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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#ifndef EIGEN_NUMTRAITS_H
#define EIGEN_NUMTRAITS_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
// default implementation of digits(), based on numeric_limits if specialized,
// 0 for integer types, and log2(epsilon()) otherwise.
template< typename T,
bool use_numeric_limits = std::numeric_limits<T>::is_specialized,
bool is_integer = NumTraits<T>::IsInteger>
struct default_digits_impl
{
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static int run() { return std::numeric_limits<T>::digits; }
};
template<typename T>
struct default_digits_impl<T,false,false> // Floating point
{
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static int run() {
using std::log2;
using std::ceil;
typedef typename NumTraits<T>::Real Real;
return int(ceil(-log2(NumTraits<Real>::epsilon())));
}
};
template<typename T>
struct default_digits_impl<T,false,true> // Integer
{
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static int run() { return 0; }
};
// default implementation of digits10(), based on numeric_limits if specialized,
// 0 for integer types, and floor((digits()-1)*log10(2)) otherwise.
template< typename T,
bool use_numeric_limits = std::numeric_limits<T>::is_specialized,
bool is_integer = NumTraits<T>::IsInteger>
struct default_digits10_impl
{
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static int run() { return std::numeric_limits<T>::digits10; }
};
template<typename T>
struct default_digits10_impl<T,false,false> // Floating point
{
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static int run() {
using std::log10;
using std::floor;
typedef typename NumTraits<T>::Real Real;
return int(floor((internal::default_digits_impl<Real>::run()-1)*log10(2)));
}
};
template<typename T>
struct default_digits10_impl<T,false,true> // Integer
{
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static int run() { return 0; }
};
// default implementation of max_digits10(), based on numeric_limits if specialized,
// 0 for integer types, and log10(2) * digits() + 1 otherwise.
template< typename T,
bool use_numeric_limits = std::numeric_limits<T>::is_specialized,
bool is_integer = NumTraits<T>::IsInteger>
struct default_max_digits10_impl
{
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static int run() { return std::numeric_limits<T>::max_digits10; }
};
template<typename T>
struct default_max_digits10_impl<T,false,false> // Floating point
{
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static int run() {
using std::log10;
using std::ceil;
typedef typename NumTraits<T>::Real Real;
return int(ceil(internal::default_digits_impl<Real>::run()*log10(2)+1));
}
};
template<typename T>
struct default_max_digits10_impl<T,false,true> // Integer
{
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static int run() { return 0; }
};
} // end namespace internal
namespace numext {
/** \internal bit-wise cast without changing the underlying bit representation. */
// TODO: Replace by std::bit_cast (available in C++20)
template <typename Tgt, typename Src>
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Tgt bit_cast(const Src& src) {
// The behaviour of memcpy is not specified for non-trivially copyable types
EIGEN_STATIC_ASSERT(std::is_trivially_copyable<Src>::value, THIS_TYPE_IS_NOT_SUPPORTED);
EIGEN_STATIC_ASSERT(std::is_trivially_copyable<Tgt>::value && std::is_default_constructible<Tgt>::value,
THIS_TYPE_IS_NOT_SUPPORTED);
EIGEN_STATIC_ASSERT(sizeof(Src) == sizeof(Tgt), THIS_TYPE_IS_NOT_SUPPORTED);
Tgt tgt;
// Load src into registers first. This allows the memcpy to be elided by CUDA.
const Src staged = src;
EIGEN_USING_STD(memcpy)
memcpy(static_cast<void*>(&tgt),static_cast<const void*>(&staged), sizeof(Tgt));
return tgt;
}
} // namespace numext
/** \class NumTraits
* \ingroup Core_Module
*
* \brief Holds information about the various numeric (i.e. scalar) types allowed by Eigen.
*
* \tparam T the numeric type at hand
*
* This class stores enums, typedefs and static methods giving information about a numeric type.
*
* The provided data consists of:
* \li A typedef \c Real, giving the "real part" type of \a T. If \a T is already real,
* then \c Real is just a typedef to \a T. If \a T is \c std::complex<U> then \c Real
* is a typedef to \a U.
* \li A typedef \c NonInteger, giving the type that should be used for operations producing non-integral values,
* such as quotients, square roots, etc. If \a T is a floating-point type, then this typedef just gives
* \a T again. Note however that many Eigen functions such as internal::sqrt simply refuse to
* take integers. Outside of a few cases, Eigen doesn't do automatic type promotion. Thus, this typedef is
* only intended as a helper for code that needs to explicitly promote types.
* \li A typedef \c Literal giving the type to use for numeric literals such as "2" or "0.5". For instance, for \c std::complex<U>, Literal is defined as \c U.
* Of course, this type must be fully compatible with \a T. In doubt, just use \a T here.
* \li A typedef \a Nested giving the type to use to nest a value inside of the expression tree. If you don't know what
* this means, just use \a T here.
* \li An enum value \a IsComplex. It is equal to 1 if \a T is a \c std::complex
* type, and to 0 otherwise.
* \li An enum value \a IsInteger. It is equal to \c 1 if \a T is an integer type such as \c int,
* and to \c 0 otherwise.
* \li Enum values ReadCost, AddCost and MulCost representing a rough estimate of the number of CPU cycles needed
* to by move / add / mul instructions respectively, assuming the data is already stored in CPU registers.
* Stay vague here. No need to do architecture-specific stuff. If you don't know what this means, just use \c Eigen::HugeCost.
* \li An enum value \a IsSigned. It is equal to \c 1 if \a T is a signed type and to 0 if \a T is unsigned.
* \li An enum value \a RequireInitialization. It is equal to \c 1 if the constructor of the numeric type \a T must
* be called, and to 0 if it is safe not to call it. Default is 0 if \a T is an arithmetic type, and 1 otherwise.
* \li An epsilon() function which, unlike <a href="http://en.cppreference.com/w/cpp/types/numeric_limits/epsilon">std::numeric_limits::epsilon()</a>,
* it returns a \a Real instead of a \a T.
* \li A dummy_precision() function returning a weak epsilon value. It is mainly used as a default
* value by the fuzzy comparison operators.
* \li highest() and lowest() functions returning the highest and lowest possible values respectively.
* \li digits() function returning the number of radix digits (non-sign digits for integers, mantissa for floating-point). This is
* the analogue of <a href="http://en.cppreference.com/w/cpp/types/numeric_limits/digits">std::numeric_limits<T>::digits</a>
* which is used as the default implementation if specialized.
* \li digits10() function returning the number of decimal digits that can be represented without change. This is
* the analogue of <a href="http://en.cppreference.com/w/cpp/types/numeric_limits/digits10">std::numeric_limits<T>::digits10</a>
* which is used as the default implementation if specialized.
* \li max_digits10() function returning the number of decimal digits required to uniquely represent all distinct values of the type. This is
* the analogue of <a href="http://en.cppreference.com/w/cpp/types/numeric_limits/max_digits10">std::numeric_limits<T>::max_digits10</a>
* which is used as the default implementation if specialized.
* \li min_exponent() and max_exponent() functions returning the highest and lowest possible values, respectively,
* such that the radix raised to the power exponent-1 is a normalized floating-point number. These are equivalent to
* <a href="http://en.cppreference.com/w/cpp/types/numeric_limits/min_exponent">std::numeric_limits<T>::min_exponent</a>/
* <a href="http://en.cppreference.com/w/cpp/types/numeric_limits/max_exponent">std::numeric_limits<T>::max_exponent</a>.
* \li infinity() function returning a representation of positive infinity, if available.
* \li quiet_NaN function returning a non-signaling "not-a-number", if available.
*/
template<typename T> struct GenericNumTraits
{
enum {
IsInteger = std::numeric_limits<T>::is_integer,
IsSigned = std::numeric_limits<T>::is_signed,
IsComplex = 0,
RequireInitialization = internal::is_arithmetic<T>::value ? 0 : 1,
ReadCost = 1,
AddCost = 1,
MulCost = 1
};
typedef T Real;
typedef std::conditional_t<IsInteger, std::conditional_t<sizeof(T)<=2, float, double>, T> NonInteger;
typedef T Nested;
typedef T Literal;
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline Real epsilon()
{
return numext::numeric_limits<T>::epsilon();
}
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline int digits10()
{
return internal::default_digits10_impl<T>::run();
}
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline int max_digits10()
{
return internal::default_max_digits10_impl<T>::run();
}
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline int digits()
{
return internal::default_digits_impl<T>::run();
}
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline int min_exponent()
{
return numext::numeric_limits<T>::min_exponent;
}
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline int max_exponent()
{
return numext::numeric_limits<T>::max_exponent;
}
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline Real dummy_precision()
{
// make sure to override this for floating-point types
return Real(0);
}
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline T highest() {
return (numext::numeric_limits<T>::max)();
}
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline T lowest() {
return IsInteger ? (numext::numeric_limits<T>::min)()
: static_cast<T>(-(numext::numeric_limits<T>::max)());
}
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline T infinity() {
return numext::numeric_limits<T>::infinity();
}
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline T quiet_NaN() {
return numext::numeric_limits<T>::quiet_NaN();
}
};
template<typename T> struct NumTraits : GenericNumTraits<T>
{};
template<> struct NumTraits<float>
: GenericNumTraits<float>
{
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline float dummy_precision() { return 1e-5f; }
};
template<> struct NumTraits<double> : GenericNumTraits<double>
{
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline double dummy_precision() { return 1e-12; }
};
// GPU devices treat `long double` as `double`.
#ifndef EIGEN_GPU_COMPILE_PHASE
template<> struct NumTraits<long double>
: GenericNumTraits<long double>
{
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline long double dummy_precision() { return static_cast<long double>(1e-15l); }
#if defined(EIGEN_ARCH_PPC) && (__LDBL_MANT_DIG__ == 106)
// PowerPC double double causes issues with some values
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline long double epsilon()
{
// 2^(-(__LDBL_MANT_DIG__)+1)
return static_cast<long double>(2.4651903288156618919116517665087e-32l);
}
#endif
};
#endif
template<typename Real_> struct NumTraits<std::complex<Real_> >
: GenericNumTraits<std::complex<Real_> >
{
typedef Real_ Real;
typedef typename NumTraits<Real_>::Literal Literal;
enum {
IsComplex = 1,
RequireInitialization = NumTraits<Real_>::RequireInitialization,
ReadCost = 2 * NumTraits<Real_>::ReadCost,
AddCost = 2 * NumTraits<Real>::AddCost,
MulCost = 4 * NumTraits<Real>::MulCost + 2 * NumTraits<Real>::AddCost
};
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline Real epsilon() { return NumTraits<Real>::epsilon(); }
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline Real dummy_precision() { return NumTraits<Real>::dummy_precision(); }
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline int digits10() { return NumTraits<Real>::digits10(); }
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline int max_digits10() { return NumTraits<Real>::max_digits10(); }
};
template<typename Scalar, int Rows, int Cols, int Options, int MaxRows, int MaxCols>
struct NumTraits<Array<Scalar, Rows, Cols, Options, MaxRows, MaxCols> >
{
typedef Array<Scalar, Rows, Cols, Options, MaxRows, MaxCols> ArrayType;
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef Array<RealScalar, Rows, Cols, Options, MaxRows, MaxCols> Real;
typedef typename NumTraits<Scalar>::NonInteger NonIntegerScalar;
typedef Array<NonIntegerScalar, Rows, Cols, Options, MaxRows, MaxCols> NonInteger;
typedef ArrayType & Nested;
typedef typename NumTraits<Scalar>::Literal Literal;
enum {
IsComplex = NumTraits<Scalar>::IsComplex,
IsInteger = NumTraits<Scalar>::IsInteger,
IsSigned = NumTraits<Scalar>::IsSigned,
RequireInitialization = 1,
ReadCost = ArrayType::SizeAtCompileTime==Dynamic ? HugeCost : ArrayType::SizeAtCompileTime * int(NumTraits<Scalar>::ReadCost),
AddCost = ArrayType::SizeAtCompileTime==Dynamic ? HugeCost : ArrayType::SizeAtCompileTime * int(NumTraits<Scalar>::AddCost),
MulCost = ArrayType::SizeAtCompileTime==Dynamic ? HugeCost : ArrayType::SizeAtCompileTime * int(NumTraits<Scalar>::MulCost)
};
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline RealScalar epsilon() { return NumTraits<RealScalar>::epsilon(); }
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
static inline RealScalar dummy_precision() { return NumTraits<RealScalar>::dummy_precision(); }
EIGEN_CONSTEXPR
static inline int digits10() { return NumTraits<Scalar>::digits10(); }
EIGEN_CONSTEXPR
static inline int max_digits10() { return NumTraits<Scalar>::max_digits10(); }
};
template<> struct NumTraits<std::string>
: GenericNumTraits<std::string>
{
enum {
RequireInitialization = 1,
ReadCost = HugeCost,
AddCost = HugeCost,
MulCost = HugeCost
};
EIGEN_CONSTEXPR
static inline int digits10() { return 0; }
EIGEN_CONSTEXPR
static inline int max_digits10() { return 0; }
private:
static inline std::string epsilon();
static inline std::string dummy_precision();
static inline std::string lowest();
static inline std::string highest();
static inline std::string infinity();
static inline std::string quiet_NaN();
};
// Empty specialization for void to allow template specialization based on NumTraits<T>::Real with T==void and SFINAE.
template<> struct NumTraits<void> {};
template<> struct NumTraits<bool> : GenericNumTraits<bool> {};
} // end namespace Eigen
#endif // EIGEN_NUMTRAITS_H