CoCalc -- piecewise_linear

GitHub Repository: freebsd/freebsd-src
Path: blob/main/contrib/llvm-project/libcxx/include/__random/piecewise_linear_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_PIECEWISE_LINEAR_DISTRIBUTION_H
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#define _LIBCPP___RANDOM_PIECEWISE_LINEAR_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 <cmath>
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#include <iosfwd>
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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 _RealType = double>
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class _LIBCPP_TEMPLATE_VIS piecewise_linear_distribution {
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  static_assert(__libcpp_random_is_valid_realtype<_RealType>::value,
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                "RealType must be a supported floating-point type");
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public:
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  // types
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  typedef _RealType result_type;
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  class _LIBCPP_TEMPLATE_VIS param_type {
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    vector<result_type> __b_;
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    vector<result_type> __densities_;
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    vector<result_type> __areas_;
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  public:
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    typedef piecewise_linear_distribution distribution_type;
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    _LIBCPP_HIDE_FROM_ABI param_type();
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    template <class _InputIteratorB, class _InputIteratorW>
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    _LIBCPP_HIDE_FROM_ABI param_type(_InputIteratorB __f_b, _InputIteratorB __l_b, _InputIteratorW __f_w);
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#ifndef _LIBCPP_CXX03_LANG
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    template <class _UnaryOperation>
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    _LIBCPP_HIDE_FROM_ABI param_type(initializer_list<result_type> __bl, _UnaryOperation __fw);
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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, result_type __xmin, result_type __xmax, _UnaryOperation __fw);
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    _LIBCPP_HIDE_FROM_ABI param_type(param_type const&) = default;
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    _LIBCPP_HIDE_FROM_ABI param_type& operator=(const param_type& __rhs);
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    _LIBCPP_HIDE_FROM_ABI vector<result_type> intervals() const { return __b_; }
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    _LIBCPP_HIDE_FROM_ABI vector<result_type> densities() const { return __densities_; }
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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.__densities_ == __y.__densities_ && __x.__b_ == __y.__b_;
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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 piecewise_linear_distribution;
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    template <class _CharT, class _Traits, class _RT>
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    friend basic_ostream<_CharT, _Traits>&
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    operator<<(basic_ostream<_CharT, _Traits>& __os, const piecewise_linear_distribution<_RT>& __x);
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    template <class _CharT, class _Traits, class _RT>
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    friend basic_istream<_CharT, _Traits>&
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    operator>>(basic_istream<_CharT, _Traits>& __is, piecewise_linear_distribution<_RT>& __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 piecewise_linear_distribution() {}
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  template <class _InputIteratorB, class _InputIteratorW>
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  _LIBCPP_HIDE_FROM_ABI
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  piecewise_linear_distribution(_InputIteratorB __f_b, _InputIteratorB __l_b, _InputIteratorW __f_w)
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      : __p_(__f_b, __l_b, __f_w) {}
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#ifndef _LIBCPP_CXX03_LANG
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  template <class _UnaryOperation>
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  _LIBCPP_HIDE_FROM_ABI piecewise_linear_distribution(initializer_list<result_type> __bl, _UnaryOperation __fw)
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      : __p_(__bl, __fw) {}
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#endif // _LIBCPP_CXX03_LANG
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  template <class _UnaryOperation>
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  _LIBCPP_HIDE_FROM_ABI
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  piecewise_linear_distribution(size_t __nw, result_type __xmin, result_type __xmax, _UnaryOperation __fw)
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      : __p_(__nw, __xmin, __xmax, __fw) {}
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  _LIBCPP_HIDE_FROM_ABI explicit piecewise_linear_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<result_type> intervals() const { return __p_.intervals(); }
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  _LIBCPP_HIDE_FROM_ABI vector<result_type> densities() const { return __p_.densities(); }
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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 __p_.__b_.front(); }
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  _LIBCPP_HIDE_FROM_ABI result_type max() const { return __p_.__b_.back(); }
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  friend _LIBCPP_HIDE_FROM_ABI bool
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  operator==(const piecewise_linear_distribution& __x, const piecewise_linear_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
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  operator!=(const piecewise_linear_distribution& __x, const piecewise_linear_distribution& __y) {
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    return !(__x == __y);
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  }
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  template <class _CharT, class _Traits, class _RT>
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  friend basic_ostream<_CharT, _Traits>&
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  operator<<(basic_ostream<_CharT, _Traits>& __os, const piecewise_linear_distribution<_RT>& __x);
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  template <class _CharT, class _Traits, class _RT>
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  friend basic_istream<_CharT, _Traits>&
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  operator>>(basic_istream<_CharT, _Traits>& __is, piecewise_linear_distribution<_RT>& __x);
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};
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template <class _RealType>
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typename piecewise_linear_distribution<_RealType>::param_type&
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piecewise_linear_distribution<_RealType>::param_type::operator=(const param_type& __rhs) {
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  //  These can throw
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  __b_.reserve(__rhs.__b_.size());
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  __densities_.reserve(__rhs.__densities_.size());
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  __areas_.reserve(__rhs.__areas_.size());
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  //  These can not throw
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  __b_         = __rhs.__b_;
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  __densities_ = __rhs.__densities_;
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  __areas_     = __rhs.__areas_;
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  return *this;
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}
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template <class _RealType>
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void piecewise_linear_distribution<_RealType>::param_type::__init() {
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  __areas_.assign(__densities_.size() - 1, result_type());
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  result_type __sp = 0;
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  for (size_t __i = 0; __i < __areas_.size(); ++__i) {
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    __areas_[__i] = (__densities_[__i + 1] + __densities_[__i]) * (__b_[__i + 1] - __b_[__i]) * .5;
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    __sp += __areas_[__i];
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  }
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  for (size_t __i = __areas_.size(); __i > 1;) {
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    --__i;
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    __areas_[__i] = __areas_[__i - 1] / __sp;
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  }
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  __areas_[0] = 0;
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  for (size_t __i = 1; __i < __areas_.size(); ++__i)
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    __areas_[__i] += __areas_[__i - 1];
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  for (size_t __i = 0; __i < __densities_.size(); ++__i)
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    __densities_[__i] /= __sp;
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}
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template <class _RealType>
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piecewise_linear_distribution<_RealType>::param_type::param_type() : __b_(2), __densities_(2, 1.0), __areas_(1, 0.0) {
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  __b_[1] = 1;
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}
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template <class _RealType>
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template <class _InputIteratorB, class _InputIteratorW>
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piecewise_linear_distribution<_RealType>::param_type::param_type(
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    _InputIteratorB __f_b, _InputIteratorB __l_b, _InputIteratorW __f_w)
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    : __b_(__f_b, __l_b) {
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  if (__b_.size() < 2) {
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    __b_.resize(2);
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    __b_[0] = 0;
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    __b_[1] = 1;
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    __densities_.assign(2, 1.0);
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    __areas_.assign(1, 0.0);
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  } else {
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    __densities_.reserve(__b_.size());
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    for (size_t __i = 0; __i < __b_.size(); ++__i, ++__f_w)
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      __densities_.push_back(*__f_w);
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    __init();
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  }
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}
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#ifndef _LIBCPP_CXX03_LANG
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template <class _RealType>
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template <class _UnaryOperation>
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piecewise_linear_distribution<_RealType>::param_type::param_type(
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    initializer_list<result_type> __bl, _UnaryOperation __fw)
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    : __b_(__bl.begin(), __bl.end()) {
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  if (__b_.size() < 2) {
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    __b_.resize(2);
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    __b_[0] = 0;
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    __b_[1] = 1;
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    __densities_.assign(2, 1.0);
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    __areas_.assign(1, 0.0);
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  } else {
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    __densities_.reserve(__b_.size());
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    for (size_t __i = 0; __i < __b_.size(); ++__i)
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      __densities_.push_back(__fw(__b_[__i]));
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    __init();
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  }
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}
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#endif // _LIBCPP_CXX03_LANG
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template <class _RealType>
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template <class _UnaryOperation>
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piecewise_linear_distribution<_RealType>::param_type::param_type(
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    size_t __nw, result_type __xmin, result_type __xmax, _UnaryOperation __fw)
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    : __b_(__nw == 0 ? 2 : __nw + 1) {
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  size_t __n      = __b_.size() - 1;
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  result_type __d = (__xmax - __xmin) / __n;
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  __densities_.reserve(__b_.size());
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  for (size_t __i = 0; __i < __n; ++__i) {
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    __b_[__i] = __xmin + __i * __d;
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    __densities_.push_back(__fw(__b_[__i]));
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  }
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  __b_[__n] = __xmax;
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  __densities_.push_back(__fw(__b_[__n]));
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  __init();
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}
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template <class _RealType>
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template <class _URNG>
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_RealType piecewise_linear_distribution<_RealType>::operator()(_URNG& __g, const param_type& __p) {
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  static_assert(__libcpp_random_is_valid_urng<_URNG>::value, "");
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  typedef uniform_real_distribution<result_type> _Gen;
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  result_type __u = _Gen()(__g);
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  ptrdiff_t __k   = std::upper_bound(__p.__areas_.begin(), __p.__areas_.end(), __u) - __p.__areas_.begin() - 1;
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  __u -= __p.__areas_[__k];
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  const result_type __dk     = __p.__densities_[__k];
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  const result_type __dk1    = __p.__densities_[__k + 1];
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  const result_type __deltad = __dk1 - __dk;
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  const result_type __bk     = __p.__b_[__k];
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  if (__deltad == 0)
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    return __u / __dk + __bk;
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  const result_type __bk1    = __p.__b_[__k + 1];
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  const result_type __deltab = __bk1 - __bk;
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  return (__bk * __dk1 - __bk1 * __dk + std::sqrt(__deltab * (__deltab * __dk * __dk + 2 * __deltad * __u))) / __deltad;
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}
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template <class _CharT, class _Traits, class _RT>
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_LIBCPP_HIDE_FROM_ABI basic_ostream<_CharT, _Traits>&
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operator<<(basic_ostream<_CharT, _Traits>& __os, const piecewise_linear_distribution<_RT>& __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_.__b_.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_.__b_[__i];
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  __n = __x.__p_.__densities_.size();
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  __os << __sp << __n;
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  for (size_t __i = 0; __i < __n; ++__i)
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    __os << __sp << __x.__p_.__densities_[__i];
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  __n = __x.__p_.__areas_.size();
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  __os << __sp << __n;
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  for (size_t __i = 0; __i < __n; ++__i)
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    __os << __sp << __x.__p_.__areas_[__i];
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  return __os;
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}
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template <class _CharT, class _Traits, class _RT>
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_LIBCPP_HIDE_FROM_ABI basic_istream<_CharT, _Traits>&
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operator>>(basic_istream<_CharT, _Traits>& __is, piecewise_linear_distribution<_RT>& __x) {
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  typedef piecewise_linear_distribution<_RT> _Eng;
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  typedef typename _Eng::result_type result_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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  size_t __n;
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  __is >> __n;
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  vector<result_type> __b(__n);
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  for (size_t __i = 0; __i < __n; ++__i)
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    __is >> __b[__i];
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  __is >> __n;
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  vector<result_type> __densities(__n);
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  for (size_t __i = 0; __i < __n; ++__i)
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    __is >> __densities[__i];
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  __is >> __n;
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  vector<result_type> __areas(__n);
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  for (size_t __i = 0; __i < __n; ++__i)
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    __is >> __areas[__i];
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  if (!__is.fail()) {
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    swap(__x.__p_.__b_, __b);
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    swap(__x.__p_.__densities_, __densities);
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    swap(__x.__p_.__areas_, __areas);
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  }
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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_PIECEWISE_LINEAR_DISTRIBUTION_H
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