chi_squared_distribution< _Ty > Class Template Reference

Classes
struct	param_type

Public Types
typedef chi_squared_distribution< _Ty >	_Myt
typedef _Ty	result_type

Public Member Functions
	_RNG_REQUIRE_REALTYPE (chi_squared_distribution, _Ty)
	chi_squared_distribution (_Ty _N0=_Ty(1))
	chi_squared_distribution (const param_type &_Par0)
_Ty	n () const
param_type	param () const
void	param (const param_type &_Par0)
result_type()	min () const
result_type()	max () const
void	reset ()
template<class _Engine >
result_type	operator() (_Engine &_Eng) const
template<class _Engine >
result_type	operator() (_Engine &_Eng, const param_type &_Par0) const
template<class _Elem , class _Traits >
basic_istream< _Elem, _Traits > &	_Read (basic_istream< _Elem, _Traits > &_Istr)
template<class _Elem , class _Traits >
basic_ostream< _Elem, _Traits > &	_Write (basic_ostream< _Elem, _Traits > &_Ostr) const

Private Member Functions
template<class _Engine >
result_type	_Eval (_Engine &_Eng, const param_type &_Par0) const

Private Attributes
param_type	_Par

Member Typedef Documentation

template<class _Ty = double>

typedef chi_squared_distribution<_Ty> chi_squared_distribution< _Ty >::_Myt

template<class _Ty = double>

typedef _Ty chi_squared_distribution< _Ty >::result_type

Constructor & Destructor Documentation

template<class _Ty = double>

chi_squared_distribution< _Ty >::chi_squared_distribution ( _Ty  _N0 = _Ty(1) )

inlineexplicit

        : _Par(_N0)
        {   // construct
        }

template<class _Ty = double>

chi_squared_distribution< _Ty >::chi_squared_distribution ( const param_type &  _Par0 )

inlineexplicit

        : _Par(_Par0)
        {   // construct from parameter package
        }

Member Function Documentation

template<class _Ty = double>

template<class _Engine >

result_type chi_squared_distribution< _Ty >::_Eval ( _Engine &  _Eng, const param_type &  _Par0  ) const

inlineprivate

        {   // return pseudo-random value
        gamma_distribution<_Ty> _Dist((_Ty)_Par0._Nx * _Ty(0.5), _Ty(2));
        return (_Dist(_Eng));
        }

template<class _Ty = double>

template<class _Elem , class _Traits >

basic_istream<_Elem, _Traits>& chi_squared_distribution< _Ty >::_Read ( basic_istream< _Elem, _Traits > &  _Istr )

inline

        {   // read state from _Istr
        _Ty _N0;
        _Istr >> _N0;
        _Par._Init(_N0);
        return (_Istr);
        }

template<class _Ty = double>

chi_squared_distribution< _Ty >::_RNG_REQUIRE_REALTYPE	(	chi_squared_distribution< _Ty >	,
		_Ty
	)

template<class _Ty = double>

template<class _Elem , class _Traits >

basic_ostream<_Elem, _Traits>& chi_squared_distribution< _Ty >::_Write ( basic_ostream< _Elem, _Traits > &  _Ostr ) const

inline

        {   // write state to _Ostr
        return (_Ostr << ' ' << _Par._Nx);
        }

template<class _Ty = double>

result_type() chi_squared_distribution< _Ty >::max ( ) const

inline

        {   // get largest possible result
        return ((numeric_limits<result_type>::max)());
        }

template<class _Ty = double>

result_type() chi_squared_distribution< _Ty >::min ( ) const

inline

        {   // get smallest possible result
        return (numeric_limits<result_type>::denorm_min());
        }

template<class _Ty = double>

_Ty chi_squared_distribution< _Ty >::n ( ) const

inline

        {   // return n value
        return (_Par.n());
        }

template<class _Ty = double>

template<class _Engine >

result_type chi_squared_distribution< _Ty >::operator() ( _Engine &  _Eng ) const

inline

        {   // return next value
        return (_Eval(_Eng, _Par));
        }

template<class _Ty = double>

template<class _Engine >

result_type chi_squared_distribution< _Ty >::operator() ( _Engine &  _Eng, const param_type &  _Par0  ) const

inline

        {   // return next value, given parameter package
        return (_Eval(_Eng, _Par0));
        }

template<class _Ty = double>

param_type chi_squared_distribution< _Ty >::param ( ) const

inline

        {   // return parameter package
        return (_Par);
        }

template<class _Ty = double>

void chi_squared_distribution< _Ty >::param ( const param_type &  _Par0 )

inline

        {   // set parameter package
        _Par = _Par0;
        }

template<class _Ty = double>

void chi_squared_distribution< _Ty >::reset ( )

inline

        {   // clear internal state
        }

Member Data Documentation

template<class _Ty = double>

param_type chi_squared_distribution< _Ty >::_Par

private

---

The documentation for this class was generated from the following file:

• VS2017/inc/random