mirror of
https://github.com/paboyle/Grid.git
synced 2024-09-20 01:05:38 +01:00
Freeze Gaussian implementation
This commit is contained in:
Peter Boyle
parent
7f6e2ee03e
commit
8637a9512a
200
Grid/random/gaussian.h
Normal file
200
Grid/random/gaussian.h
Normal file
@ -0,0 +1,200 @@
|
||||
// -*- C++ -*-
|
||||
//===--------------------------- random -----------------------------------===//
|
||||
//
|
||||
// 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
|
||||
//
|
||||
//===----------------------------------------------------------------------===//
|
||||
|
||||
// Peter Boyle: Taken from libc++ in Clang/LLVM.
|
||||
// Reason is that libstdc++ and clang differ in their return order in the normal_distribution / box mueller type step.
|
||||
// standardise on one and call it "gaussian_distribution".
|
||||
|
||||
#pragma once
|
||||
|
||||
#include <cstddef>
|
||||
#include <cstdint>
|
||||
#include <cmath>
|
||||
#include <type_traits>
|
||||
#include <initializer_list>
|
||||
#include <limits>
|
||||
#include <algorithm>
|
||||
#include <numeric>
|
||||
#include <vector>
|
||||
#include <string>
|
||||
#include <istream>
|
||||
#include <ostream>
|
||||
#include <random>
|
||||
|
||||
// normal_distribution -> gaussian distribution
|
||||
namespace Grid {
|
||||
|
||||
template<class _RealType = double>
|
||||
class gaussian_distribution
|
||||
{
|
||||
public:
|
||||
// types
|
||||
typedef _RealType result_type;
|
||||
|
||||
class param_type
|
||||
{
|
||||
result_type __mean_;
|
||||
result_type __stddev_;
|
||||
public:
|
||||
typedef gaussian_distribution distribution_type;
|
||||
|
||||
strong_inline
|
||||
explicit param_type(result_type __mean = 0, result_type __stddev = 1)
|
||||
: __mean_(__mean), __stddev_(__stddev) {}
|
||||
|
||||
strong_inline
|
||||
result_type mean() const {return __mean_;}
|
||||
strong_inline
|
||||
result_type stddev() const {return __stddev_;}
|
||||
|
||||
friend strong_inline
|
||||
bool operator==(const param_type& __x, const param_type& __y)
|
||||
{return __x.__mean_ == __y.__mean_ && __x.__stddev_ == __y.__stddev_;}
|
||||
friend strong_inline
|
||||
bool operator!=(const param_type& __x, const param_type& __y)
|
||||
{return !(__x == __y);}
|
||||
};
|
||||
|
||||
private:
|
||||
param_type __p_;
|
||||
result_type _V_;
|
||||
bool _V_hot_;
|
||||
|
||||
public:
|
||||
// constructors and reset functions
|
||||
strong_inline
|
||||
explicit gaussian_distribution(result_type __mean = 0, result_type __stddev = 1)
|
||||
: __p_(param_type(__mean, __stddev)), _V_hot_(false) {}
|
||||
strong_inline
|
||||
explicit gaussian_distribution(const param_type& __p)
|
||||
: __p_(__p), _V_hot_(false) {}
|
||||
strong_inline
|
||||
void reset() {_V_hot_ = false;}
|
||||
|
||||
// generating functions
|
||||
template<class _URNG>
|
||||
strong_inline
|
||||
result_type operator()(_URNG& __g)
|
||||
{return (*this)(__g, __p_);}
|
||||
template<class _URNG> result_type operator()(_URNG& __g, const param_type& __p);
|
||||
|
||||
// property functions
|
||||
strong_inline
|
||||
result_type mean() const {return __p_.mean();}
|
||||
strong_inline
|
||||
result_type stddev() const {return __p_.stddev();}
|
||||
|
||||
strong_inline
|
||||
param_type param() const {return __p_;}
|
||||
strong_inline
|
||||
void param(const param_type& __p) {__p_ = __p;}
|
||||
|
||||
strong_inline
|
||||
result_type min() const {return -std::numeric_limits<result_type>::infinity();}
|
||||
strong_inline
|
||||
result_type max() const {return std::numeric_limits<result_type>::infinity();}
|
||||
|
||||
friend strong_inline
|
||||
bool operator==(const gaussian_distribution& __x,
|
||||
const gaussian_distribution& __y)
|
||||
{return __x.__p_ == __y.__p_ && __x._V_hot_ == __y._V_hot_ &&
|
||||
(!__x._V_hot_ || __x._V_ == __y._V_);}
|
||||
friend strong_inline
|
||||
bool operator!=(const gaussian_distribution& __x,
|
||||
const gaussian_distribution& __y)
|
||||
{return !(__x == __y);}
|
||||
|
||||
template <class _CharT, class _Traits, class _RT>
|
||||
friend
|
||||
std::basic_ostream<_CharT, _Traits>&
|
||||
operator<<(std::basic_ostream<_CharT, _Traits>& __os,
|
||||
const gaussian_distribution<_RT>& __x);
|
||||
|
||||
template <class _CharT, class _Traits, class _RT>
|
||||
friend
|
||||
std::basic_istream<_CharT, _Traits>&
|
||||
operator>>(std::basic_istream<_CharT, _Traits>& __is,
|
||||
gaussian_distribution<_RT>& __x);
|
||||
};
|
||||
|
||||
template <class _RealType>
|
||||
template<class _URNG>
|
||||
_RealType
|
||||
gaussian_distribution<_RealType>::operator()(_URNG& __g, const param_type& __p)
|
||||
{
|
||||
result_type _Up;
|
||||
if (_V_hot_)
|
||||
{
|
||||
_V_hot_ = false;
|
||||
_Up = _V_;
|
||||
}
|
||||
else
|
||||
{
|
||||
std::uniform_real_distribution<result_type> _Uni(-1, 1);
|
||||
result_type __u;
|
||||
result_type __v;
|
||||
result_type __s;
|
||||
do
|
||||
{
|
||||
__u = _Uni(__g);
|
||||
__v = _Uni(__g);
|
||||
__s = __u * __u + __v * __v;
|
||||
} while (__s > 1 || __s == 0);
|
||||
result_type _Fp = _VSTD::sqrt(-2 * _VSTD::log(__s) / __s);
|
||||
_V_ = __v * _Fp;
|
||||
_V_hot_ = true;
|
||||
_Up = __u * _Fp;
|
||||
}
|
||||
return _Up * __p.stddev() + __p.mean();
|
||||
}
|
||||
|
||||
template <class _CharT, class _Traits, class _RT>
|
||||
std::basic_ostream<_CharT, _Traits>&
|
||||
operator<<(std::basic_ostream<_CharT, _Traits>& __os,
|
||||
const gaussian_distribution<_RT>& __x)
|
||||
{
|
||||
auto __save_flags = __os.flags();
|
||||
__os.flags(std::ios_base::dec | std::ios_base::left | std::ios_base::fixed |
|
||||
std::ios_base::scientific);
|
||||
_CharT __sp = __os.widen(' ');
|
||||
__os.fill(__sp);
|
||||
__os << __x.mean() << __sp << __x.stddev() << __sp << __x._V_hot_;
|
||||
if (__x._V_hot_)
|
||||
__os << __sp << __x._V_;
|
||||
__os.flags(__save_flags);
|
||||
return __os;
|
||||
}
|
||||
|
||||
template <class _CharT, class _Traits, class _RT>
|
||||
std::basic_istream<_CharT, _Traits>&
|
||||
operator>>(std::basic_istream<_CharT, _Traits>& __is,
|
||||
gaussian_distribution<_RT>& __x)
|
||||
{
|
||||
typedef gaussian_distribution<_RT> _Eng;
|
||||
typedef typename _Eng::result_type result_type;
|
||||
typedef typename _Eng::param_type param_type;
|
||||
auto __save_flags = __is.flags();
|
||||
__is.flags(std::ios_base::dec | std::ios_base::skipws);
|
||||
result_type __mean;
|
||||
result_type __stddev;
|
||||
result_type _Vp = 0;
|
||||
bool _V_hot = false;
|
||||
__is >> __mean >> __stddev >> _V_hot;
|
||||
if (_V_hot)
|
||||
__is >> _Vp;
|
||||
if (!__is.fail())
|
||||
{
|
||||
__x.param(param_type(__mean, __stddev));
|
||||
__x._V_hot_ = _V_hot;
|
||||
__x._V_ = _Vp;
|
||||
}
|
||||
__is.flags(__save_flags);
|
||||
return __is;
|
||||
}
|
||||
}
|
||||
Loading…
Reference in New Issue
Block a user