STK_Kernel_Hamming.h

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/*--------------------------------------------------------------------*/
/*     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,
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    USA
 
    Contact : S..._Dot_I..._At_stkpp_Dot_org (see copyright for ...)
*/
 
/*
 * Project:  stkpp::STatisitK::Kernel
 * created on: 2 feb. 2016
 * Author:   iovleff, S..._Dot_I..._At_stkpp_Dot_org (see copyright for ...)
 **/
 
#ifndef STK_KERNEL_HAMMING_H
#define STK_KERNEL_HAMMING_H
 
#include "STK_Kernel_IKernelBase.h"
#include "STK_Stat_MultiFactor.h"
 
namespace STK
{
 
namespace Kernel
{
template<class Array>
class Hamming: public IKernelBase<Array>
{
  public:
    typedef IKernelBase<Array> Base;
    typedef typename Array::Type Type;
    using Base::p_data_;
    using Base::gram_;
    using Base::hasRun_;
 
    Hamming( Array const* p_data, Real const& lambda= 1.)
          : Base(p_data), lambda_(lambda), diagElt_(1.), factors_(p_data)
    {
      if (!p_data)
      { STKRUNTIME_ERROR_NO_ARG(Hamming::Hamming(p_data,lambda),p_data is 0);}
      factors_.run();
      computeDiagonalElement();
    }
    Hamming( Array const& data, Real const& lambda= 1.)
          : Base(data), lambda_(lambda), diagElt_(1.), factors_(data)
    {
      factors_.run();
      computeDiagonalElement();
    }
     template<class Derived>
     Hamming( Array const* p_data, ExprBase<Derived> const& param)
           : Base(p_data), lambda_(param.empty() ? 1. : param.front())
            , diagElt_(1.), factors_(p_data)
     {
         if (!p_data)
         { STKRUNTIME_ERROR_NO_ARG(Hamming::Hamming(p_data,lambda),p_data is 0);}
         factors_.run();
         computeDiagonalElement();
     }
     template<class Derived>
     Hamming( Array const& data, ExprBase<Derived> const& param)
           : Base(data), lambda_(param.empty() ? 1. : param.front())
            , diagElt_(1.), factors_(data)
     {
         factors_.run();
         computeDiagonalElement();
     }
 
    virtual ~Hamming() {}
 
    Real const& lambda() const {return lambda_;}
    Stat::MultiFactor<Array> const& factors() const {return factors_;}
    void setLambda(Real const& lambda)
    {
      lambda_ = lambda;
      computeDiagonalElement();
    }
    template<class Derived>
    void setParam(  ExprBase<Derived> const& param)
    {
      lambda_ = (param.empty() ? 1. : param.front());
      computeDiagonalElement();
    }
 
    virtual Real diag(int i) const;
    virtual Real comp(int i, int j) const;
 
  private:
    Real lambda_;
    Real diagElt_;
    Stat::MultiFactor<Array> factors_;
    void computeDiagonalElement();
};
 
/* Compute the diagonal element of the kernel*/
template<class Array>
void Hamming<Array>::computeDiagonalElement()
{
   diagElt_ = 1.;
   for(int j=factors_.nbLevels().begin(); j < factors_.nbLevels().end(); ++j)
   { diagElt_ *= lambda_*lambda_*(factors_.nbLevels()[j]-1) + 1;}
}
 
template<class Array>
inline Real Hamming<Array>::diag(int i) const { return diagElt_;}
 
template<class Array>
Real Hamming<Array>::comp(int i, int j) const
{
  typedef typename hidden::Traits<Array>::Row RowVector;
  if (hasRun_) return gram_(i,j);
  // create references on row i and j
  RowVector ind1(p_data_->row(i), true), ind2(p_data_->row(j), true);
  Real value = 1.;
  for(int j=factors_.nbLevels().begin(); j < factors_.nbLevels().end(); ++j)
  {
    value *= (ind1[j]==ind2[j]) ? lambda_*lambda_*(factors_.nbLevels()[j]-1) + 1.
                                : lambda_*(lambda_*(factors_.nbLevels()[j]-2) + 2.);
  }
  return value;
}
 
} // namespace Kernel
 
} // namespace STK
 
#endif /* STK_KERNEL_HAMMING_H */