CoCalc -- discrete_distribution.h

GitHub Repository: freebsd/freebsd-src
Path: blob/main/contrib/llvm-project/libcxx/include/__random/discrete_distribution.h
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//===----------------------------------------------------------------------===//
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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_DISCRETE_DISTRIBUTION_H
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#define _LIBCPP___RANDOM_DISCRETE_DISTRIBUTION_H
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#include <__algorithm/upper_bound.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 <cstddef>
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#include <iosfwd>
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#include <numeric>
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#include <vector>
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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 discrete_distribution {
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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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    vector<double> __p_;
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  public:
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    typedef discrete_distribution distribution_type;
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    _LIBCPP_HIDE_FROM_ABI param_type() {}
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    template <class _InputIterator>
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    _LIBCPP_HIDE_FROM_ABI param_type(_InputIterator __f, _InputIterator __l) : __p_(__f, __l) {
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      __init();
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    }
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#ifndef _LIBCPP_CXX03_LANG
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    _LIBCPP_HIDE_FROM_ABI param_type(initializer_list<double> __wl) : __p_(__wl.begin(), __wl.end()) { __init(); }
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#endif // _LIBCPP_CXX03_LANG
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    template <class _UnaryOperation>
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    _LIBCPP_HIDE_FROM_ABI param_type(size_t __nw, double __xmin, double __xmax, _UnaryOperation __fw);
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    _LIBCPP_HIDE_FROM_ABI vector<double> probabilities() const;
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    friend _LIBCPP_HIDE_FROM_ABI bool operator==(const param_type& __x, const param_type& __y) {
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      return __x.__p_ == __y.__p_;
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    }
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    friend _LIBCPP_HIDE_FROM_ABI bool operator!=(const param_type& __x, const param_type& __y) { return !(__x == __y); }
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  private:
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    _LIBCPP_HIDE_FROM_ABI void __init();
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    friend class discrete_distribution;
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    template <class _CharT, class _Traits, class _IT>
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    friend basic_ostream<_CharT, _Traits>&
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    operator<<(basic_ostream<_CharT, _Traits>& __os, const discrete_distribution<_IT>& __x);
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    template <class _CharT, class _Traits, class _IT>
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    friend basic_istream<_CharT, _Traits>&
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    operator>>(basic_istream<_CharT, _Traits>& __is, discrete_distribution<_IT>& __x);
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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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  // constructor and reset functions
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  _LIBCPP_HIDE_FROM_ABI discrete_distribution() {}
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  template <class _InputIterator>
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  _LIBCPP_HIDE_FROM_ABI discrete_distribution(_InputIterator __f, _InputIterator __l) : __p_(__f, __l) {}
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#ifndef _LIBCPP_CXX03_LANG
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  _LIBCPP_HIDE_FROM_ABI discrete_distribution(initializer_list<double> __wl) : __p_(__wl) {}
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#endif // _LIBCPP_CXX03_LANG
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  template <class _UnaryOperation>
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  _LIBCPP_HIDE_FROM_ABI discrete_distribution(size_t __nw, double __xmin, double __xmax, _UnaryOperation __fw)
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      : __p_(__nw, __xmin, __xmax, __fw) {}
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  _LIBCPP_HIDE_FROM_ABI explicit discrete_distribution(const param_type& __p) : __p_(__p) {}
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  _LIBCPP_HIDE_FROM_ABI void reset() {}
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  // generating functions
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  template <class _URNG>
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  _LIBCPP_HIDE_FROM_ABI result_type operator()(_URNG& __g) {
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    return (*this)(__g, __p_);
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  }
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  template <class _URNG>
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  _LIBCPP_HIDE_FROM_ABI result_type operator()(_URNG& __g, const param_type& __p);
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  // property functions
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  _LIBCPP_HIDE_FROM_ABI vector<double> probabilities() const { return __p_.probabilities(); }
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  _LIBCPP_HIDE_FROM_ABI param_type param() const { return __p_; }
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  _LIBCPP_HIDE_FROM_ABI void param(const param_type& __p) { __p_ = __p; }
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  _LIBCPP_HIDE_FROM_ABI result_type min() const { return 0; }
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  _LIBCPP_HIDE_FROM_ABI result_type max() const { return __p_.__p_.size(); }
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  friend _LIBCPP_HIDE_FROM_ABI bool operator==(const discrete_distribution& __x, const discrete_distribution& __y) {
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    return __x.__p_ == __y.__p_;
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  }
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  friend _LIBCPP_HIDE_FROM_ABI bool operator!=(const discrete_distribution& __x, const discrete_distribution& __y) {
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    return !(__x == __y);
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  }
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  template <class _CharT, class _Traits, class _IT>
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  friend basic_ostream<_CharT, _Traits>&
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  operator<<(basic_ostream<_CharT, _Traits>& __os, const discrete_distribution<_IT>& __x);
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  template <class _CharT, class _Traits, class _IT>
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  friend basic_istream<_CharT, _Traits>&
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  operator>>(basic_istream<_CharT, _Traits>& __is, discrete_distribution<_IT>& __x);
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};
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template <class _IntType>
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template <class _UnaryOperation>
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discrete_distribution<_IntType>::param_type::param_type(
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    size_t __nw, double __xmin, double __xmax, _UnaryOperation __fw) {
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  if (__nw > 1) {
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    __p_.reserve(__nw - 1);
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    double __d  = (__xmax - __xmin) / __nw;
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    double __d2 = __d / 2;
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    for (size_t __k = 0; __k < __nw; ++__k)
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      __p_.push_back(__fw(__xmin + __k * __d + __d2));
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    __init();
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  }
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}
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template <class _IntType>
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void discrete_distribution<_IntType>::param_type::__init() {
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  if (!__p_.empty()) {
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    if (__p_.size() > 1) {
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      double __s = std::accumulate(__p_.begin(), __p_.end(), 0.0);
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      for (vector<double>::iterator __i = __p_.begin(), __e = __p_.end(); __i < __e; ++__i)
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        *__i /= __s;
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      vector<double> __t(__p_.size() - 1);
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      std::partial_sum(__p_.begin(), __p_.end() - 1, __t.begin());
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      swap(__p_, __t);
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    } else {
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      __p_.clear();
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      __p_.shrink_to_fit();
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    }
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  }
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}
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template <class _IntType>
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vector<double> discrete_distribution<_IntType>::param_type::probabilities() const {
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  size_t __n = __p_.size();
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  vector<double> __p(__n + 1);
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  std::adjacent_difference(__p_.begin(), __p_.end(), __p.begin());
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  if (__n > 0)
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    __p[__n] = 1 - __p_[__n - 1];
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  else
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    __p[0] = 1;
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  return __p;
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}
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template <class _IntType>
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template <class _URNG>
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_IntType discrete_distribution<_IntType>::operator()(_URNG& __g, const param_type& __p) {
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  static_assert(__libcpp_random_is_valid_urng<_URNG>::value, "");
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  uniform_real_distribution<double> __gen;
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  return static_cast<_IntType>(std::upper_bound(__p.__p_.begin(), __p.__p_.end(), __gen(__g)) - __p.__p_.begin());
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}
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template <class _CharT, class _Traits, class _IT>
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_LIBCPP_HIDE_FROM_ABI basic_ostream<_CharT, _Traits>&
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operator<<(basic_ostream<_CharT, _Traits>& __os, const discrete_distribution<_IT>& __x) {
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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 | _OStream::scientific);
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  _CharT __sp = __os.widen(' ');
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  __os.fill(__sp);
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  size_t __n = __x.__p_.__p_.size();
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  __os << __n;
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  for (size_t __i = 0; __i < __n; ++__i)
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    __os << __sp << __x.__p_.__p_[__i];
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  return __os;
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}
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template <class _CharT, class _Traits, class _IT>
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_LIBCPP_HIDE_FROM_ABI basic_istream<_CharT, _Traits>&
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operator>>(basic_istream<_CharT, _Traits>& __is, discrete_distribution<_IT>& __x) {
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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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  size_t __n;
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  __is >> __n;
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  vector<double> __p(__n);
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  for (size_t __i = 0; __i < __n; ++__i)
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    __is >> __p[__i];
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  if (!__is.fail())
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    swap(__x.__p_.__p_, __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_DISCRETE_DISTRIBUTION_H
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