#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); } } }