StorableClass] |
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31 | public class CMALogweightedRecombinator : CMARecombinator { |
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32 | |
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33 | [StorableConstructor] |
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34 | protected CMALogweightedRecombinator(bool deserializing) : base(deserializing) { } |
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35 | protected CMALogweightedRecombinator(CMALogweightedRecombinator original, Cloner cloner) : base(original, cloner) { } |
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36 | public CMALogweightedRecombinator() : base() { } |
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37 | |
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38 | public override IDeepCloneable Clone(Cloner cloner) { |
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39 | return new CMALogweightedRecombinator(this, cloner); |
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40 | } |
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41 | |
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42 | protected override double[] GetWeights(int mu) { |
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43 | var weights = new double[mu]; |
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44 | for (int i = 0; i < mu; i++) weights[i] = Math.Log((mu + 1.0) / (i + 1.0)); |
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45 | var sum = weights.Sum(); |
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46 | for (int i = 0; i < mu; i++) weights[i] /= sum; |
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47 | return weights; |
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48 | } |
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49 | } |
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50 | } |
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