|  | // This file is part of Eigen, a lightweight C++ template library | 
|  | // for linear algebra. | 
|  | // | 
|  | // Copyright (C) 2014 Pedro Gonnet (pedro.gonnet@gmail.com) | 
|  | // Copyright (C) 2016 Gael Guennebaud <gael.guennebaud@inria.fr> | 
|  | // | 
|  | // 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_MATHFUNCTIONSIMPL_H | 
|  | #define EIGEN_MATHFUNCTIONSIMPL_H | 
|  |  | 
|  | #include "./InternalHeaderCheck.h" | 
|  |  | 
|  | namespace Eigen { | 
|  |  | 
|  | namespace internal { | 
|  |  | 
|  | /** \internal \returns the hyperbolic tan of \a a (coeff-wise) | 
|  | Doesn't do anything fancy, just a 13/6-degree rational interpolant which | 
|  | is accurate up to a couple of ulps in the (approximate) range [-8, 8], | 
|  | outside of which tanh(x) = +/-1 in single precision. The input is clamped | 
|  | to the range [-c, c]. The value c is chosen as the smallest value where | 
|  | the approximation evaluates to exactly 1. In the reange [-0.0004, 0.0004] | 
|  | the approximation tanh(x) ~= x is used for better accuracy as x tends to zero. | 
|  |  | 
|  | This implementation works on both scalars and packets. | 
|  | */ | 
|  | template<typename T> | 
|  | T generic_fast_tanh_float(const T& a_x) | 
|  | { | 
|  | // Clamp the inputs to the range [-c, c] | 
|  | #ifdef EIGEN_VECTORIZE_FMA | 
|  | const T plus_clamp = pset1<T>(7.99881172180175781f); | 
|  | const T minus_clamp = pset1<T>(-7.99881172180175781f); | 
|  | #else | 
|  | const T plus_clamp = pset1<T>(7.90531110763549805f); | 
|  | const T minus_clamp = pset1<T>(-7.90531110763549805f); | 
|  | #endif | 
|  | const T tiny = pset1<T>(0.0004f); | 
|  | const T x = pmax(pmin(a_x, plus_clamp), minus_clamp); | 
|  | const T tiny_mask = pcmp_lt(pabs(a_x), tiny); | 
|  | // The monomial coefficients of the numerator polynomial (odd). | 
|  | const T alpha_1 = pset1<T>(4.89352455891786e-03f); | 
|  | const T alpha_3 = pset1<T>(6.37261928875436e-04f); | 
|  | const T alpha_5 = pset1<T>(1.48572235717979e-05f); | 
|  | const T alpha_7 = pset1<T>(5.12229709037114e-08f); | 
|  | const T alpha_9 = pset1<T>(-8.60467152213735e-11f); | 
|  | const T alpha_11 = pset1<T>(2.00018790482477e-13f); | 
|  | const T alpha_13 = pset1<T>(-2.76076847742355e-16f); | 
|  |  | 
|  | // The monomial coefficients of the denominator polynomial (even). | 
|  | const T beta_0 = pset1<T>(4.89352518554385e-03f); | 
|  | const T beta_2 = pset1<T>(2.26843463243900e-03f); | 
|  | const T beta_4 = pset1<T>(1.18534705686654e-04f); | 
|  | const T beta_6 = pset1<T>(1.19825839466702e-06f); | 
|  |  | 
|  | // Since the polynomials are odd/even, we need x^2. | 
|  | const T x2 = pmul(x, x); | 
|  |  | 
|  | // Evaluate the numerator polynomial p. | 
|  | T p = pmadd(x2, alpha_13, alpha_11); | 
|  | p = pmadd(x2, p, alpha_9); | 
|  | p = pmadd(x2, p, alpha_7); | 
|  | p = pmadd(x2, p, alpha_5); | 
|  | p = pmadd(x2, p, alpha_3); | 
|  | p = pmadd(x2, p, alpha_1); | 
|  | p = pmul(x, p); | 
|  |  | 
|  | // Evaluate the denominator polynomial q. | 
|  | T q = pmadd(x2, beta_6, beta_4); | 
|  | q = pmadd(x2, q, beta_2); | 
|  | q = pmadd(x2, q, beta_0); | 
|  |  | 
|  | // Divide the numerator by the denominator. | 
|  | return pselect(tiny_mask, x, pdiv(p, q)); | 
|  | } | 
|  |  | 
|  | template<typename RealScalar> | 
|  | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE | 
|  | RealScalar positive_real_hypot(const RealScalar& x, const RealScalar& y) | 
|  | { | 
|  | // IEEE IEC 6059 special cases. | 
|  | if ((numext::isinf)(x) || (numext::isinf)(y)) | 
|  | return NumTraits<RealScalar>::infinity(); | 
|  | if ((numext::isnan)(x) || (numext::isnan)(y)) | 
|  | return NumTraits<RealScalar>::quiet_NaN(); | 
|  |  | 
|  | EIGEN_USING_STD(sqrt); | 
|  | RealScalar p, qp; | 
|  | p = numext::maxi(x,y); | 
|  | if(p==RealScalar(0)) return RealScalar(0); | 
|  | qp = numext::mini(y,x) / p; | 
|  | return p * sqrt(RealScalar(1) + qp*qp); | 
|  | } | 
|  |  | 
|  | template<typename Scalar> | 
|  | struct hypot_impl | 
|  | { | 
|  | typedef typename NumTraits<Scalar>::Real RealScalar; | 
|  | static EIGEN_DEVICE_FUNC | 
|  | inline RealScalar run(const Scalar& x, const Scalar& y) | 
|  | { | 
|  | EIGEN_USING_STD(abs); | 
|  | return positive_real_hypot<RealScalar>(abs(x), abs(y)); | 
|  | } | 
|  | }; | 
|  |  | 
|  | // Generic complex sqrt implementation that correctly handles corner cases | 
|  | // according to https://en.cppreference.com/w/cpp/numeric/complex/sqrt | 
|  | template<typename T> | 
|  | EIGEN_DEVICE_FUNC std::complex<T> complex_sqrt(const std::complex<T>& z) { | 
|  | // Computes the principal sqrt of the input. | 
|  | // | 
|  | // For a complex square root of the number x + i*y. We want to find real | 
|  | // numbers u and v such that | 
|  | //    (u + i*v)^2 = x + i*y  <=> | 
|  | //    u^2 - v^2 + i*2*u*v = x + i*v. | 
|  | // By equating the real and imaginary parts we get: | 
|  | //    u^2 - v^2 = x | 
|  | //    2*u*v = y. | 
|  | // | 
|  | // For x >= 0, this has the numerically stable solution | 
|  | //    u = sqrt(0.5 * (x + sqrt(x^2 + y^2))) | 
|  | //    v = y / (2 * u) | 
|  | // and for x < 0, | 
|  | //    v = sign(y) * sqrt(0.5 * (-x + sqrt(x^2 + y^2))) | 
|  | //    u = y / (2 * v) | 
|  | // | 
|  | // Letting w = sqrt(0.5 * (|x| + |z|)), | 
|  | //   if x == 0: u = w, v = sign(y) * w | 
|  | //   if x > 0:  u = w, v = y / (2 * w) | 
|  | //   if x < 0:  u = |y| / (2 * w), v = sign(y) * w | 
|  |  | 
|  | const T x = numext::real(z); | 
|  | const T y = numext::imag(z); | 
|  | const T zero = T(0); | 
|  | const T w = numext::sqrt(T(0.5) * (numext::abs(x) + numext::hypot(x, y))); | 
|  |  | 
|  | return | 
|  | (numext::isinf)(y) ? std::complex<T>(NumTraits<T>::infinity(), y) | 
|  | : x == zero ? std::complex<T>(w, y < zero ? -w : w) | 
|  | : x > zero ? std::complex<T>(w, y / (2 * w)) | 
|  | : std::complex<T>(numext::abs(y) / (2 * w), y < zero ? -w : w ); | 
|  | } | 
|  |  | 
|  | // Generic complex rsqrt implementation. | 
|  | template<typename T> | 
|  | EIGEN_DEVICE_FUNC std::complex<T> complex_rsqrt(const std::complex<T>& z) { | 
|  | // Computes the principal reciprocal sqrt of the input. | 
|  | // | 
|  | // For a complex reciprocal square root of the number z = x + i*y. We want to | 
|  | // find real numbers u and v such that | 
|  | //    (u + i*v)^2 = 1 / (x + i*y)  <=> | 
|  | //    u^2 - v^2 + i*2*u*v = x/|z|^2 - i*v/|z|^2. | 
|  | // By equating the real and imaginary parts we get: | 
|  | //    u^2 - v^2 = x/|z|^2 | 
|  | //    2*u*v = y/|z|^2. | 
|  | // | 
|  | // For x >= 0, this has the numerically stable solution | 
|  | //    u = sqrt(0.5 * (x + |z|)) / |z| | 
|  | //    v = -y / (2 * u * |z|) | 
|  | // and for x < 0, | 
|  | //    v = -sign(y) * sqrt(0.5 * (-x + |z|)) / |z| | 
|  | //    u = -y / (2 * v * |z|) | 
|  | // | 
|  | // Letting w = sqrt(0.5 * (|x| + |z|)), | 
|  | //   if x == 0: u = w / |z|, v = -sign(y) * w / |z| | 
|  | //   if x > 0:  u = w / |z|, v = -y / (2 * w * |z|) | 
|  | //   if x < 0:  u = |y| / (2 * w * |z|), v = -sign(y) * w / |z| | 
|  |  | 
|  | const T x = numext::real(z); | 
|  | const T y = numext::imag(z); | 
|  | const T zero = T(0); | 
|  |  | 
|  | const T abs_z = numext::hypot(x, y); | 
|  | const T w = numext::sqrt(T(0.5) * (numext::abs(x) + abs_z)); | 
|  | const T woz = w / abs_z; | 
|  | // Corner cases consistent with 1/sqrt(z) on gcc/clang. | 
|  | return | 
|  | abs_z == zero ? std::complex<T>(NumTraits<T>::infinity(), NumTraits<T>::quiet_NaN()) | 
|  | : ((numext::isinf)(x) || (numext::isinf)(y)) ? std::complex<T>(zero, zero) | 
|  | : x == zero ? std::complex<T>(woz, y < zero ? woz : -woz) | 
|  | : x > zero ? std::complex<T>(woz, -y / (2 * w * abs_z)) | 
|  | : std::complex<T>(numext::abs(y) / (2 * w * abs_z), y < zero ? woz : -woz ); | 
|  | } | 
|  |  | 
|  | template<typename T> | 
|  | EIGEN_DEVICE_FUNC std::complex<T> complex_log(const std::complex<T>& z) { | 
|  | // Computes complex log. | 
|  | T a = numext::abs(z); | 
|  | EIGEN_USING_STD(atan2); | 
|  | T b = atan2(z.imag(), z.real()); | 
|  | return std::complex<T>(numext::log(a), b); | 
|  | } | 
|  |  | 
|  | } // end namespace internal | 
|  |  | 
|  | } // end namespace Eigen | 
|  |  | 
|  | #endif // EIGEN_MATHFUNCTIONSIMPL_H |