#region License Information /* HeuristicLab * Copyright (C) 2002-2019 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 . */ #endregion using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Encodings.RealVectorEncoding; using HeuristicLab.Operators; using HeuristicLab.Parameters; using HEAL.Attic; using System; namespace HeuristicLab.Algorithms.CMAEvolutionStrategy { [Item("CMARecombinator", "Base class that calculates the weighted mean of a number of offspring.")] [StorableType("C0798B4D-1685-4720-828A-17E40879000B")] public abstract class CMARecombinator : SingleSuccessorOperator, ICMARecombinator { public Type CMAType { get { return typeof(CMAParameters); } } #region Parameter Properties public IScopeTreeLookupParameter OffspringParameter { get { return (IScopeTreeLookupParameter)Parameters["Offspring"]; } } public ILookupParameter MeanParameter { get { return (ILookupParameter)Parameters["Mean"]; } } public ILookupParameter OldMeanParameter { get { return (ILookupParameter)Parameters["OldMean"]; } } public ILookupParameter StrategyParametersParameter { get { return (ILookupParameter)Parameters["StrategyParameters"]; } } #endregion [StorableConstructor] protected CMARecombinator(StorableConstructorFlag _) : base(_) { } protected CMARecombinator(CMARecombinator original, Cloner cloner) : base(original, cloner) { } protected CMARecombinator() : base() { Parameters.Add(new ScopeTreeLookupParameter("Offspring", "The offspring that should be recombined.")); Parameters.Add(new LookupParameter("Mean", "The new mean solution.")); Parameters.Add(new LookupParameter("OldMean", "The old mean solution.")); Parameters.Add(new LookupParameter("StrategyParameters", "The CMA-ES strategy parameters used for mutation.")); OffspringParameter.ActualName = "RealVector"; MeanParameter.ActualName = "XMean"; OldMeanParameter.ActualName = "XOld"; } public override IOperation Apply() { var sp = StrategyParametersParameter.ActualValue; if (sp.Weights == null) sp.Weights = GetWeights(sp.Mu); var offspring = OffspringParameter.ActualValue; var mean = new RealVector(offspring[0].Length); for (int i = 0; i < mean.Length; i++) { for (int j = 0; j < sp.Mu; j++) mean[i] += sp.Weights[j] * offspring[j][i]; } var oldMean = MeanParameter.ActualValue; MeanParameter.ActualValue = mean; OldMeanParameter.ActualValue = oldMean; return base.Apply(); } protected abstract double[] GetWeights(int mu); } }