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📄 initesvecop.hpp

📁 非常好的进化算法EC 实现平台 可以实现多种算法 GA GP
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/* *  Open BEAGLE *  Copyright (C) 2001-2005 by Christian Gagne and Marc Parizeau * *  This library is free software; you can redistribute it and/or *  modify it under the terms of the GNU Lesser General Public *  License as published by the Free Software Foundation; either *  version 2.1 of the License, or (at your option) any later version. * *  This library 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 *  Lesser General Public License for more details. * *  You should have received a copy of the GNU Lesser General Public *  License along with this library; if not, write to the Free Software *  Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA * *  Contact: *  Laboratoire de Vision et Systemes Numeriques *  Departement de genie electrique et de genie informatique *  Universite Laval, Quebec, Canada, G1K 7P4 *  http://vision.gel.ulaval.ca * *//*! *  \file   beagle/GA/InitESVecOp.hpp *  \brief  Definition of the class GA::InitESVecOp. *  \author Christian Gagne *  \author Marc Parizeau *  $Revision: 1.10 $ *  $Date: 2005/09/30 15:04:53 $ */#ifndef Beagle_GA_InitESVecOp_hpp#define Beagle_GA_InitESVecOp_hpp#include <string>#include "beagle/config.hpp"#include "beagle/macros.hpp"#include "beagle/Object.hpp"#include "beagle/AllocatorT.hpp"#include "beagle/PointerT.hpp"#include "beagle/ContainerT.hpp"#include "beagle/InitializationOp.hpp"#include "beagle/Float.hpp"namespace Beagle {namespace GA {/*! *  \class InitESVecOp beagle/GA/InitESVecOp.hpp "beagle/GA/InitESVecOp.hpp" *  \brief ES genotype initialization operator class. *  \ingroup GAF *  \ingroup GAES * *  Initialization is based on one parameter, the initial strategy value (es.init.strategy). Each *  strategy parameters (\f$sigma_{init}\f$) are initialized to this value, while the value of the ES  *  vector is randomly initialized to a value following a Gaussian distribution (\f$N(\mu,\sigma)\f$) *  of zero mean (\f$\mu=0.0\f$) and a standard deviation of the initial stategy parameter value *  (\f$\sigma=\sigma_{init}\f$). * */class InitESVecOp : public InitializationOp {public:  //! GA::InitESVecOp allocator type.  typedef AllocatorT<InitESVecOp,InitializationOp::Alloc>          Alloc;  //! GA::InitESVecOp handle type.  typedef PointerT<InitESVecOp,InitializationOp::Handle>          Handle;  //! GA::InitESVecOp bag type.  typedef ContainerT<InitESVecOp,InitializationOp::Bag>          Bag;  explicit InitESVecOp(unsigned int inESVectorSize=0,                       string inReproProbaName="ec.repro.prob",                       string inName="GA-InitESVecOp");  virtual ~InitESVecOp() { }  virtual void initialize(System& ioSystem);  virtual void initIndividual(Individual& outIndividual, Context& ioContext);  /*!   *  \return ES vector size to use for initialization.   */  unsigned int getESVectorSize() const  {    Beagle_StackTraceBeginM();    return mESVectorSize->getWrappedValue();    Beagle_StackTraceEndM("unsigned int GA::InitESVecOp::getESVectorSize() const");  }  /*!   *  \brief Set ES vector size to use for initialization.   *  \param inESVectorSize New ES vector size.   */  void setESVectorSize(unsigned int inESVectorSize)  {    Beagle_StackTraceBeginM();    mESVectorSize->getWrappedValue() = inESVectorSize;    Beagle_StackTraceEndM("void GA::InitESVecOp::setESVectorSize(unsigned int inESVectorSize)");  }protected:  DoubleArray::Handle  mMaxValue;           //!< Maximum of ES vector values.  DoubleArray::Handle  mMinValue;           //!< Minimum of ES vector values.  UInt::Handle         mESVectorSize;       //!< Individual float vectors size.  Double::Handle       mInitStrategyValue;  //!< Mutation strategy value at initialization.};}}#endif // Beagle_GA_InitESVecOp_hpp

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