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https://gitlab.com/libeigen/eigen.git
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6e215cf109
- Split SpecialFunctions files in to a separate BesselFunctions file.
In particular add:
- Modified bessel functions of the second kind k0, k1, k0e, k1e
- Bessel functions of the first kind j0, j1
- Bessel functions of the second kind y0, y1
316 lines
11 KiB
C++
316 lines
11 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) 2016 Eugene Brevdo <ebrevdo@gmail.com>
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// Copyright (C) 2016 Gael Guennebaud <gael.guennebaud@inria.fr>
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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_SPECIALFUNCTIONS_FUNCTORS_H
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#define EIGEN_SPECIALFUNCTIONS_FUNCTORS_H
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namespace Eigen {
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namespace internal {
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/** \internal
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* \brief Template functor to compute the incomplete gamma function igamma(a, x)
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*
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* \sa class CwiseBinaryOp, Cwise::igamma
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*/
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template<typename Scalar> struct scalar_igamma_op : binary_op_base<Scalar,Scalar>
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{
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EIGEN_EMPTY_STRUCT_CTOR(scalar_igamma_op)
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& x) const {
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using numext::igamma; return igamma(a, x);
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}
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template<typename Packet>
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& x) const {
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return internal::pigamma(a, x);
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}
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};
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template<typename Scalar>
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struct functor_traits<scalar_igamma_op<Scalar> > {
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enum {
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// Guesstimate
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Cost = 20 * NumTraits<Scalar>::MulCost + 10 * NumTraits<Scalar>::AddCost,
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PacketAccess = packet_traits<Scalar>::HasIGamma
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};
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};
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/** \internal
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* \brief Template functor to compute the derivative of the incomplete gamma
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* function igamma_der_a(a, x)
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*
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* \sa class CwiseBinaryOp, Cwise::igamma_der_a
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*/
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template <typename Scalar>
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struct scalar_igamma_der_a_op {
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EIGEN_EMPTY_STRUCT_CTOR(scalar_igamma_der_a_op)
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator()(const Scalar& a, const Scalar& x) const {
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using numext::igamma_der_a;
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return igamma_der_a(a, x);
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}
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template <typename Packet>
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& x) const {
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return internal::pigamma_der_a(a, x);
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}
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};
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template <typename Scalar>
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struct functor_traits<scalar_igamma_der_a_op<Scalar> > {
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enum {
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// 2x the cost of igamma
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Cost = 40 * NumTraits<Scalar>::MulCost + 20 * NumTraits<Scalar>::AddCost,
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PacketAccess = packet_traits<Scalar>::HasIGammaDerA
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};
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};
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/** \internal
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* \brief Template functor to compute the derivative of the sample
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* of a Gamma(alpha, 1) random variable with respect to the parameter alpha
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* gamma_sample_der_alpha(alpha, sample)
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*
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* \sa class CwiseBinaryOp, Cwise::gamma_sample_der_alpha
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*/
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template <typename Scalar>
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struct scalar_gamma_sample_der_alpha_op {
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EIGEN_EMPTY_STRUCT_CTOR(scalar_gamma_sample_der_alpha_op)
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator()(const Scalar& alpha, const Scalar& sample) const {
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using numext::gamma_sample_der_alpha;
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return gamma_sample_der_alpha(alpha, sample);
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}
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template <typename Packet>
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& alpha, const Packet& sample) const {
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return internal::pgamma_sample_der_alpha(alpha, sample);
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}
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};
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template <typename Scalar>
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struct functor_traits<scalar_gamma_sample_der_alpha_op<Scalar> > {
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enum {
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// 2x the cost of igamma, minus the lgamma cost (the lgamma cancels out)
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Cost = 30 * NumTraits<Scalar>::MulCost + 15 * NumTraits<Scalar>::AddCost,
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PacketAccess = packet_traits<Scalar>::HasGammaSampleDerAlpha
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};
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};
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/** \internal
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* \brief Template functor to compute the complementary incomplete gamma function igammac(a, x)
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*
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* \sa class CwiseBinaryOp, Cwise::igammac
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*/
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template<typename Scalar> struct scalar_igammac_op : binary_op_base<Scalar,Scalar>
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{
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EIGEN_EMPTY_STRUCT_CTOR(scalar_igammac_op)
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& x) const {
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using numext::igammac; return igammac(a, x);
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}
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template<typename Packet>
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& x) const
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{
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return internal::pigammac(a, x);
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}
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};
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template<typename Scalar>
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struct functor_traits<scalar_igammac_op<Scalar> > {
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enum {
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// Guesstimate
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Cost = 20 * NumTraits<Scalar>::MulCost + 10 * NumTraits<Scalar>::AddCost,
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PacketAccess = packet_traits<Scalar>::HasIGammac
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};
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};
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/** \internal
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* \brief Template functor to compute the incomplete beta integral betainc(a, b, x)
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*
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*/
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template<typename Scalar> struct scalar_betainc_op {
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EIGEN_EMPTY_STRUCT_CTOR(scalar_betainc_op)
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& x, const Scalar& a, const Scalar& b) const {
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using numext::betainc; return betainc(x, a, b);
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}
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template<typename Packet>
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& x, const Packet& a, const Packet& b) const
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{
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return internal::pbetainc(x, a, b);
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}
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};
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template<typename Scalar>
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struct functor_traits<scalar_betainc_op<Scalar> > {
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enum {
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// Guesstimate
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Cost = 400 * NumTraits<Scalar>::MulCost + 400 * NumTraits<Scalar>::AddCost,
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PacketAccess = packet_traits<Scalar>::HasBetaInc
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};
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};
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/** \internal
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* \brief Template functor to compute the natural log of the absolute
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* value of Gamma of a scalar
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* \sa class CwiseUnaryOp, Cwise::lgamma()
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*/
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template<typename Scalar> struct scalar_lgamma_op {
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EIGEN_EMPTY_STRUCT_CTOR(scalar_lgamma_op)
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const {
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using numext::lgamma; return lgamma(a);
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}
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typedef typename packet_traits<Scalar>::type Packet;
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a) const { return internal::plgamma(a); }
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};
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template<typename Scalar>
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struct functor_traits<scalar_lgamma_op<Scalar> >
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{
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enum {
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// Guesstimate
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Cost = 10 * NumTraits<Scalar>::MulCost + 5 * NumTraits<Scalar>::AddCost,
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PacketAccess = packet_traits<Scalar>::HasLGamma
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};
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};
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/** \internal
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* \brief Template functor to compute psi, the derivative of lgamma of a scalar.
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* \sa class CwiseUnaryOp, Cwise::digamma()
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*/
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template<typename Scalar> struct scalar_digamma_op {
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EIGEN_EMPTY_STRUCT_CTOR(scalar_digamma_op)
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const {
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using numext::digamma; return digamma(a);
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}
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typedef typename packet_traits<Scalar>::type Packet;
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a) const { return internal::pdigamma(a); }
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};
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template<typename Scalar>
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struct functor_traits<scalar_digamma_op<Scalar> >
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{
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enum {
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// Guesstimate
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Cost = 10 * NumTraits<Scalar>::MulCost + 5 * NumTraits<Scalar>::AddCost,
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PacketAccess = packet_traits<Scalar>::HasDiGamma
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};
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};
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/** \internal
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* \brief Template functor to compute the Riemann Zeta function of two arguments.
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* \sa class CwiseUnaryOp, Cwise::zeta()
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*/
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template<typename Scalar> struct scalar_zeta_op {
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EIGEN_EMPTY_STRUCT_CTOR(scalar_zeta_op)
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& x, const Scalar& q) const {
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using numext::zeta; return zeta(x, q);
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}
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typedef typename packet_traits<Scalar>::type Packet;
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& x, const Packet& q) const { return internal::pzeta(x, q); }
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};
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template<typename Scalar>
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struct functor_traits<scalar_zeta_op<Scalar> >
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{
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enum {
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// Guesstimate
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Cost = 10 * NumTraits<Scalar>::MulCost + 5 * NumTraits<Scalar>::AddCost,
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PacketAccess = packet_traits<Scalar>::HasZeta
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};
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};
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/** \internal
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* \brief Template functor to compute the polygamma function.
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* \sa class CwiseUnaryOp, Cwise::polygamma()
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*/
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template<typename Scalar> struct scalar_polygamma_op {
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EIGEN_EMPTY_STRUCT_CTOR(scalar_polygamma_op)
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& n, const Scalar& x) const {
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using numext::polygamma; return polygamma(n, x);
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}
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typedef typename packet_traits<Scalar>::type Packet;
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& n, const Packet& x) const { return internal::ppolygamma(n, x); }
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};
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template<typename Scalar>
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struct functor_traits<scalar_polygamma_op<Scalar> >
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{
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enum {
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// Guesstimate
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Cost = 10 * NumTraits<Scalar>::MulCost + 5 * NumTraits<Scalar>::AddCost,
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PacketAccess = packet_traits<Scalar>::HasPolygamma
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};
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};
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/** \internal
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* \brief Template functor to compute the Gauss error function of a
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* scalar
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* \sa class CwiseUnaryOp, Cwise::erf()
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*/
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template<typename Scalar> struct scalar_erf_op {
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EIGEN_EMPTY_STRUCT_CTOR(scalar_erf_op)
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const {
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using numext::erf; return erf(a);
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}
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typedef typename packet_traits<Scalar>::type Packet;
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a) const { return internal::perf(a); }
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};
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template<typename Scalar>
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struct functor_traits<scalar_erf_op<Scalar> >
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{
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enum {
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// Guesstimate
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Cost = 10 * NumTraits<Scalar>::MulCost + 5 * NumTraits<Scalar>::AddCost,
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PacketAccess = packet_traits<Scalar>::HasErf
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};
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};
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/** \internal
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* \brief Template functor to compute the Complementary Error Function
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* of a scalar
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* \sa class CwiseUnaryOp, Cwise::erfc()
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*/
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template<typename Scalar> struct scalar_erfc_op {
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EIGEN_EMPTY_STRUCT_CTOR(scalar_erfc_op)
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const {
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using numext::erfc; return erfc(a);
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}
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typedef typename packet_traits<Scalar>::type Packet;
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a) const { return internal::perfc(a); }
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};
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template<typename Scalar>
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struct functor_traits<scalar_erfc_op<Scalar> >
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{
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enum {
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// Guesstimate
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Cost = 10 * NumTraits<Scalar>::MulCost + 5 * NumTraits<Scalar>::AddCost,
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PacketAccess = packet_traits<Scalar>::HasErfc
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};
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};
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/** \internal
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* \brief Template functor to compute the Inverse of the normal distribution
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* function of a scalar
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* \sa class CwiseUnaryOp, Cwise::ndtri()
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*/
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template<typename Scalar> struct scalar_ndtri_op {
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EIGEN_EMPTY_STRUCT_CTOR(scalar_ndtri_op)
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const {
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using numext::ndtri; return ndtri(a);
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}
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typedef typename packet_traits<Scalar>::type Packet;
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a) const { return internal::pndtri(a); }
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};
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template<typename Scalar>
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struct functor_traits<scalar_ndtri_op<Scalar> >
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{
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enum {
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// On average, We are evaluating rational functions with degree N=9 in the
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// numerator and denominator. This results in 2*N additions and 2*N
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// multiplications.
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Cost = 18 * NumTraits<Scalar>::MulCost + 18 * NumTraits<Scalar>::AddCost,
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PacketAccess = packet_traits<Scalar>::HasNdtri
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};
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};
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} // end namespace internal
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} // end namespace Eigen
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#endif // EIGEN_SPECIALFUNCTIONS_FUNCTORS_H
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