file HepLike_1_2/wrapper_HL_nDimLikelihood_def.h
[No description available]
Functions
Name | |
---|---|
namespace | CAT_3(BACKENDNAME , _ , SAFE_VERSION ) |
Functions Documentation
function CAT_3
namespace CAT_3(
BACKENDNAME ,
_ ,
SAFE_VERSION
)
Source code
#ifndef __wrapper_HL_nDimLikelihood_def_HepLike_1_2_h__
#define __wrapper_HL_nDimLikelihood_def_HepLike_1_2_h__
#include <string>
#include <vector>
#include <boost/numeric/ublas/matrix.hpp>
#include "identification.hpp"
namespace CAT_3(BACKENDNAME,_,SAFE_VERSION)
{
// Member functions:
inline void HL_nDimLikelihood::Read()
{
get_BEptr()->Read();
}
inline double HL_nDimLikelihood::GetChi2(::std::vector<double> theory)
{
return get_BEptr()->GetChi2(theory);
}
inline double HL_nDimLikelihood::GetChi2(::std::vector<double> theory, ::boost::numeric::ublas::matrix<double> theory_cov)
{
return get_BEptr()->GetChi2(theory, theory_cov);
}
inline double HL_nDimLikelihood::GetLikelihood(::std::vector<double> theory)
{
return get_BEptr()->GetLikelihood(theory);
}
inline double HL_nDimLikelihood::GetLikelihood(::std::vector<double> theory, ::boost::numeric::ublas::matrix<double> theory_cov)
{
return get_BEptr()->GetLikelihood(theory, theory_cov);
}
inline double HL_nDimLikelihood::GetLogLikelihood(::std::vector<double> theory)
{
return get_BEptr()->GetLogLikelihood(theory);
}
inline double HL_nDimLikelihood::GetLogLikelihood(::std::vector<double> theory, ::boost::numeric::ublas::matrix<double> theory_cov)
{
return get_BEptr()->GetLogLikelihood(theory, theory_cov);
}
inline void HL_nDimLikelihood::Profile()
{
get_BEptr()->Profile();
}
inline double HL_nDimLikelihood::GetChi2_profile(double theory, ::std::basic_string<char> arg_1)
{
return get_BEptr()->GetChi2_profile(theory, arg_1);
}
inline double HL_nDimLikelihood::GetLikelihood_profile(double theory, ::std::basic_string<char> axis)
{
return get_BEptr()->GetLikelihood_profile(theory, axis);
}
inline double HL_nDimLikelihood::GetLogLikelihood_profile(double theory, ::std::basic_string<char> X)
{
return get_BEptr()->GetLogLikelihood_profile(theory, X);
}
inline ::std::vector<std::basic_string<char>> HL_nDimLikelihood::GetObservables()
{
return get_BEptr()->GetObservables();
}
// Wrappers for original constructors:
inline HL_nDimLikelihood::HL_nDimLikelihood() :
HL_Data(__factory0()),
loglikelihood_penalty( get_BEptr()->loglikelihood_penalty_ref__BOSS())
{
get_BEptr()->set_wptr(this);
get_BEptr()->set_delete_wrapper(false);
}
inline HL_nDimLikelihood::HL_nDimLikelihood(::std::basic_string<char> s) :
HL_Data(__factory1(s)),
loglikelihood_penalty( get_BEptr()->loglikelihood_penalty_ref__BOSS())
{
get_BEptr()->set_wptr(this);
get_BEptr()->set_delete_wrapper(false);
}
// Special pointer-based constructor:
inline HL_nDimLikelihood::HL_nDimLikelihood(Abstract_HL_nDimLikelihood* in) :
HL_Data(in),
loglikelihood_penalty( get_BEptr()->loglikelihood_penalty_ref__BOSS())
{
get_BEptr()->set_wptr(this);
get_BEptr()->set_delete_wrapper(false);
}
// Copy constructor:
inline HL_nDimLikelihood::HL_nDimLikelihood(const HL_nDimLikelihood& in) :
HL_Data(in.get_BEptr()->pointer_copy__BOSS()),
loglikelihood_penalty( get_BEptr()->loglikelihood_penalty_ref__BOSS())
{
get_BEptr()->set_wptr(this);
get_BEptr()->set_delete_wrapper(false);
}
// Assignment operator:
inline HL_nDimLikelihood& HL_nDimLikelihood::operator=(const HL_nDimLikelihood& in)
{
if (this != &in)
{
get_BEptr()->pointer_assign__BOSS(in.get_BEptr());
}
return *this;
}
// Destructor:
inline HL_nDimLikelihood::~HL_nDimLikelihood()
{
if (get_BEptr() != 0)
{
get_BEptr()->set_delete_wrapper(false);
if (can_delete_BEptr())
{
delete BEptr;
BEptr = 0;
}
}
set_delete_BEptr(false);
}
// Returns correctly casted pointer to Abstract class:
inline Abstract_HL_nDimLikelihood* HL_nDimLikelihood::get_BEptr() const
{
return dynamic_cast<Abstract_HL_nDimLikelihood*>(BEptr);
}
}
#include "gambit/Backends/backend_undefs.hpp"
#endif /* __wrapper_HL_nDimLikelihood_def_HepLike_1_2_h__ */
Updated on 2022-08-03 at 12:58:05 +0000