STD::CAUCHY_DISTRIBUTION(3)
β¨ NAME β¨</p>
std::cauchy_distribution< _RealType > β a cauchy_distribution random number distribution π
π SYNOPSIS π
#include <random>
Classes π
struct param_type
Public Types πΈ
typedef _RealType result_type
Public Member Functions π¦
cauchy_distribution (_RealType __a, _RealType __b=1.0)cauchy_distribution (const param_type &__p)template<typename _ForwardIterator, typename _UniformRandomNumberGenerator> void __generate (_ForwardIterator __f, _ForwardIterator __t, _UniformRandomNumberGenerator &__urng)template<typename _ForwardIterator, typename _UniformRandomNumberGenerator> void __generate (_ForwardIterator __f, _ForwardIterator __t, _UniformRandomNumberGenerator &__urng, const param_type &__p)template<typename _UniformRandomNumberGenerator> void __generate (result_type *__f, result_type *__t, _UniformRandomNumberGenerator &__urng, const param_type &__p)_RealType a () const_RealType b () constresult_type max () constβ Returns the least upper bound value of the distribution.result_type min () constβ Returns the greatest lower bound value of the distribution.template<typename _UniformRandomNumberGenerator> result_type operator() (_UniformRandomNumberGenerator &__urng)β Generating functions.template<typename _UniformRandomNumberGenerator> result_type operator() (_UniformRandomNumberGenerator &__urng, const param_type &__p)param_type param () constβ Returns the parameter set of the distribution.void param (const param_type &__param)β Sets the parameter set of the distribution.void reset ()β Resets the distribution state.
Friends π«Ά
bool operator== (const cauchy_distribution &__d1, const cauchy_distribution &__d2)β Return true if two Cauchy distributions have the same parameters.
π DETAILED DESCRIPTION π
template<typename _RealType = double>
class std::cauchy_distribution< _RealType >
"A cauchy_distribution random number distribution. π²
The formula for the normal probability mass function is $p(x|a,b) = (i b (1 + (ac{x-a}{b})^2))^{-1}$ β¨
Since C++11
π§ MEMBER TYPEDEF DOCUMENTATION π§
template<typename _RealType = double> typedef _RealType
std::cauchy_distribution< _RealType >::result_type
The type of the range of the distribution. slay π
β MEMBER FUNCTION DOCUMENTATION β
max() π«
template<typename _RealType = double> result_type std::cauchy_distribution<
_RealType >::max () const [inline]
Returns the least upper bound value of the distribution. π
min() π«
template<typename _RealType = double> result_type std::cauchy_distribution<
_RealType >::min () const [inline]
Returns the greatest lower bound value of the distribution. π«Ά
operator() π«
template<typename _RealType = double> template<typename
_UniformRandomNumberGenerator> result_type std::cauchy_distribution<
_RealType >::operator() (_UniformRandomNumberGenerator & __urng)
[inline]
Generating functions. π°
Referenced by operator()().
param() const π«
template<typename _RealType = double> param_type std::cauchy_distribution<
_RealType >::param () const [inline]
Returns the parameter set of the distribution. π¦
Referenced by std::operator>>().
param(const param_type & __param) π«
template<typename _RealType = double> void std::cauchy_distribution<
_RealType >::param (const param_type & __param) [inline]
Sets the parameter set of the distribution. βοΈ
Parameters
__paramβ The new parameter set of the distribution.
reset() π«
template<typename _RealType = double> void std::cauchy_distribution<
_RealType >::reset () [inline]
Resets the distribution state. π
π FRIENDS AND RELATED SYMBOL DOCUMENTATION π
operator== π
template<typename _RealType = double> bool operator== (const
cauchy_distribution< _RealType > & __d1, const cauchy_distribution<
_RealType > & __d2) [friend]
Return true if two Cauchy distributions have the same parameters. π°
π AUTHOR π
Generated automatically by Doxygen for libstdc++ from the source code.
okay bestie that's literally the whole page, no cap π this was libstdc++'s std::cauch..._RealType >(3) β Library Functions Manual energy, and it's giving generated automatically by Doxygen for libstdc++ from the source code π periodt, go forth and generate some Cauchy randomness β¨π¦
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