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//===----------------------------------------------------------------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
#ifndef _LIBCPP___RANDOM_BINOMIAL_DISTRIBUTION_H
#define _LIBCPP___RANDOM_BINOMIAL_DISTRIBUTION_H
#include <__config>
#include <__random/is_valid.h>
#include <__random/uniform_real_distribution.h>
#include <cmath>
#include <iosfwd>
#if !defined(_LIBCPP_HAS_NO_PRAGMA_SYSTEM_HEADER)
# pragma GCC system_header
#endif
_LIBCPP_PUSH_MACROS
#include <__undef_macros>
_LIBCPP_BEGIN_NAMESPACE_STD
template<class _IntType = int>
class _LIBCPP_TEMPLATE_VIS binomial_distribution
{
static_assert(__libcpp_random_is_valid_inttype<_IntType>::value, "IntType must be a supported integer type");
public:
// types
typedef _IntType result_type;
class _LIBCPP_TEMPLATE_VIS param_type
{
result_type __t_;
double __p_;
double __pr_;
double __odds_ratio_;
result_type __r0_;
public:
typedef binomial_distribution distribution_type;
explicit param_type(result_type __t = 1, double __p = 0.5);
_LIBCPP_INLINE_VISIBILITY
result_type t() const {return __t_;}
_LIBCPP_INLINE_VISIBILITY
double p() const {return __p_;}
friend _LIBCPP_INLINE_VISIBILITY
bool operator==(const param_type& __x, const param_type& __y)
{return __x.__t_ == __y.__t_ && __x.__p_ == __y.__p_;}
friend _LIBCPP_INLINE_VISIBILITY
bool operator!=(const param_type& __x, const param_type& __y)
{return !(__x == __y);}
friend class binomial_distribution;
};
private:
param_type __p_;
public:
// constructors and reset functions
#ifndef _LIBCPP_CXX03_LANG
_LIBCPP_INLINE_VISIBILITY
binomial_distribution() : binomial_distribution(1) {}
_LIBCPP_INLINE_VISIBILITY
explicit binomial_distribution(result_type __t, double __p = 0.5)
: __p_(param_type(__t, __p)) {}
#else
_LIBCPP_INLINE_VISIBILITY
explicit binomial_distribution(result_type __t = 1, double __p = 0.5)
: __p_(param_type(__t, __p)) {}
#endif
_LIBCPP_INLINE_VISIBILITY
explicit binomial_distribution(const param_type& __p) : __p_(__p) {}
_LIBCPP_INLINE_VISIBILITY
void reset() {}
// generating functions
template<class _URNG>
_LIBCPP_INLINE_VISIBILITY
result_type operator()(_URNG& __g)
{return (*this)(__g, __p_);}
template<class _URNG> result_type operator()(_URNG& __g, const param_type& __p);
// property functions
_LIBCPP_INLINE_VISIBILITY
result_type t() const {return __p_.t();}
_LIBCPP_INLINE_VISIBILITY
double p() const {return __p_.p();}
_LIBCPP_INLINE_VISIBILITY
param_type param() const {return __p_;}
_LIBCPP_INLINE_VISIBILITY
void param(const param_type& __p) {__p_ = __p;}
_LIBCPP_INLINE_VISIBILITY
result_type min() const {return 0;}
_LIBCPP_INLINE_VISIBILITY
result_type max() const {return t();}
friend _LIBCPP_INLINE_VISIBILITY
bool operator==(const binomial_distribution& __x,
const binomial_distribution& __y)
{return __x.__p_ == __y.__p_;}
friend _LIBCPP_INLINE_VISIBILITY
bool operator!=(const binomial_distribution& __x,
const binomial_distribution& __y)
{return !(__x == __y);}
};
inline _LIBCPP_INLINE_VISIBILITY double __libcpp_lgamma(double __d) {
#if defined(_LIBCPP_MSVCRT_LIKE)
return lgamma(__d);
#else
int __sign;
return lgamma_r(__d, &__sign);
#endif
}
template<class _IntType>
binomial_distribution<_IntType>::param_type::param_type(result_type __t, double __p)
: __t_(__t), __p_(__p)
{
if (0 < __p_ && __p_ < 1)
{
__r0_ = static_cast<result_type>((__t_ + 1) * __p_);
__pr_ = _VSTD::exp(std::__libcpp_lgamma(__t_ + 1.) -
std::__libcpp_lgamma(__r0_ + 1.) -
std::__libcpp_lgamma(__t_ - __r0_ + 1.) + __r0_ * _VSTD::log(__p_) +
(__t_ - __r0_) * _VSTD::log(1 - __p_));
__odds_ratio_ = __p_ / (1 - __p_);
}
}
// Reference: Kemp, C.D. (1986). `A modal method for generating binomial
// variables', Commun. Statist. - Theor. Meth. 15(3), 805-813.
template<class _IntType>
template<class _URNG>
_IntType
binomial_distribution<_IntType>::operator()(_URNG& __g, const param_type& __pr)
{
static_assert(__libcpp_random_is_valid_urng<_URNG>::value, "");
if (__pr.__t_ == 0 || __pr.__p_ == 0)
return 0;
if (__pr.__p_ == 1)
return __pr.__t_;
uniform_real_distribution<double> __gen;
double __u = __gen(__g) - __pr.__pr_;
if (__u < 0)
return __pr.__r0_;
double __pu = __pr.__pr_;
double __pd = __pu;
result_type __ru = __pr.__r0_;
result_type __rd = __ru;
while (true)
{
bool __break = true;
if (__rd >= 1)
{
__pd *= __rd / (__pr.__odds_ratio_ * (__pr.__t_ - __rd + 1));
__u -= __pd;
__break = false;
if (__u < 0)
return __rd - 1;
}
if ( __rd != 0 )
--__rd;
++__ru;
if (__ru <= __pr.__t_)
{
__pu *= (__pr.__t_ - __ru + 1) * __pr.__odds_ratio_ / __ru;
__u -= __pu;
__break = false;
if (__u < 0)
return __ru;
}
if (__break)
return 0;
}
}
template <class _CharT, class _Traits, class _IntType>
_LIBCPP_HIDE_FROM_ABI basic_ostream<_CharT, _Traits>&
operator<<(basic_ostream<_CharT, _Traits>& __os,
const binomial_distribution<_IntType>& __x)
{
__save_flags<_CharT, _Traits> __lx(__os);
typedef basic_ostream<_CharT, _Traits> _OStream;
__os.flags(_OStream::dec | _OStream::left | _OStream::fixed |
_OStream::scientific);
_CharT __sp = __os.widen(' ');
__os.fill(__sp);
return __os << __x.t() << __sp << __x.p();
}
template <class _CharT, class _Traits, class _IntType>
_LIBCPP_HIDE_FROM_ABI basic_istream<_CharT, _Traits>&
operator>>(basic_istream<_CharT, _Traits>& __is,
binomial_distribution<_IntType>& __x)
{
typedef binomial_distribution<_IntType> _Eng;
typedef typename _Eng::result_type result_type;
typedef typename _Eng::param_type param_type;
__save_flags<_CharT, _Traits> __lx(__is);
typedef basic_istream<_CharT, _Traits> _Istream;
__is.flags(_Istream::dec | _Istream::skipws);
result_type __t;
double __p;
__is >> __t >> __p;
if (!__is.fail())
__x.param(param_type(__t, __p));
return __is;
}
_LIBCPP_END_NAMESPACE_STD
_LIBCPP_POP_MACROS
#endif // _LIBCPP___RANDOM_BINOMIAL_DISTRIBUTION_H
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