#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);
}
}