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