[9129] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[17181] | 3 | * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[9129] | 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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[9709] | 22 | using System;
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| 23 | using System.Linq;
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[9129] | 24 | using HeuristicLab.Common;
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| 25 | using HeuristicLab.Core;
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[17097] | 26 | using HEAL.Attic;
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[9129] | 27 |
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| 28 | namespace HeuristicLab.Algorithms.CMAEvolutionStrategy {
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[9709] | 29 | [Item("CMA Log-weighted Recombinator", "Calculates weighted mean based on a logarithmic decreasing weights.")]
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[17097] | 30 | [StorableType("83A47E81-FF87-4A28-AEB4-DE453B55B680")]
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[9129] | 31 | public class CMALogweightedRecombinator : CMARecombinator {
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| 32 |
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| 33 | [StorableConstructor]
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[17097] | 34 | protected CMALogweightedRecombinator(StorableConstructorFlag _) : base(_) { }
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[9129] | 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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[9297] | 42 | protected override double[] GetWeights(int mu) {
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| 43 | var weights = new double[mu];
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[9129] | 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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