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authorarcadia-devtools <arcadia-devtools@yandex-team.ru>2022-03-11 15:09:26 +0300
committerarcadia-devtools <arcadia-devtools@yandex-team.ru>2022-03-11 15:09:26 +0300
commitf788a054cb1ff227c2958ac72f600a6617020dde (patch)
treeac431d866e93aa6e190359c7a8716dbce1a831ad /contrib/libs/cxxsupp/libcxx/include/__random/discrete_distribution.h
parent4e88d9ba201a15fa209d034b3a99bf1a0567e912 (diff)
downloadydb-f788a054cb1ff227c2958ac72f600a6617020dde.tar.gz
intermediate changes
ref:e5e2fe1e6ffa080d851e8418ce8b74d73ea51def
Diffstat (limited to 'contrib/libs/cxxsupp/libcxx/include/__random/discrete_distribution.h')
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diff --git a/contrib/libs/cxxsupp/libcxx/include/__random/discrete_distribution.h b/contrib/libs/cxxsupp/libcxx/include/__random/discrete_distribution.h
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+++ b/contrib/libs/cxxsupp/libcxx/include/__random/discrete_distribution.h
@@ -0,0 +1,260 @@
+//===----------------------------------------------------------------------===//
+//
+// 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_DISCRETE_DISTRIBUTION_H
+#define _LIBCPP___RANDOM_DISCRETE_DISTRIBUTION_H
+
+#include <__algorithm/upper_bound.h>
+#include <__config>
+#include <__random/uniform_real_distribution.h>
+#include <cstddef>
+#include <iosfwd>
+#include <numeric>
+#include <vector>
+
+#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 discrete_distribution
+{
+public:
+ // types
+ typedef _IntType result_type;
+
+ class _LIBCPP_TEMPLATE_VIS param_type
+ {
+ vector<double> __p_;
+ public:
+ typedef discrete_distribution distribution_type;
+
+ _LIBCPP_INLINE_VISIBILITY
+ param_type() {}
+ template<class _InputIterator>
+ _LIBCPP_INLINE_VISIBILITY
+ param_type(_InputIterator __f, _InputIterator __l)
+ : __p_(__f, __l) {__init();}
+#ifndef _LIBCPP_CXX03_LANG
+ _LIBCPP_INLINE_VISIBILITY
+ param_type(initializer_list<double> __wl)
+ : __p_(__wl.begin(), __wl.end()) {__init();}
+#endif // _LIBCPP_CXX03_LANG
+ template<class _UnaryOperation>
+ param_type(size_t __nw, double __xmin, double __xmax,
+ _UnaryOperation __fw);
+
+ vector<double> probabilities() const;
+
+ friend _LIBCPP_INLINE_VISIBILITY
+ bool operator==(const param_type& __x, const param_type& __y)
+ {return __x.__p_ == __y.__p_;}
+ friend _LIBCPP_INLINE_VISIBILITY
+ bool operator!=(const param_type& __x, const param_type& __y)
+ {return !(__x == __y);}
+
+ private:
+ void __init();
+
+ friend class discrete_distribution;
+
+ template <class _CharT, class _Traits, class _IT>
+ friend
+ basic_ostream<_CharT, _Traits>&
+ operator<<(basic_ostream<_CharT, _Traits>& __os,
+ const discrete_distribution<_IT>& __x);
+
+ template <class _CharT, class _Traits, class _IT>
+ friend
+ basic_istream<_CharT, _Traits>&
+ operator>>(basic_istream<_CharT, _Traits>& __is,
+ discrete_distribution<_IT>& __x);
+ };
+
+private:
+ param_type __p_;
+
+public:
+ // constructor and reset functions
+ _LIBCPP_INLINE_VISIBILITY
+ discrete_distribution() {}
+ template<class _InputIterator>
+ _LIBCPP_INLINE_VISIBILITY
+ discrete_distribution(_InputIterator __f, _InputIterator __l)
+ : __p_(__f, __l) {}
+#ifndef _LIBCPP_CXX03_LANG
+ _LIBCPP_INLINE_VISIBILITY
+ discrete_distribution(initializer_list<double> __wl)
+ : __p_(__wl) {}
+#endif // _LIBCPP_CXX03_LANG
+ template<class _UnaryOperation>
+ _LIBCPP_INLINE_VISIBILITY
+ discrete_distribution(size_t __nw, double __xmin, double __xmax,
+ _UnaryOperation __fw)
+ : __p_(__nw, __xmin, __xmax, __fw) {}
+ _LIBCPP_INLINE_VISIBILITY
+ explicit discrete_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
+ vector<double> probabilities() const {return __p_.probabilities();}
+
+ _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 __p_.__p_.size();}
+
+ friend _LIBCPP_INLINE_VISIBILITY
+ bool operator==(const discrete_distribution& __x,
+ const discrete_distribution& __y)
+ {return __x.__p_ == __y.__p_;}
+ friend _LIBCPP_INLINE_VISIBILITY
+ bool operator!=(const discrete_distribution& __x,
+ const discrete_distribution& __y)
+ {return !(__x == __y);}
+
+ template <class _CharT, class _Traits, class _IT>
+ friend
+ basic_ostream<_CharT, _Traits>&
+ operator<<(basic_ostream<_CharT, _Traits>& __os,
+ const discrete_distribution<_IT>& __x);
+
+ template <class _CharT, class _Traits, class _IT>
+ friend
+ basic_istream<_CharT, _Traits>&
+ operator>>(basic_istream<_CharT, _Traits>& __is,
+ discrete_distribution<_IT>& __x);
+};
+
+template<class _IntType>
+template<class _UnaryOperation>
+discrete_distribution<_IntType>::param_type::param_type(size_t __nw,
+ double __xmin,
+ double __xmax,
+ _UnaryOperation __fw)
+{
+ if (__nw > 1)
+ {
+ __p_.reserve(__nw - 1);
+ double __d = (__xmax - __xmin) / __nw;
+ double __d2 = __d / 2;
+ for (size_t __k = 0; __k < __nw; ++__k)
+ __p_.push_back(__fw(__xmin + __k * __d + __d2));
+ __init();
+ }
+}
+
+template<class _IntType>
+void
+discrete_distribution<_IntType>::param_type::__init()
+{
+ if (!__p_.empty())
+ {
+ if (__p_.size() > 1)
+ {
+ double __s = _VSTD::accumulate(__p_.begin(), __p_.end(), 0.0);
+ for (vector<double>::iterator __i = __p_.begin(), __e = __p_.end(); __i < __e; ++__i)
+ *__i /= __s;
+ vector<double> __t(__p_.size() - 1);
+ _VSTD::partial_sum(__p_.begin(), __p_.end() - 1, __t.begin());
+ swap(__p_, __t);
+ }
+ else
+ {
+ __p_.clear();
+ __p_.shrink_to_fit();
+ }
+ }
+}
+
+template<class _IntType>
+vector<double>
+discrete_distribution<_IntType>::param_type::probabilities() const
+{
+ size_t __n = __p_.size();
+ vector<double> __p(__n+1);
+ _VSTD::adjacent_difference(__p_.begin(), __p_.end(), __p.begin());
+ if (__n > 0)
+ __p[__n] = 1 - __p_[__n-1];
+ else
+ __p[0] = 1;
+ return __p;
+}
+
+template<class _IntType>
+template<class _URNG>
+_IntType
+discrete_distribution<_IntType>::operator()(_URNG& __g, const param_type& __p)
+{
+ uniform_real_distribution<double> __gen;
+ return static_cast<_IntType>(
+ _VSTD::upper_bound(__p.__p_.begin(), __p.__p_.end(), __gen(__g)) -
+ __p.__p_.begin());
+}
+
+template <class _CharT, class _Traits, class _IT>
+basic_ostream<_CharT, _Traits>&
+operator<<(basic_ostream<_CharT, _Traits>& __os,
+ const discrete_distribution<_IT>& __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);
+ size_t __n = __x.__p_.__p_.size();
+ __os << __n;
+ for (size_t __i = 0; __i < __n; ++__i)
+ __os << __sp << __x.__p_.__p_[__i];
+ return __os;
+}
+
+template <class _CharT, class _Traits, class _IT>
+basic_istream<_CharT, _Traits>&
+operator>>(basic_istream<_CharT, _Traits>& __is,
+ discrete_distribution<_IT>& __x)
+{
+ __save_flags<_CharT, _Traits> __lx(__is);
+ typedef basic_istream<_CharT, _Traits> _Istream;
+ __is.flags(_Istream::dec | _Istream::skipws);
+ size_t __n;
+ __is >> __n;
+ vector<double> __p(__n);
+ for (size_t __i = 0; __i < __n; ++__i)
+ __is >> __p[__i];
+ if (!__is.fail())
+ swap(__x.__p_.__p_, __p);
+ return __is;
+}
+
+_LIBCPP_END_NAMESPACE_STD
+
+_LIBCPP_POP_MACROS
+
+#endif // _LIBCPP___RANDOM_DISCRETE_DISTRIBUTION_H