#region License Information
/* HeuristicLab
* Copyright (C) 2002-2008 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 System;
using System.Collections.Generic;
using System.Text;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Random;
namespace HeuristicLab.RealVector {
public class SelfAdaptiveNormalAllPositionsManipulator : RealVectorManipulatorBase {
public override string Description {
get { return @"Manipulates each dimension in the real vector with the mutation strength given in the strategy parameter vector"; }
}
public SelfAdaptiveNormalAllPositionsManipulator()
: base() {
AddVariableInfo(new VariableInfo("StrategyVector", "The strategy vector determining the strength of the mutation", typeof(DoubleArrayData), VariableKind.In));
}
public static double[] Apply(double[] strategyParameters, IRandom random, double[] vector) {
NormalDistributedRandom N = new NormalDistributedRandom(random, 0.0, 1.0);
if (strategyParameters.Length != vector.Length)
throw new InvalidOperationException("ERROR: Strategy Vector must be as long as parameter vector");
for (int i = 0; i < vector.Length; i++) {
vector[i] = vector[i] + (N.NextDouble() * strategyParameters[i]);
}
return vector;
}
protected override double[] Manipulate(IScope scope, IRandom random, double[] vector) {
double[] strategyVector = scope.GetVariableValue("StrategyVector", true).Data;
return Apply(strategyVector, random, vector);
}
}
}