STK_Kernel_Gaussian.h

Go to the documentation of this file.

/*--------------------------------------------------------------------*/
/*     Copyright (C) 2004-2016  Serge Iovleff, Université Lille 1, Inria
 
    This program 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 of the
    License, or (at your option) any later version.
 
    This program 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 program; if not, write to the
    Free Software Foundation, Inc.,
    59 Temple Place,
    Suite 330,
    Boston, MA 02111-1307
    USA
 
    Contact : S..._Dot_I..._At_stkpp_Dot_org (see copyright for ...)
*/
 
/*
 * Project:  stkpp::
 * created on: 5 avr. 2015
 * Author:   iovleff, S..._Dot_I..._At_stkpp_Dot_org (see copyright for ...)
 **/
 
#ifndef STK_KERNEL_GAUSSIAN_H
#define STK_KERNEL_GAUSSIAN_H
 
#include "STK_Kernel_IKernelBase.h"
 
namespace STK
{
 
namespace Kernel
{
template<class Array>
class Gaussian: public IKernelBase<Array>
{
  public:
    typedef IKernelBase<Array> Base;
    typedef typename Array::Type Type;
    using Base::p_data_;
    using Base::gram_;
    using Base::hasRun_;
 
    Gaussian( Real const& width= 1.)
           : Base(0), width_(width)
    {}
    Gaussian( Array const* p_data, Real const& width= 1.)
           : Base(p_data), width_(width)
    {}
    Gaussian( Array const& data, Real const& width= 1.)
           : Base(data), width_(width)
    {}
 
    template<class Derived>
    Gaussian( Array const* p_data, ExprBase<Derived> const& param)
           : Base(p_data), width_(param.empty() ? 1. : param.front())
    {}
    template<class Derived>
    Gaussian( Array const& data, ExprBase<Derived> const& param)
           : Base(data), width_(param.empty() ? 1. : param.front())
    {}
 
    virtual ~Gaussian() {}
    Real const& width() const {return width_;}
    void setWidth(Real const& width) {width_ = width;}
    template<class Derived>
    void setParam(  ExprBase<Derived> const& param)
    { width_ = (param.empty() ? 1. : param.front());}
 
    virtual inline Real diag(int i) const {return 1.;};
    virtual Real comp(int i, int j) const;
 
    virtual Real value(Type const& v) const;
 
  private:
    Real width_;
};
 
template<class Array>
Real Gaussian<Array>::comp(int i, int j) const
{ return hasRun_ ? gram_(i,j)
                 : std::exp(-(p_data_->row(i) - p_data_->row(j)).norm2()/(2.*width_));
}
 
template<class Array>
Real Gaussian<Array>::value(Type const& v) const
{ return std::exp(-v*v/(2.*width_));}
 
} // namespace Kernel
 
} // namespace STK
 
#endif /* STK_KERNEL_GAUSSIAN_H */