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