aboutsummaryrefslogtreecommitdiffhomepage
path: root/Eigen
diff options
context:
space:
mode:
authorGravatar Gael Guennebaud <g.gael@free.fr>2013-11-06 10:36:10 +0100
committerGravatar Gael Guennebaud <g.gael@free.fr>2013-11-06 10:36:10 +0100
commit03de5c24102678c5c7ad78a006fd72a247b276ef (patch)
tree3620f2785f1bf2bef089cb3081526ab56f7ebc66 /Eigen
parent4f572e4c14445158bd9e58c2ba651528847053d6 (diff)
Split the huge Functors.h file
Diffstat (limited to 'Eigen')
-rw-r--r--Eigen/Core6
-rw-r--r--Eigen/src/Core/Functors.h1044
-rw-r--r--Eigen/src/Core/functors/BinaryFunctors.h448
-rw-r--r--Eigen/src/Core/functors/NullaryFunctors.h158
-rw-r--r--Eigen/src/Core/functors/StlFunctors.h129
-rw-r--r--Eigen/src/Core/functors/UnaryFunctors.h376
6 files changed, 1116 insertions, 1045 deletions
diff --git a/Eigen/Core b/Eigen/Core
index 4c9c3d297..bf2d3a908 100644
--- a/Eigen/Core
+++ b/Eigen/Core
@@ -301,7 +301,11 @@ using std::ptrdiff_t;
#include "src/Core/arch/Default/Settings.h"
-#include "src/Core/Functors.h"
+#include "src/Core/functors/BinaryFunctors.h"
+#include "src/Core/functors/UnaryFunctors.h"
+#include "src/Core/functors/NullaryFunctors.h"
+#include "src/Core/functors/StlFunctors.h"
+
#include "src/Core/DenseCoeffsBase.h"
#include "src/Core/DenseBase.h"
#include "src/Core/MatrixBase.h"
diff --git a/Eigen/src/Core/Functors.h b/Eigen/src/Core/Functors.h
deleted file mode 100644
index 3d43b528f..000000000
--- a/Eigen/src/Core/Functors.h
+++ /dev/null
@@ -1,1044 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2010 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_FUNCTORS_H
-#define EIGEN_FUNCTORS_H
-
-namespace Eigen {
-
-namespace internal {
-
-// associative functors:
-
-/** \internal
- * \brief Template functor to compute the sum of two scalars
- *
- * \sa class CwiseBinaryOp, MatrixBase::operator+, class VectorwiseOp, DenseBase::sum()
- */
-template<typename Scalar> struct scalar_sum_op {
-// typedef Scalar result_type;
- EIGEN_EMPTY_STRUCT_CTOR(scalar_sum_op)
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { return a + b; }
- template<typename Packet>
- EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
- { return internal::padd(a,b); }
- template<typename Packet>
- EIGEN_STRONG_INLINE const Scalar predux(const Packet& a) const
- { return internal::predux(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_sum_op<Scalar> > {
- enum {
- Cost = NumTraits<Scalar>::AddCost,
- PacketAccess = packet_traits<Scalar>::HasAdd
- };
-};
-
-/** \internal
- * \brief Template specialization to deprecate the summation of boolean expressions.
- * This is required to solve Bug 426.
- * \sa DenseBase::count(), DenseBase::any(), ArrayBase::cast(), MatrixBase::cast()
- */
-template<> struct scalar_sum_op<bool> : scalar_sum_op<int> {
- EIGEN_DEPRECATED
- scalar_sum_op() {}
-};
-
-
-/** \internal
- * \brief Template functor to compute the product of two scalars
- *
- * \sa class CwiseBinaryOp, Cwise::operator*(), class VectorwiseOp, MatrixBase::redux()
- */
-template<typename LhsScalar,typename RhsScalar> struct scalar_product_op {
- enum {
- // TODO vectorize mixed product
- Vectorizable = is_same<LhsScalar,RhsScalar>::value && packet_traits<LhsScalar>::HasMul && packet_traits<RhsScalar>::HasMul
- };
- typedef typename scalar_product_traits<LhsScalar,RhsScalar>::ReturnType result_type;
- EIGEN_EMPTY_STRUCT_CTOR(scalar_product_op)
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const { return a * b; }
- template<typename Packet>
- EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
- { return internal::pmul(a,b); }
- template<typename Packet>
- EIGEN_STRONG_INLINE const result_type predux(const Packet& a) const
- { return internal::predux_mul(a); }
-};
-template<typename LhsScalar,typename RhsScalar>
-struct functor_traits<scalar_product_op<LhsScalar,RhsScalar> > {
- enum {
- Cost = (NumTraits<LhsScalar>::MulCost + NumTraits<RhsScalar>::MulCost)/2, // rough estimate!
- PacketAccess = scalar_product_op<LhsScalar,RhsScalar>::Vectorizable
- };
-};
-
-/** \internal
- * \brief Template functor to compute the conjugate product of two scalars
- *
- * This is a short cut for conj(x) * y which is needed for optimization purpose; in Eigen2 support mode, this becomes x * conj(y)
- */
-template<typename LhsScalar,typename RhsScalar> struct scalar_conj_product_op {
-
- enum {
- Conj = NumTraits<LhsScalar>::IsComplex
- };
-
- typedef typename scalar_product_traits<LhsScalar,RhsScalar>::ReturnType result_type;
-
- EIGEN_EMPTY_STRUCT_CTOR(scalar_conj_product_op)
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const
- { return conj_helper<LhsScalar,RhsScalar,Conj,false>().pmul(a,b); }
-
- template<typename Packet>
- EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
- { return conj_helper<Packet,Packet,Conj,false>().pmul(a,b); }
-};
-template<typename LhsScalar,typename RhsScalar>
-struct functor_traits<scalar_conj_product_op<LhsScalar,RhsScalar> > {
- enum {
- Cost = NumTraits<LhsScalar>::MulCost,
- PacketAccess = internal::is_same<LhsScalar, RhsScalar>::value && packet_traits<LhsScalar>::HasMul
- };
-};
-
-/** \internal
- * \brief Template functor to compute the min of two scalars
- *
- * \sa class CwiseBinaryOp, MatrixBase::cwiseMin, class VectorwiseOp, MatrixBase::minCoeff()
- */
-template<typename Scalar> struct scalar_min_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_min_op)
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { EIGEN_USING_STD_MATH(min); return (min)(a, b); }
- template<typename Packet>
- EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
- { return internal::pmin(a,b); }
- template<typename Packet>
- EIGEN_STRONG_INLINE const Scalar predux(const Packet& a) const
- { return internal::predux_min(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_min_op<Scalar> > {
- enum {
- Cost = NumTraits<Scalar>::AddCost,
- PacketAccess = packet_traits<Scalar>::HasMin
- };
-};
-
-/** \internal
- * \brief Template functor to compute the max of two scalars
- *
- * \sa class CwiseBinaryOp, MatrixBase::cwiseMax, class VectorwiseOp, MatrixBase::maxCoeff()
- */
-template<typename Scalar> struct scalar_max_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_max_op)
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { EIGEN_USING_STD_MATH(max); return (max)(a, b); }
- template<typename Packet>
- EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
- { return internal::pmax(a,b); }
- template<typename Packet>
- EIGEN_STRONG_INLINE const Scalar predux(const Packet& a) const
- { return internal::predux_max(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_max_op<Scalar> > {
- enum {
- Cost = NumTraits<Scalar>::AddCost,
- PacketAccess = packet_traits<Scalar>::HasMax
- };
-};
-
-/** \internal
- * \brief Template functor to compute the hypot of two scalars
- *
- * \sa MatrixBase::stableNorm(), class Redux
- */
-template<typename Scalar> struct scalar_hypot_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_hypot_op)
-// typedef typename NumTraits<Scalar>::Real result_type;
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& _x, const Scalar& _y) const
- {
- EIGEN_USING_STD_MATH(max);
- EIGEN_USING_STD_MATH(min);
- using std::sqrt;
- Scalar p = (max)(_x, _y);
- Scalar q = (min)(_x, _y);
- Scalar qp = q/p;
- return p * sqrt(Scalar(1) + qp*qp);
- }
-};
-template<typename Scalar>
-struct functor_traits<scalar_hypot_op<Scalar> > {
- enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess=0 };
-};
-
-/** \internal
- * \brief Template functor to compute the pow of two scalars
- */
-template<typename Scalar, typename OtherScalar> struct scalar_binary_pow_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_binary_pow_op)
- EIGEN_DEVICE_FUNC
- inline Scalar operator() (const Scalar& a, const OtherScalar& b) const { return numext::pow(a, b); }
-};
-template<typename Scalar, typename OtherScalar>
-struct functor_traits<scalar_binary_pow_op<Scalar,OtherScalar> > {
- enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false };
-};
-
-// other binary functors:
-
-/** \internal
- * \brief Template functor to compute the difference of two scalars
- *
- * \sa class CwiseBinaryOp, MatrixBase::operator-
- */
-template<typename Scalar> struct scalar_difference_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_difference_op)
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { return a - b; }
- template<typename Packet>
- EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
- { return internal::psub(a,b); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_difference_op<Scalar> > {
- enum {
- Cost = NumTraits<Scalar>::AddCost,
- PacketAccess = packet_traits<Scalar>::HasSub
- };
-};
-
-/** \internal
- * \brief Template functor to compute the quotient of two scalars
- *
- * \sa class CwiseBinaryOp, Cwise::operator/()
- */
-template<typename LhsScalar,typename RhsScalar> struct scalar_quotient_op {
- enum {
- // TODO vectorize mixed product
- Vectorizable = is_same<LhsScalar,RhsScalar>::value && packet_traits<LhsScalar>::HasDiv && packet_traits<RhsScalar>::HasDiv
- };
- typedef typename scalar_product_traits<LhsScalar,RhsScalar>::ReturnType result_type;
- EIGEN_EMPTY_STRUCT_CTOR(scalar_quotient_op)
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const { return a / b; }
- template<typename Packet>
- EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
- { return internal::pdiv(a,b); }
-};
-template<typename LhsScalar,typename RhsScalar>
-struct functor_traits<scalar_quotient_op<LhsScalar,RhsScalar> > {
- enum {
- Cost = (NumTraits<LhsScalar>::MulCost + NumTraits<RhsScalar>::MulCost), // rough estimate!
- PacketAccess = scalar_quotient_op<LhsScalar,RhsScalar>::Vectorizable
- };
-};
-
-
-
-/** \internal
- * \brief Template functor to compute the and of two booleans
- *
- * \sa class CwiseBinaryOp, ArrayBase::operator&&
- */
-struct scalar_boolean_and_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_boolean_and_op)
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool operator() (const bool& a, const bool& b) const { return a && b; }
-};
-template<> struct functor_traits<scalar_boolean_and_op> {
- enum {
- Cost = NumTraits<bool>::AddCost,
- PacketAccess = false
- };
-};
-
-/** \internal
- * \brief Template functor to compute the or of two booleans
- *
- * \sa class CwiseBinaryOp, ArrayBase::operator||
- */
-struct scalar_boolean_or_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_boolean_or_op)
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool operator() (const bool& a, const bool& b) const { return a || b; }
-};
-template<> struct functor_traits<scalar_boolean_or_op> {
- enum {
- Cost = NumTraits<bool>::AddCost,
- PacketAccess = false
- };
-};
-
-// unary functors:
-
-/** \internal
- * \brief Template functor to compute the opposite of a scalar
- *
- * \sa class CwiseUnaryOp, MatrixBase::operator-
- */
-template<typename Scalar> struct scalar_opposite_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_opposite_op)
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return -a; }
- template<typename Packet>
- EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
- { return internal::pnegate(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_opposite_op<Scalar> >
-{ enum {
- Cost = NumTraits<Scalar>::AddCost,
- PacketAccess = packet_traits<Scalar>::HasNegate };
-};
-
-/** \internal
- * \brief Template functor to compute the absolute value of a scalar
- *
- * \sa class CwiseUnaryOp, Cwise::abs
- */
-template<typename Scalar> struct scalar_abs_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_abs_op)
- typedef typename NumTraits<Scalar>::Real result_type;
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { using std::abs; return abs(a); }
- template<typename Packet>
- EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
- { return internal::pabs(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_abs_op<Scalar> >
-{
- enum {
- Cost = NumTraits<Scalar>::AddCost,
- PacketAccess = packet_traits<Scalar>::HasAbs
- };
-};
-
-/** \internal
- * \brief Template functor to compute the squared absolute value of a scalar
- *
- * \sa class CwiseUnaryOp, Cwise::abs2
- */
-template<typename Scalar> struct scalar_abs2_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_abs2_op)
- typedef typename NumTraits<Scalar>::Real result_type;
- EIGEN_DEVICE_FUNC
- EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return numext::abs2(a); }
- template<typename Packet>
- EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
- { return internal::pmul(a,a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_abs2_op<Scalar> >
-{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasAbs2 }; };
-
-/** \internal
- * \brief Template functor to compute the conjugate of a complex value
- *
- * \sa class CwiseUnaryOp, MatrixBase::conjugate()
- */
-template<typename Scalar> struct scalar_conjugate_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_conjugate_op)
- EIGEN_DEVICE_FUNC
- EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { using numext::conj; return conj(a); }
- template<typename Packet>
- EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const { return internal::pconj(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_conjugate_op<Scalar> >
-{
- enum {
- Cost = NumTraits<Scalar>::IsComplex ? NumTraits<Scalar>::AddCost : 0,
- PacketAccess = packet_traits<Scalar>::HasConj
- };
-};
-
-/** \internal
- * \brief Template functor to cast a scalar to another type
- *
- * \sa class CwiseUnaryOp, MatrixBase::cast()
- */
-template<typename Scalar, typename NewType>
-struct scalar_cast_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_cast_op)
- typedef NewType result_type;
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const NewType operator() (const Scalar& a) const { return cast<Scalar, NewType>(a); }
-};
-template<typename Scalar, typename NewType>
-struct functor_traits<scalar_cast_op<Scalar,NewType> >
-{ enum { Cost = is_same<Scalar, NewType>::value ? 0 : NumTraits<NewType>::AddCost, PacketAccess = false }; };
-
-/** \internal
- * \brief Template functor to extract the real part of a complex
- *
- * \sa class CwiseUnaryOp, MatrixBase::real()
- */
-template<typename Scalar>
-struct scalar_real_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_real_op)
- typedef typename NumTraits<Scalar>::Real result_type;
- EIGEN_DEVICE_FUNC
- EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return numext::real(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_real_op<Scalar> >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-/** \internal
- * \brief Template functor to extract the imaginary part of a complex
- *
- * \sa class CwiseUnaryOp, MatrixBase::imag()
- */
-template<typename Scalar>
-struct scalar_imag_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_op)
- typedef typename NumTraits<Scalar>::Real result_type;
- EIGEN_DEVICE_FUNC
- EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return numext::imag(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_imag_op<Scalar> >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-/** \internal
- * \brief Template functor to extract the real part of a complex as a reference
- *
- * \sa class CwiseUnaryOp, MatrixBase::real()
- */
-template<typename Scalar>
-struct scalar_real_ref_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_real_ref_op)
- typedef typename NumTraits<Scalar>::Real result_type;
- EIGEN_DEVICE_FUNC
- EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return numext::real_ref(*const_cast<Scalar*>(&a)); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_real_ref_op<Scalar> >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-/** \internal
- * \brief Template functor to extract the imaginary part of a complex as a reference
- *
- * \sa class CwiseUnaryOp, MatrixBase::imag()
- */
-template<typename Scalar>
-struct scalar_imag_ref_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_ref_op)
- typedef typename NumTraits<Scalar>::Real result_type;
- EIGEN_DEVICE_FUNC
- EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return numext::imag_ref(*const_cast<Scalar*>(&a)); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_imag_ref_op<Scalar> >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-/** \internal
- *
- * \brief Template functor to compute the exponential of a scalar
- *
- * \sa class CwiseUnaryOp, Cwise::exp()
- */
-template<typename Scalar> struct scalar_exp_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_exp_op)
- EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { using std::exp; return exp(a); }
- typedef typename packet_traits<Scalar>::type Packet;
- inline Packet packetOp(const Packet& a) const { return internal::pexp(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_exp_op<Scalar> >
-{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasExp }; };
-
-/** \internal
- *
- * \brief Template functor to compute the logarithm of a scalar
- *
- * \sa class CwiseUnaryOp, Cwise::log()
- */
-template<typename Scalar> struct scalar_log_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_log_op)
- EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { using std::log; return log(a); }
- typedef typename packet_traits<Scalar>::type Packet;
- inline Packet packetOp(const Packet& a) const { return internal::plog(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_log_op<Scalar> >
-{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasLog }; };
-
-/** \internal
- * \brief Template functor to multiply a scalar by a fixed other one
- *
- * \sa class CwiseUnaryOp, MatrixBase::operator*, MatrixBase::operator/
- */
-/* NOTE why doing the pset1() in packetOp *is* an optimization ?
- * indeed it seems better to declare m_other as a Packet and do the pset1() once
- * in the constructor. However, in practice:
- * - GCC does not like m_other as a Packet and generate a load every time it needs it
- * - on the other hand GCC is able to moves the pset1() outside the loop :)
- * - simpler code ;)
- * (ICC and gcc 4.4 seems to perform well in both cases, the issue is visible with y = a*x + b*y)
- */
-template<typename Scalar>
-struct scalar_multiple_op {
- typedef typename packet_traits<Scalar>::type Packet;
- // FIXME default copy constructors seems bugged with std::complex<>
- EIGEN_DEVICE_FUNC
- EIGEN_STRONG_INLINE scalar_multiple_op(const scalar_multiple_op& other) : m_other(other.m_other) { }
- EIGEN_DEVICE_FUNC
- EIGEN_STRONG_INLINE scalar_multiple_op(const Scalar& other) : m_other(other) { }
- EIGEN_DEVICE_FUNC
- EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a * m_other; }
- EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
- { return internal::pmul(a, pset1<Packet>(m_other)); }
- typename add_const_on_value_type<typename NumTraits<Scalar>::Nested>::type m_other;
-};
-template<typename Scalar>
-struct functor_traits<scalar_multiple_op<Scalar> >
-{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
-
-template<typename Scalar1, typename Scalar2>
-struct scalar_multiple2_op {
- typedef typename scalar_product_traits<Scalar1,Scalar2>::ReturnType result_type;
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE scalar_multiple2_op(const scalar_multiple2_op& other) : m_other(other.m_other) { }
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE scalar_multiple2_op(const Scalar2& other) : m_other(other) { }
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE result_type operator() (const Scalar1& a) const { return a * m_other; }
- typename add_const_on_value_type<typename NumTraits<Scalar2>::Nested>::type m_other;
-};
-template<typename Scalar1,typename Scalar2>
-struct functor_traits<scalar_multiple2_op<Scalar1,Scalar2> >
-{ enum { Cost = NumTraits<Scalar1>::MulCost, PacketAccess = false }; };
-
-/** \internal
- * \brief Template functor to divide a scalar by a fixed other one
- *
- * This functor is used to implement the quotient of a matrix by
- * a scalar where the scalar type is not necessarily a floating point type.
- *
- * \sa class CwiseUnaryOp, MatrixBase::operator/
- */
-template<typename Scalar>
-struct scalar_quotient1_op {
- typedef typename packet_traits<Scalar>::type Packet;
- // FIXME default copy constructors seems bugged with std::complex<>
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE scalar_quotient1_op(const scalar_quotient1_op& other) : m_other(other.m_other) { }
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE scalar_quotient1_op(const Scalar& other) : m_other(other) {}
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a / m_other; }
- EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
- { return internal::pdiv(a, pset1<Packet>(m_other)); }
- typename add_const_on_value_type<typename NumTraits<Scalar>::Nested>::type m_other;
-};
-template<typename Scalar>
-struct functor_traits<scalar_quotient1_op<Scalar> >
-{ enum { Cost = 2 * NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasDiv }; };
-
-// nullary functors
-
-template<typename Scalar>
-struct scalar_constant_op {
- typedef typename packet_traits<Scalar>::type Packet;
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE scalar_constant_op(const scalar_constant_op& other) : m_other(other.m_other) { }
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE scalar_constant_op(const Scalar& other) : m_other(other) { }
- template<typename Index>
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (Index, Index = 0) const { return m_other; }
- template<typename Index>
- EIGEN_STRONG_INLINE const Packet packetOp(Index, Index = 0) const { return internal::pset1<Packet>(m_other); }
- const Scalar m_other;
-};
-template<typename Scalar>
-struct functor_traits<scalar_constant_op<Scalar> >
-// FIXME replace this packet test by a safe one
-{ enum { Cost = 1, PacketAccess = packet_traits<Scalar>::Vectorizable, IsRepeatable = true }; };
-
-template<typename Scalar> struct scalar_identity_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_identity_op)
- template<typename Index>
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (Index row, Index col) const { return row==col ? Scalar(1) : Scalar(0); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_identity_op<Scalar> >
-{ enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = false, IsRepeatable = true }; };
-
-template <typename Scalar, bool RandomAccess> struct linspaced_op_impl;
-
-// linear access for packet ops:
-// 1) initialization
-// base = [low, ..., low] + ([step, ..., step] * [-size, ..., 0])
-// 2) each step (where size is 1 for coeff access or PacketSize for packet access)
-// base += [size*step, ..., size*step]
-//
-// TODO: Perhaps it's better to initialize lazily (so not in the constructor but in packetOp)
-// in order to avoid the padd() in operator() ?
-template <typename Scalar>
-struct linspaced_op_impl<Scalar,false>
-{
- typedef typename packet_traits<Scalar>::type Packet;
-
- linspaced_op_impl(const Scalar& low, const Scalar& step) :
- m_low(low), m_step(step),
- m_packetStep(pset1<Packet>(packet_traits<Scalar>::size*step)),
- m_base(padd(pset1<Packet>(low), pmul(pset1<Packet>(step),plset<Scalar>(-packet_traits<Scalar>::size)))) {}
-
- template<typename Index>
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (Index i) const
- {
- m_base = padd(m_base, pset1<Packet>(m_step));
- return m_low+Scalar(i)*m_step;
- }
-
- template<typename Index>
- EIGEN_STRONG_INLINE const Packet packetOp(Index) const { return m_base = padd(m_base,m_packetStep); }
-
- const Scalar m_low;
- const Scalar m_step;
- const Packet m_packetStep;
- mutable Packet m_base;
-};
-
-// random access for packet ops:
-// 1) each step
-// [low, ..., low] + ( [step, ..., step] * ( [i, ..., i] + [0, ..., size] ) )
-template <typename Scalar>
-struct linspaced_op_impl<Scalar,true>
-{
- typedef typename packet_traits<Scalar>::type Packet;
-
- linspaced_op_impl(const Scalar& low, const Scalar& step) :
- m_low(low), m_step(step),
- m_lowPacket(pset1<Packet>(m_low)), m_stepPacket(pset1<Packet>(m_step)), m_interPacket(plset<Scalar>(0)) {}
-
- template<typename Index>
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return m_low+i*m_step; }
-
- template<typename Index>
- EIGEN_STRONG_INLINE const Packet packetOp(Index i) const
- { return internal::padd(m_lowPacket, pmul(m_stepPacket, padd(pset1<Packet>(i),m_interPacket))); }
-
- const Scalar m_low;
- const Scalar m_step;
- const Packet m_lowPacket;
- const Packet m_stepPacket;
- const Packet m_interPacket;
-};
-
-// ----- Linspace functor ----------------------------------------------------------------
-
-// Forward declaration (we default to random access which does not really give
-// us a speed gain when using packet access but it allows to use the functor in
-// nested expressions).
-template <typename Scalar, bool RandomAccess = true> struct linspaced_op;
-template <typename Scalar, bool RandomAccess> struct functor_traits< linspaced_op<Scalar,RandomAccess> >
-{ enum { Cost = 1, PacketAccess = packet_traits<Scalar>::HasSetLinear, IsRepeatable = true }; };
-template <typename Scalar, bool RandomAccess> struct linspaced_op
-{
- typedef typename packet_traits<Scalar>::type Packet;
- linspaced_op(const Scalar& low, const Scalar& high, DenseIndex num_steps) : impl((num_steps==1 ? high : low), (num_steps==1 ? Scalar() : (high-low)/(num_steps-1))) {}
-
- template<typename Index>
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return impl(i); }
-
- // We need this function when assigning e.g. a RowVectorXd to a MatrixXd since
- // there row==0 and col is used for the actual iteration.
- template<typename Index>
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (Index row, Index col) const
- {
- eigen_assert(col==0 || row==0);
- return impl(col + row);
- }
-
- template<typename Index>
- EIGEN_STRONG_INLINE const Packet packetOp(Index i) const { return impl.packetOp(i); }
-
- // We need this function when assigning e.g. a RowVectorXd to a MatrixXd since
- // there row==0 and col is used for the actual iteration.
- template<typename Index>
- EIGEN_STRONG_INLINE const Packet packetOp(Index row, Index col) const
- {
- eigen_assert(col==0 || row==0);
- return impl.packetOp(col + row);
- }
-
- // This proxy object handles the actual required temporaries, the different
- // implementations (random vs. sequential access) as well as the
- // correct piping to size 2/4 packet operations.
- const linspaced_op_impl<Scalar,RandomAccess> impl;
-};
-
-// all functors allow linear access, except scalar_identity_op. So we fix here a quick meta
-// to indicate whether a functor allows linear access, just always answering 'yes' except for
-// scalar_identity_op.
-// FIXME move this to functor_traits adding a functor_default
-template<typename Functor> struct functor_has_linear_access { enum { ret = 1 }; };
-template<typename Scalar> struct functor_has_linear_access<scalar_identity_op<Scalar> > { enum { ret = 0 }; };
-
-// In Eigen, any binary op (Product, CwiseBinaryOp) require the Lhs and Rhs to have the same scalar type, except for multiplication
-// where the mixing of different types is handled by scalar_product_traits
-// In particular, real * complex<real> is allowed.
-// FIXME move this to functor_traits adding a functor_default
-template<typename Functor> struct functor_is_product_like { enum { ret = 0 }; };
-template<typename LhsScalar,typename RhsScalar> struct functor_is_product_like<scalar_product_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
-template<typename LhsScalar,typename RhsScalar> struct functor_is_product_like<scalar_conj_product_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
-template<typename LhsScalar,typename RhsScalar> struct functor_is_product_like<scalar_quotient_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
-
-
-/** \internal
- * \brief Template functor to add a scalar to a fixed other one
- * \sa class CwiseUnaryOp, Array::operator+
- */
-/* If you wonder why doing the pset1() in packetOp() is an optimization check scalar_multiple_op */
-template<typename Scalar>
-struct scalar_add_op {
- typedef typename packet_traits<Scalar>::type Packet;
- // FIXME default copy constructors seems bugged with std::complex<>
- EIGEN_DEVICE_FUNC inline scalar_add_op(const scalar_add_op& other) : m_other(other.m_other) { }
- EIGEN_DEVICE_FUNC inline scalar_add_op(const Scalar& other) : m_other(other) { }
- EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { return a + m_other; }
- inline const Packet packetOp(const Packet& a) const
- { return internal::padd(a, pset1<Packet>(m_other)); }
- const Scalar m_other;
-};
-template<typename Scalar>
-struct functor_traits<scalar_add_op<Scalar> >
-{ enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = packet_traits<Scalar>::HasAdd }; };
-
-/** \internal
- * \brief Template functor to subtract a fixed scalar to another one
- * \sa class CwiseUnaryOp, Array::operator-, struct scalar_add_op, struct scalar_rsub_op
- */
-template<typename Scalar>
-struct scalar_sub_op {
- typedef typename packet_traits<Scalar>::type Packet;
- inline scalar_sub_op(const scalar_sub_op& other) : m_other(other.m_other) { }
- inline scalar_sub_op(const Scalar& other) : m_other(other) { }
- inline Scalar operator() (const Scalar& a) const { return a - m_other; }
- inline const Packet packetOp(const Packet& a) const
- { return internal::psub(a, pset1<Packet>(m_other)); }
- const Scalar m_other;
-};
-template<typename Scalar>
-struct functor_traits<scalar_sub_op<Scalar> >
-{ enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = packet_traits<Scalar>::HasAdd }; };
-
-/** \internal
- * \brief Template functor to subtract a scalar to fixed another one
- * \sa class CwiseUnaryOp, Array::operator-, struct scalar_add_op, struct scalar_sub_op
- */
-template<typename Scalar>
-struct scalar_rsub_op {
- typedef typename packet_traits<Scalar>::type Packet;
- inline scalar_rsub_op(const scalar_rsub_op& other) : m_other(other.m_other) { }
- inline scalar_rsub_op(const Scalar& other) : m_other(other) { }
- inline Scalar operator() (const Scalar& a) const { return m_other - a; }
- inline const Packet packetOp(const Packet& a) const
- { return internal::psub(pset1<Packet>(m_other), a); }
- const Scalar m_other;
-};
-template<typename Scalar>
-struct functor_traits<scalar_rsub_op<Scalar> >
-{ enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = packet_traits<Scalar>::HasAdd }; };
-
-/** \internal
- * \brief Template functor to compute the square root of a scalar
- * \sa class CwiseUnaryOp, Cwise::sqrt()
- */
-template<typename Scalar> struct scalar_sqrt_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_sqrt_op)
- EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { using std::sqrt; return sqrt(a); }
- typedef typename packet_traits<Scalar>::type Packet;
- inline Packet packetOp(const Packet& a) const { return internal::psqrt(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_sqrt_op<Scalar> >
-{ enum {
- Cost = 5 * NumTraits<Scalar>::MulCost,
- PacketAccess = packet_traits<Scalar>::HasSqrt
- };
-};
-
-/** \internal
- * \brief Template functor to compute the cosine of a scalar
- * \sa class CwiseUnaryOp, ArrayBase::cos()
- */
-template<typename Scalar> struct scalar_cos_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_cos_op)
- EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { using std::cos; return cos(a); }
- typedef typename packet_traits<Scalar>::type Packet;
- inline Packet packetOp(const Packet& a) const { return internal::pcos(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_cos_op<Scalar> >
-{
- enum {
- Cost = 5 * NumTraits<Scalar>::MulCost,
- PacketAccess = packet_traits<Scalar>::HasCos
- };
-};
-
-/** \internal
- * \brief Template functor to compute the sine of a scalar
- * \sa class CwiseUnaryOp, ArrayBase::sin()
- */
-template<typename Scalar> struct scalar_sin_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_sin_op)
- EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { using std::sin; return sin(a); }
- typedef typename packet_traits<Scalar>::type Packet;
- inline Packet packetOp(const Packet& a) const { return internal::psin(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_sin_op<Scalar> >
-{
- enum {
- Cost = 5 * NumTraits<Scalar>::MulCost,
- PacketAccess = packet_traits<Scalar>::HasSin
- };
-};
-
-
-/** \internal
- * \brief Template functor to compute the tan of a scalar
- * \sa class CwiseUnaryOp, ArrayBase::tan()
- */
-template<typename Scalar> struct scalar_tan_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_tan_op)
- EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { using std::tan; return tan(a); }
- typedef typename packet_traits<Scalar>::type Packet;
- inline Packet packetOp(const Packet& a) const { return internal::ptan(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_tan_op<Scalar> >
-{
- enum {
- Cost = 5 * NumTraits<Scalar>::MulCost,
- PacketAccess = packet_traits<Scalar>::HasTan
- };
-};
-
-/** \internal
- * \brief Template functor to compute the arc cosine of a scalar
- * \sa class CwiseUnaryOp, ArrayBase::acos()
- */
-template<typename Scalar> struct scalar_acos_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_acos_op)
- EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { using std::acos; return acos(a); }
- typedef typename packet_traits<Scalar>::type Packet;
- inline Packet packetOp(const Packet& a) const { return internal::pacos(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_acos_op<Scalar> >
-{
- enum {
- Cost = 5 * NumTraits<Scalar>::MulCost,
- PacketAccess = packet_traits<Scalar>::HasACos
- };
-};
-
-/** \internal
- * \brief Template functor to compute the arc sine of a scalar
- * \sa class CwiseUnaryOp, ArrayBase::asin()
- */
-template<typename Scalar> struct scalar_asin_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_asin_op)
- EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { using std::asin; return asin(a); }
- typedef typename packet_traits<Scalar>::type Packet;
- inline Packet packetOp(const Packet& a) const { return internal::pasin(a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_asin_op<Scalar> >
-{
- enum {
- Cost = 5 * NumTraits<Scalar>::MulCost,
- PacketAccess = packet_traits<Scalar>::HasASin
- };
-};
-
-/** \internal
- * \brief Template functor to raise a scalar to a power
- * \sa class CwiseUnaryOp, Cwise::pow
- */
-template<typename Scalar>
-struct scalar_pow_op {
- // FIXME default copy constructors seems bugged with std::complex<>
- inline scalar_pow_op(const scalar_pow_op& other) : m_exponent(other.m_exponent) { }
- inline scalar_pow_op(const Scalar& exponent) : m_exponent(exponent) {}
- EIGEN_DEVICE_FUNC
- inline Scalar operator() (const Scalar& a) const { return numext::pow(a, m_exponent); }
- const Scalar m_exponent;
-};
-template<typename Scalar>
-struct functor_traits<scalar_pow_op<Scalar> >
-{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false }; };
-
-/** \internal
- * \brief Template functor to compute the quotient between a scalar and array entries.
- * \sa class CwiseUnaryOp, Cwise::inverse()
- */
-template<typename Scalar>
-struct scalar_inverse_mult_op {
- scalar_inverse_mult_op(const Scalar& other) : m_other(other) {}
- EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { return m_other / a; }
- template<typename Packet>
- inline const Packet packetOp(const Packet& a) const
- { return internal::pdiv(pset1<Packet>(m_other),a); }
- Scalar m_other;
-};
-
-/** \internal
- * \brief Template functor to compute the inverse of a scalar
- * \sa class CwiseUnaryOp, Cwise::inverse()
- */
-template<typename Scalar>
-struct scalar_inverse_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_inverse_op)
- EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { return Scalar(1)/a; }
- template<typename Packet>
- inline const Packet packetOp(const Packet& a) const
- { return internal::pdiv(pset1<Packet>(Scalar(1)),a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_inverse_op<Scalar> >
-{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasDiv }; };
-
-/** \internal
- * \brief Template functor to compute the square of a scalar
- * \sa class CwiseUnaryOp, Cwise::square()
- */
-template<typename Scalar>
-struct scalar_square_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_square_op)
- EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { return a*a; }
- template<typename Packet>
- inline const Packet packetOp(const Packet& a) const
- { return internal::pmul(a,a); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_square_op<Scalar> >
-{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
-
-/** \internal
- * \brief Template functor to compute the cube of a scalar
- * \sa class CwiseUnaryOp, Cwise::cube()
- */
-template<typename Scalar>
-struct scalar_cube_op {
- EIGEN_EMPTY_STRUCT_CTOR(scalar_cube_op)
- EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { return a*a*a; }
- template<typename Packet>
- inline const Packet packetOp(const Packet& a) const
- { return internal::pmul(a,pmul(a,a)); }
-};
-template<typename Scalar>
-struct functor_traits<scalar_cube_op<Scalar> >
-{ enum { Cost = 2*NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
-
-// default functor traits for STL functors:
-
-template<typename T>
-struct functor_traits<std::multiplies<T> >
-{ enum { Cost = NumTraits<T>::MulCost, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::divides<T> >
-{ enum { Cost = NumTraits<T>::MulCost, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::plus<T> >
-{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::minus<T> >
-{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::negate<T> >
-{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::logical_or<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::logical_and<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::logical_not<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::greater<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::less<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::greater_equal<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::less_equal<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::equal_to<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::not_equal_to<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::binder2nd<T> >
-{ enum { Cost = functor_traits<T>::Cost, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::binder1st<T> >
-{ enum { Cost = functor_traits<T>::Cost, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::unary_negate<T> >
-{ enum { Cost = 1 + functor_traits<T>::Cost, PacketAccess = false }; };
-
-template<typename T>
-struct functor_traits<std::binary_negate<T> >
-{ enum { Cost = 1 + functor_traits<T>::Cost, PacketAccess = false }; };
-
-#ifdef EIGEN_STDEXT_SUPPORT
-
-template<typename T0,typename T1>
-struct functor_traits<std::project1st<T0,T1> >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-template<typename T0,typename T1>
-struct functor_traits<std::project2nd<T0,T1> >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-template<typename T0,typename T1>
-struct functor_traits<std::select2nd<std::pair<T0,T1> > >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-template<typename T0,typename T1>
-struct functor_traits<std::select1st<std::pair<T0,T1> > >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-template<typename T0,typename T1>
-struct functor_traits<std::unary_compose<T0,T1> >
-{ enum { Cost = functor_traits<T0>::Cost + functor_traits<T1>::Cost, PacketAccess = false }; };
-
-template<typename T0,typename T1,typename T2>
-struct functor_traits<std::binary_compose<T0,T1,T2> >
-{ enum { Cost = functor_traits<T0>::Cost + functor_traits<T1>::Cost + functor_traits<T2>::Cost, PacketAccess = false }; };
-
-#endif // EIGEN_STDEXT_SUPPORT
-
-// allow to add new functors and specializations of functor_traits from outside Eigen.
-// this macro is really needed because functor_traits must be specialized after it is declared but before it is used...
-#ifdef EIGEN_FUNCTORS_PLUGIN
-#include EIGEN_FUNCTORS_PLUGIN
-#endif
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_FUNCTORS_H
diff --git a/Eigen/src/Core/functors/BinaryFunctors.h b/Eigen/src/Core/functors/BinaryFunctors.h
new file mode 100644
index 000000000..ba094f5d1
--- /dev/null
+++ b/Eigen/src/Core/functors/BinaryFunctors.h
@@ -0,0 +1,448 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2010 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_BINARY_FUNCTORS_H
+#define EIGEN_BINARY_FUNCTORS_H
+
+namespace Eigen {
+
+namespace internal {
+
+//---------- associative binary functors ----------
+
+/** \internal
+ * \brief Template functor to compute the sum of two scalars
+ *
+ * \sa class CwiseBinaryOp, MatrixBase::operator+, class VectorwiseOp, DenseBase::sum()
+ */
+template<typename Scalar> struct scalar_sum_op {
+// typedef Scalar result_type;
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_sum_op)
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { return a + b; }
+ template<typename Packet>
+ EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
+ { return internal::padd(a,b); }
+ template<typename Packet>
+ EIGEN_STRONG_INLINE const Scalar predux(const Packet& a) const
+ { return internal::predux(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_sum_op<Scalar> > {
+ enum {
+ Cost = NumTraits<Scalar>::AddCost,
+ PacketAccess = packet_traits<Scalar>::HasAdd
+ };
+};
+
+/** \internal
+ * \brief Template specialization to deprecate the summation of boolean expressions.
+ * This is required to solve Bug 426.
+ * \sa DenseBase::count(), DenseBase::any(), ArrayBase::cast(), MatrixBase::cast()
+ */
+template<> struct scalar_sum_op<bool> : scalar_sum_op<int> {
+ EIGEN_DEPRECATED
+ scalar_sum_op() {}
+};
+
+
+/** \internal
+ * \brief Template functor to compute the product of two scalars
+ *
+ * \sa class CwiseBinaryOp, Cwise::operator*(), class VectorwiseOp, MatrixBase::redux()
+ */
+template<typename LhsScalar,typename RhsScalar> struct scalar_product_op {
+ enum {
+ // TODO vectorize mixed product
+ Vectorizable = is_same<LhsScalar,RhsScalar>::value && packet_traits<LhsScalar>::HasMul && packet_traits<RhsScalar>::HasMul
+ };
+ typedef typename scalar_product_traits<LhsScalar,RhsScalar>::ReturnType result_type;
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_product_op)
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const { return a * b; }
+ template<typename Packet>
+ EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
+ { return internal::pmul(a,b); }
+ template<typename Packet>
+ EIGEN_STRONG_INLINE const result_type predux(const Packet& a) const
+ { return internal::predux_mul(a); }
+};
+template<typename LhsScalar,typename RhsScalar>
+struct functor_traits<scalar_product_op<LhsScalar,RhsScalar> > {
+ enum {
+ Cost = (NumTraits<LhsScalar>::MulCost + NumTraits<RhsScalar>::MulCost)/2, // rough estimate!
+ PacketAccess = scalar_product_op<LhsScalar,RhsScalar>::Vectorizable
+ };
+};
+
+/** \internal
+ * \brief Template functor to compute the conjugate product of two scalars
+ *
+ * This is a short cut for conj(x) * y which is needed for optimization purpose; in Eigen2 support mode, this becomes x * conj(y)
+ */
+template<typename LhsScalar,typename RhsScalar> struct scalar_conj_product_op {
+
+ enum {
+ Conj = NumTraits<LhsScalar>::IsComplex
+ };
+
+ typedef typename scalar_product_traits<LhsScalar,RhsScalar>::ReturnType result_type;
+
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_conj_product_op)
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const
+ { return conj_helper<LhsScalar,RhsScalar,Conj,false>().pmul(a,b); }
+
+ template<typename Packet>
+ EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
+ { return conj_helper<Packet,Packet,Conj,false>().pmul(a,b); }
+};
+template<typename LhsScalar,typename RhsScalar>
+struct functor_traits<scalar_conj_product_op<LhsScalar,RhsScalar> > {
+ enum {
+ Cost = NumTraits<LhsScalar>::MulCost,
+ PacketAccess = internal::is_same<LhsScalar, RhsScalar>::value && packet_traits<LhsScalar>::HasMul
+ };
+};
+
+/** \internal
+ * \brief Template functor to compute the min of two scalars
+ *
+ * \sa class CwiseBinaryOp, MatrixBase::cwiseMin, class VectorwiseOp, MatrixBase::minCoeff()
+ */
+template<typename Scalar> struct scalar_min_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_min_op)
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { EIGEN_USING_STD_MATH(min); return (min)(a, b); }
+ template<typename Packet>
+ EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
+ { return internal::pmin(a,b); }
+ template<typename Packet>
+ EIGEN_STRONG_INLINE const Scalar predux(const Packet& a) const
+ { return internal::predux_min(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_min_op<Scalar> > {
+ enum {
+ Cost = NumTraits<Scalar>::AddCost,
+ PacketAccess = packet_traits<Scalar>::HasMin
+ };
+};
+
+/** \internal
+ * \brief Template functor to compute the max of two scalars
+ *
+ * \sa class CwiseBinaryOp, MatrixBase::cwiseMax, class VectorwiseOp, MatrixBase::maxCoeff()
+ */
+template<typename Scalar> struct scalar_max_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_max_op)
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { EIGEN_USING_STD_MATH(max); return (max)(a, b); }
+ template<typename Packet>
+ EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
+ { return internal::pmax(a,b); }
+ template<typename Packet>
+ EIGEN_STRONG_INLINE const Scalar predux(const Packet& a) const
+ { return internal::predux_max(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_max_op<Scalar> > {
+ enum {
+ Cost = NumTraits<Scalar>::AddCost,
+ PacketAccess = packet_traits<Scalar>::HasMax
+ };
+};
+
+/** \internal
+ * \brief Template functor to compute the hypot of two scalars
+ *
+ * \sa MatrixBase::stableNorm(), class Redux
+ */
+template<typename Scalar> struct scalar_hypot_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_hypot_op)
+// typedef typename NumTraits<Scalar>::Real result_type;
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& _x, const Scalar& _y) const
+ {
+ EIGEN_USING_STD_MATH(max);
+ EIGEN_USING_STD_MATH(min);
+ using std::sqrt;
+ Scalar p = (max)(_x, _y);
+ Scalar q = (min)(_x, _y);
+ Scalar qp = q/p;
+ return p * sqrt(Scalar(1) + qp*qp);
+ }
+};
+template<typename Scalar>
+struct functor_traits<scalar_hypot_op<Scalar> > {
+ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess=0 };
+};
+
+/** \internal
+ * \brief Template functor to compute the pow of two scalars
+ */
+template<typename Scalar, typename OtherScalar> struct scalar_binary_pow_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_binary_pow_op)
+ EIGEN_DEVICE_FUNC
+ inline Scalar operator() (const Scalar& a, const OtherScalar& b) const { return numext::pow(a, b); }
+};
+template<typename Scalar, typename OtherScalar>
+struct functor_traits<scalar_binary_pow_op<Scalar,OtherScalar> > {
+ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false };
+};
+
+
+
+//---------- non associative binary functors ----------
+
+/** \internal
+ * \brief Template functor to compute the difference of two scalars
+ *
+ * \sa class CwiseBinaryOp, MatrixBase::operator-
+ */
+template<typename Scalar> struct scalar_difference_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_difference_op)
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { return a - b; }
+ template<typename Packet>
+ EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
+ { return internal::psub(a,b); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_difference_op<Scalar> > {
+ enum {
+ Cost = NumTraits<Scalar>::AddCost,
+ PacketAccess = packet_traits<Scalar>::HasSub
+ };
+};
+
+/** \internal
+ * \brief Template functor to compute the quotient of two scalars
+ *
+ * \sa class CwiseBinaryOp, Cwise::operator/()
+ */
+template<typename LhsScalar,typename RhsScalar> struct scalar_quotient_op {
+ enum {
+ // TODO vectorize mixed product
+ Vectorizable = is_same<LhsScalar,RhsScalar>::value && packet_traits<LhsScalar>::HasDiv && packet_traits<RhsScalar>::HasDiv
+ };
+ typedef typename scalar_product_traits<LhsScalar,RhsScalar>::ReturnType result_type;
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_quotient_op)
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const { return a / b; }
+ template<typename Packet>
+ EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
+ { return internal::pdiv(a,b); }
+};
+template<typename LhsScalar,typename RhsScalar>
+struct functor_traits<scalar_quotient_op<LhsScalar,RhsScalar> > {
+ enum {
+ Cost = (NumTraits<LhsScalar>::MulCost + NumTraits<RhsScalar>::MulCost), // rough estimate!
+ PacketAccess = scalar_quotient_op<LhsScalar,RhsScalar>::Vectorizable
+ };
+};
+
+
+
+/** \internal
+ * \brief Template functor to compute the and of two booleans
+ *
+ * \sa class CwiseBinaryOp, ArrayBase::operator&&
+ */
+struct scalar_boolean_and_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_boolean_and_op)
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool operator() (const bool& a, const bool& b) const { return a && b; }
+};
+template<> struct functor_traits<scalar_boolean_and_op> {
+ enum {
+ Cost = NumTraits<bool>::AddCost,
+ PacketAccess = false
+ };
+};
+
+/** \internal
+ * \brief Template functor to compute the or of two booleans
+ *
+ * \sa class CwiseBinaryOp, ArrayBase::operator||
+ */
+struct scalar_boolean_or_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_boolean_or_op)
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool operator() (const bool& a, const bool& b) const { return a || b; }
+};
+template<> struct functor_traits<scalar_boolean_or_op> {
+ enum {
+ Cost = NumTraits<bool>::AddCost,
+ PacketAccess = false
+ };
+};
+
+
+
+//---------- binary functors bound to a constant, thus appearing as a unary functor ----------
+
+/** \internal
+ * \brief Template functor to multiply a scalar by a fixed other one
+ *
+ * \sa class CwiseUnaryOp, MatrixBase::operator*, MatrixBase::operator/
+ */
+/* NOTE why doing the pset1() in packetOp *is* an optimization ?
+ * indeed it seems better to declare m_other as a Packet and do the pset1() once
+ * in the constructor. However, in practice:
+ * - GCC does not like m_other as a Packet and generate a load every time it needs it
+ * - on the other hand GCC is able to moves the pset1() outside the loop :)
+ * - simpler code ;)
+ * (ICC and gcc 4.4 seems to perform well in both cases, the issue is visible with y = a*x + b*y)
+ */
+template<typename Scalar>
+struct scalar_multiple_op {
+ typedef typename packet_traits<Scalar>::type Packet;
+ // FIXME default copy constructors seems bugged with std::complex<>
+ EIGEN_DEVICE_FUNC
+ EIGEN_STRONG_INLINE scalar_multiple_op(const scalar_multiple_op& other) : m_other(other.m_other) { }
+ EIGEN_DEVICE_FUNC
+ EIGEN_STRONG_INLINE scalar_multiple_op(const Scalar& other) : m_other(other) { }
+ EIGEN_DEVICE_FUNC
+ EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a * m_other; }
+ EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
+ { return internal::pmul(a, pset1<Packet>(m_other)); }
+ typename add_const_on_value_type<typename NumTraits<Scalar>::Nested>::type m_other;
+};
+template<typename Scalar>
+struct functor_traits<scalar_multiple_op<Scalar> >
+{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
+
+template<typename Scalar1, typename Scalar2>
+struct scalar_multiple2_op {
+ typedef typename scalar_product_traits<Scalar1,Scalar2>::ReturnType result_type;
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE scalar_multiple2_op(const scalar_multiple2_op& other) : m_other(other.m_other) { }
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE scalar_multiple2_op(const Scalar2& other) : m_other(other) { }
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE result_type operator() (const Scalar1& a) const { return a * m_other; }
+ typename add_const_on_value_type<typename NumTraits<Scalar2>::Nested>::type m_other;
+};
+template<typename Scalar1,typename Scalar2>
+struct functor_traits<scalar_multiple2_op<Scalar1,Scalar2> >
+{ enum { Cost = NumTraits<Scalar1>::MulCost, PacketAccess = false }; };
+
+/** \internal
+ * \brief Template functor to divide a scalar by a fixed other one
+ *
+ * This functor is used to implement the quotient of a matrix by
+ * a scalar where the scalar type is not necessarily a floating point type.
+ *
+ * \sa class CwiseUnaryOp, MatrixBase::operator/
+ */
+template<typename Scalar>
+struct scalar_quotient1_op {
+ typedef typename packet_traits<Scalar>::type Packet;
+ // FIXME default copy constructors seems bugged with std::complex<>
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE scalar_quotient1_op(const scalar_quotient1_op& other) : m_other(other.m_other) { }
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE scalar_quotient1_op(const Scalar& other) : m_other(other) {}
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a / m_other; }
+ EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
+ { return internal::pdiv(a, pset1<Packet>(m_other)); }
+ typename add_const_on_value_type<typename NumTraits<Scalar>::Nested>::type m_other;
+};
+template<typename Scalar>
+struct functor_traits<scalar_quotient1_op<Scalar> >
+{ enum { Cost = 2 * NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasDiv }; };
+
+// In Eigen, any binary op (Product, CwiseBinaryOp) require the Lhs and Rhs to have the same scalar type, except for multiplication
+// where the mixing of different types is handled by scalar_product_traits
+// In particular, real * complex<real> is allowed.
+// FIXME move this to functor_traits adding a functor_default
+template<typename Functor> struct functor_is_product_like { enum { ret = 0 }; };
+template<typename LhsScalar,typename RhsScalar> struct functor_is_product_like<scalar_product_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
+template<typename LhsScalar,typename RhsScalar> struct functor_is_product_like<scalar_conj_product_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
+template<typename LhsScalar,typename RhsScalar> struct functor_is_product_like<scalar_quotient_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
+
+
+/** \internal
+ * \brief Template functor to add a scalar to a fixed other one
+ * \sa class CwiseUnaryOp, Array::operator+
+ */
+/* If you wonder why doing the pset1() in packetOp() is an optimization check scalar_multiple_op */
+template<typename Scalar>
+struct scalar_add_op {
+ typedef typename packet_traits<Scalar>::type Packet;
+ // FIXME default copy constructors seems bugged with std::complex<>
+ EIGEN_DEVICE_FUNC inline scalar_add_op(const scalar_add_op& other) : m_other(other.m_other) { }
+ EIGEN_DEVICE_FUNC inline scalar_add_op(const Scalar& other) : m_other(other) { }
+ EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { return a + m_other; }
+ inline const Packet packetOp(const Packet& a) const
+ { return internal::padd(a, pset1<Packet>(m_other)); }
+ const Scalar m_other;
+};
+template<typename Scalar>
+struct functor_traits<scalar_add_op<Scalar> >
+{ enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = packet_traits<Scalar>::HasAdd }; };
+
+/** \internal
+ * \brief Template functor to subtract a fixed scalar to another one
+ * \sa class CwiseUnaryOp, Array::operator-, struct scalar_add_op, struct scalar_rsub_op
+ */
+template<typename Scalar>
+struct scalar_sub_op {
+ typedef typename packet_traits<Scalar>::type Packet;
+ inline scalar_sub_op(const scalar_sub_op& other) : m_other(other.m_other) { }
+ inline scalar_sub_op(const Scalar& other) : m_other(other) { }
+ inline Scalar operator() (const Scalar& a) const { return a - m_other; }
+ inline const Packet packetOp(const Packet& a) const
+ { return internal::psub(a, pset1<Packet>(m_other)); }
+ const Scalar m_other;
+};
+template<typename Scalar>
+struct functor_traits<scalar_sub_op<Scalar> >
+{ enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = packet_traits<Scalar>::HasAdd }; };
+
+/** \internal
+ * \brief Template functor to subtract a scalar to fixed another one
+ * \sa class CwiseUnaryOp, Array::operator-, struct scalar_add_op, struct scalar_sub_op
+ */
+template<typename Scalar>
+struct scalar_rsub_op {
+ typedef typename packet_traits<Scalar>::type Packet;
+ inline scalar_rsub_op(const scalar_rsub_op& other) : m_other(other.m_other) { }
+ inline scalar_rsub_op(const Scalar& other) : m_other(other) { }
+ inline Scalar operator() (const Scalar& a) const { return m_other - a; }
+ inline const Packet packetOp(const Packet& a) const
+ { return internal::psub(pset1<Packet>(m_other), a); }
+ const Scalar m_other;
+};
+template<typename Scalar>
+struct functor_traits<scalar_rsub_op<Scalar> >
+{ enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = packet_traits<Scalar>::HasAdd }; };
+
+/** \internal
+ * \brief Template functor to raise a scalar to a power
+ * \sa class CwiseUnaryOp, Cwise::pow
+ */
+template<typename Scalar>
+struct scalar_pow_op {
+ // FIXME default copy constructors seems bugged with std::complex<>
+ inline scalar_pow_op(const scalar_pow_op& other) : m_exponent(other.m_exponent) { }
+ inline scalar_pow_op(const Scalar& exponent) : m_exponent(exponent) {}
+ EIGEN_DEVICE_FUNC
+ inline Scalar operator() (const Scalar& a) const { return numext::pow(a, m_exponent); }
+ const Scalar m_exponent;
+};
+template<typename Scalar>
+struct functor_traits<scalar_pow_op<Scalar> >
+{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false }; };
+
+/** \internal
+ * \brief Template functor to compute the quotient between a scalar and array entries.
+ * \sa class CwiseUnaryOp, Cwise::inverse()
+ */
+template<typename Scalar>
+struct scalar_inverse_mult_op {
+ scalar_inverse_mult_op(const Scalar& other) : m_other(other) {}
+ EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { return m_other / a; }
+ template<typename Packet>
+ inline const Packet packetOp(const Packet& a) const
+ { return internal::pdiv(pset1<Packet>(m_other),a); }
+ Scalar m_other;
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_BINARY_FUNCTORS_H
diff --git a/Eigen/src/Core/functors/NullaryFunctors.h b/Eigen/src/Core/functors/NullaryFunctors.h
new file mode 100644
index 000000000..950acd93b
--- /dev/null
+++ b/Eigen/src/Core/functors/NullaryFunctors.h
@@ -0,0 +1,158 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2010 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_NULLARY_FUNCTORS_H
+#define EIGEN_NULLARY_FUNCTORS_H
+
+namespace Eigen {
+
+namespace internal {
+
+template<typename Scalar>
+struct scalar_constant_op {
+ typedef typename packet_traits<Scalar>::type Packet;
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE scalar_constant_op(const scalar_constant_op& other) : m_other(other.m_other) { }
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE scalar_constant_op(const Scalar& other) : m_other(other) { }
+ template<typename Index>
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (Index, Index = 0) const { return m_other; }
+ template<typename Index>
+ EIGEN_STRONG_INLINE const Packet packetOp(Index, Index = 0) const { return internal::pset1<Packet>(m_other); }
+ const Scalar m_other;
+};
+template<typename Scalar>
+struct functor_traits<scalar_constant_op<Scalar> >
+// FIXME replace this packet test by a safe one
+{ enum { Cost = 1, PacketAccess = packet_traits<Scalar>::Vectorizable, IsRepeatable = true }; };
+
+template<typename Scalar> struct scalar_identity_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_identity_op)
+ template<typename Index>
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (Index row, Index col) const { return row==col ? Scalar(1) : Scalar(0); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_identity_op<Scalar> >
+{ enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = false, IsRepeatable = true }; };
+
+template <typename Scalar, bool RandomAccess> struct linspaced_op_impl;
+
+// linear access for packet ops:
+// 1) initialization
+// base = [low, ..., low] + ([step, ..., step] * [-size, ..., 0])
+// 2) each step (where size is 1 for coeff access or PacketSize for packet access)
+// base += [size*step, ..., size*step]
+//
+// TODO: Perhaps it's better to initialize lazily (so not in the constructor but in packetOp)
+// in order to avoid the padd() in operator() ?
+template <typename Scalar>
+struct linspaced_op_impl<Scalar,false>
+{
+ typedef typename packet_traits<Scalar>::type Packet;
+
+ linspaced_op_impl(const Scalar& low, const Scalar& step) :
+ m_low(low), m_step(step),
+ m_packetStep(pset1<Packet>(packet_traits<Scalar>::size*step)),
+ m_base(padd(pset1<Packet>(low), pmul(pset1<Packet>(step),plset<Scalar>(-packet_traits<Scalar>::size)))) {}
+
+ template<typename Index>
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (Index i) const
+ {
+ m_base = padd(m_base, pset1<Packet>(m_step));
+ return m_low+Scalar(i)*m_step;
+ }
+
+ template<typename Index>
+ EIGEN_STRONG_INLINE const Packet packetOp(Index) const { return m_base = padd(m_base,m_packetStep); }
+
+ const Scalar m_low;
+ const Scalar m_step;
+ const Packet m_packetStep;
+ mutable Packet m_base;
+};
+
+// random access for packet ops:
+// 1) each step
+// [low, ..., low] + ( [step, ..., step] * ( [i, ..., i] + [0, ..., size] ) )
+template <typename Scalar>
+struct linspaced_op_impl<Scalar,true>
+{
+ typedef typename packet_traits<Scalar>::type Packet;
+
+ linspaced_op_impl(const Scalar& low, const Scalar& step) :
+ m_low(low), m_step(step),
+ m_lowPacket(pset1<Packet>(m_low)), m_stepPacket(pset1<Packet>(m_step)), m_interPacket(plset<Scalar>(0)) {}
+
+ template<typename Index>
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return m_low+i*m_step; }
+
+ template<typename Index>
+ EIGEN_STRONG_INLINE const Packet packetOp(Index i) const
+ { return internal::padd(m_lowPacket, pmul(m_stepPacket, padd(pset1<Packet>(i),m_interPacket))); }
+
+ const Scalar m_low;
+ const Scalar m_step;
+ const Packet m_lowPacket;
+ const Packet m_stepPacket;
+ const Packet m_interPacket;
+};
+
+// ----- Linspace functor ----------------------------------------------------------------
+
+// Forward declaration (we default to random access which does not really give
+// us a speed gain when using packet access but it allows to use the functor in
+// nested expressions).
+template <typename Scalar, bool RandomAccess = true> struct linspaced_op;
+template <typename Scalar, bool RandomAccess> struct functor_traits< linspaced_op<Scalar,RandomAccess> >
+{ enum { Cost = 1, PacketAccess = packet_traits<Scalar>::HasSetLinear, IsRepeatable = true }; };
+template <typename Scalar, bool RandomAccess> struct linspaced_op
+{
+ typedef typename packet_traits<Scalar>::type Packet;
+ linspaced_op(const Scalar& low, const Scalar& high, DenseIndex num_steps) : impl((num_steps==1 ? high : low), (num_steps==1 ? Scalar() : (high-low)/(num_steps-1))) {}
+
+ template<typename Index>
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return impl(i); }
+
+ // We need this function when assigning e.g. a RowVectorXd to a MatrixXd since
+ // there row==0 and col is used for the actual iteration.
+ template<typename Index>
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (Index row, Index col) const
+ {
+ eigen_assert(col==0 || row==0);
+ return impl(col + row);
+ }
+
+ template<typename Index>
+ EIGEN_STRONG_INLINE const Packet packetOp(Index i) const { return impl.packetOp(i); }
+
+ // We need this function when assigning e.g. a RowVectorXd to a MatrixXd since
+ // there row==0 and col is used for the actual iteration.
+ template<typename Index>
+ EIGEN_STRONG_INLINE const Packet packetOp(Index row, Index col) const
+ {
+ eigen_assert(col==0 || row==0);
+ return impl.packetOp(col + row);
+ }
+
+ // This proxy object handles the actual required temporaries, the different
+ // implementations (random vs. sequential access) as well as the
+ // correct piping to size 2/4 packet operations.
+ const linspaced_op_impl<Scalar,RandomAccess> impl;
+};
+
+// all functors allow linear access, except scalar_identity_op. So we fix here a quick meta
+// to indicate whether a functor allows linear access, just always answering 'yes' except for
+// scalar_identity_op.
+// FIXME move this to functor_traits adding a functor_default
+template<typename Functor> struct functor_has_linear_access { enum { ret = 1 }; };
+template<typename Scalar> struct functor_has_linear_access<scalar_identity_op<Scalar> > { enum { ret = 0 }; };
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_NULLARY_FUNCTORS_H
diff --git a/Eigen/src/Core/functors/StlFunctors.h b/Eigen/src/Core/functors/StlFunctors.h
new file mode 100644
index 000000000..863fd451d
--- /dev/null
+++ b/Eigen/src/Core/functors/StlFunctors.h
@@ -0,0 +1,129 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2010 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_STL_FUNCTORS_H
+#define EIGEN_STL_FUNCTORS_H
+
+namespace Eigen {
+
+namespace internal {
+
+// default functor traits for STL functors:
+
+template<typename T>
+struct functor_traits<std::multiplies<T> >
+{ enum { Cost = NumTraits<T>::MulCost, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::divides<T> >
+{ enum { Cost = NumTraits<T>::MulCost, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::plus<T> >
+{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::minus<T> >
+{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::negate<T> >
+{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::logical_or<T> >
+{ enum { Cost = 1, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::logical_and<T> >
+{ enum { Cost = 1, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::logical_not<T> >
+{ enum { Cost = 1, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::greater<T> >
+{ enum { Cost = 1, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::less<T> >
+{ enum { Cost = 1, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::greater_equal<T> >
+{ enum { Cost = 1, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::less_equal<T> >
+{ enum { Cost = 1, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::equal_to<T> >
+{ enum { Cost = 1, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::not_equal_to<T> >
+{ enum { Cost = 1, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::binder2nd<T> >
+{ enum { Cost = functor_traits<T>::Cost, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::binder1st<T> >
+{ enum { Cost = functor_traits<T>::Cost, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::unary_negate<T> >
+{ enum { Cost = 1 + functor_traits<T>::Cost, PacketAccess = false }; };
+
+template<typename T>
+struct functor_traits<std::binary_negate<T> >
+{ enum { Cost = 1 + functor_traits<T>::Cost, PacketAccess = false }; };
+
+#ifdef EIGEN_STDEXT_SUPPORT
+
+template<typename T0,typename T1>
+struct functor_traits<std::project1st<T0,T1> >
+{ enum { Cost = 0, PacketAccess = false }; };
+
+template<typename T0,typename T1>
+struct functor_traits<std::project2nd<T0,T1> >
+{ enum { Cost = 0, PacketAccess = false }; };
+
+template<typename T0,typename T1>
+struct functor_traits<std::select2nd<std::pair<T0,T1> > >
+{ enum { Cost = 0, PacketAccess = false }; };
+
+template<typename T0,typename T1>
+struct functor_traits<std::select1st<std::pair<T0,T1> > >
+{ enum { Cost = 0, PacketAccess = false }; };
+
+template<typename T0,typename T1>
+struct functor_traits<std::unary_compose<T0,T1> >
+{ enum { Cost = functor_traits<T0>::Cost + functor_traits<T1>::Cost, PacketAccess = false }; };
+
+template<typename T0,typename T1,typename T2>
+struct functor_traits<std::binary_compose<T0,T1,T2> >
+{ enum { Cost = functor_traits<T0>::Cost + functor_traits<T1>::Cost + functor_traits<T2>::Cost, PacketAccess = false }; };
+
+#endif // EIGEN_STDEXT_SUPPORT
+
+// allow to add new functors and specializations of functor_traits from outside Eigen.
+// this macro is really needed because functor_traits must be specialized after it is declared but before it is used...
+#ifdef EIGEN_FUNCTORS_PLUGIN
+#include EIGEN_FUNCTORS_PLUGIN
+#endif
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_STL_FUNCTORS_H
diff --git a/Eigen/src/Core/functors/UnaryFunctors.h b/Eigen/src/Core/functors/UnaryFunctors.h
new file mode 100644
index 000000000..a0fcea3f9
--- /dev/null
+++ b/Eigen/src/Core/functors/UnaryFunctors.h
@@ -0,0 +1,376 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2010 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_UNARY_FUNCTORS_H
+#define EIGEN_UNARY_FUNCTORS_H
+
+namespace Eigen {
+
+namespace internal {
+
+/** \internal
+ * \brief Template functor to compute the opposite of a scalar
+ *
+ * \sa class CwiseUnaryOp, MatrixBase::operator-
+ */
+template<typename Scalar> struct scalar_opposite_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_opposite_op)
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return -a; }
+ template<typename Packet>
+ EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
+ { return internal::pnegate(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_opposite_op<Scalar> >
+{ enum {
+ Cost = NumTraits<Scalar>::AddCost,
+ PacketAccess = packet_traits<Scalar>::HasNegate };
+};
+
+/** \internal
+ * \brief Template functor to compute the absolute value of a scalar
+ *
+ * \sa class CwiseUnaryOp, Cwise::abs
+ */
+template<typename Scalar> struct scalar_abs_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_abs_op)
+ typedef typename NumTraits<Scalar>::Real result_type;
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { using std::abs; return abs(a); }
+ template<typename Packet>
+ EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
+ { return internal::pabs(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_abs_op<Scalar> >
+{
+ enum {
+ Cost = NumTraits<Scalar>::AddCost,
+ PacketAccess = packet_traits<Scalar>::HasAbs
+ };
+};
+
+/** \internal
+ * \brief Template functor to compute the squared absolute value of a scalar
+ *
+ * \sa class CwiseUnaryOp, Cwise::abs2
+ */
+template<typename Scalar> struct scalar_abs2_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_abs2_op)
+ typedef typename NumTraits<Scalar>::Real result_type;
+ EIGEN_DEVICE_FUNC
+ EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return numext::abs2(a); }
+ template<typename Packet>
+ EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
+ { return internal::pmul(a,a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_abs2_op<Scalar> >
+{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasAbs2 }; };
+
+/** \internal
+ * \brief Template functor to compute the conjugate of a complex value
+ *
+ * \sa class CwiseUnaryOp, MatrixBase::conjugate()
+ */
+template<typename Scalar> struct scalar_conjugate_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_conjugate_op)
+ EIGEN_DEVICE_FUNC
+ EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { using numext::conj; return conj(a); }
+ template<typename Packet>
+ EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const { return internal::pconj(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_conjugate_op<Scalar> >
+{
+ enum {
+ Cost = NumTraits<Scalar>::IsComplex ? NumTraits<Scalar>::AddCost : 0,
+ PacketAccess = packet_traits<Scalar>::HasConj
+ };
+};
+
+/** \internal
+ * \brief Template functor to cast a scalar to another type
+ *
+ * \sa class CwiseUnaryOp, MatrixBase::cast()
+ */
+template<typename Scalar, typename NewType>
+struct scalar_cast_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_cast_op)
+ typedef NewType result_type;
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const NewType operator() (const Scalar& a) const { return cast<Scalar, NewType>(a); }
+};
+template<typename Scalar, typename NewType>
+struct functor_traits<scalar_cast_op<Scalar,NewType> >
+{ enum { Cost = is_same<Scalar, NewType>::value ? 0 : NumTraits<NewType>::AddCost, PacketAccess = false }; };
+
+/** \internal
+ * \brief Template functor to extract the real part of a complex
+ *
+ * \sa class CwiseUnaryOp, MatrixBase::real()
+ */
+template<typename Scalar>
+struct scalar_real_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_real_op)
+ typedef typename NumTraits<Scalar>::Real result_type;
+ EIGEN_DEVICE_FUNC
+ EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return numext::real(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_real_op<Scalar> >
+{ enum { Cost = 0, PacketAccess = false }; };
+
+/** \internal
+ * \brief Template functor to extract the imaginary part of a complex
+ *
+ * \sa class CwiseUnaryOp, MatrixBase::imag()
+ */
+template<typename Scalar>
+struct scalar_imag_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_op)
+ typedef typename NumTraits<Scalar>::Real result_type;
+ EIGEN_DEVICE_FUNC
+ EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return numext::imag(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_imag_op<Scalar> >
+{ enum { Cost = 0, PacketAccess = false }; };
+
+/** \internal
+ * \brief Template functor to extract the real part of a complex as a reference
+ *
+ * \sa class CwiseUnaryOp, MatrixBase::real()
+ */
+template<typename Scalar>
+struct scalar_real_ref_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_real_ref_op)
+ typedef typename NumTraits<Scalar>::Real result_type;
+ EIGEN_DEVICE_FUNC
+ EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return numext::real_ref(*const_cast<Scalar*>(&a)); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_real_ref_op<Scalar> >
+{ enum { Cost = 0, PacketAccess = false }; };
+
+/** \internal
+ * \brief Template functor to extract the imaginary part of a complex as a reference
+ *
+ * \sa class CwiseUnaryOp, MatrixBase::imag()
+ */
+template<typename Scalar>
+struct scalar_imag_ref_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_ref_op)
+ typedef typename NumTraits<Scalar>::Real result_type;
+ EIGEN_DEVICE_FUNC
+ EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return numext::imag_ref(*const_cast<Scalar*>(&a)); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_imag_ref_op<Scalar> >
+{ enum { Cost = 0, PacketAccess = false }; };
+
+/** \internal
+ *
+ * \brief Template functor to compute the exponential of a scalar
+ *
+ * \sa class CwiseUnaryOp, Cwise::exp()
+ */
+template<typename Scalar> struct scalar_exp_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_exp_op)
+ EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { using std::exp; return exp(a); }
+ typedef typename packet_traits<Scalar>::type Packet;
+ inline Packet packetOp(const Packet& a) const { return internal::pexp(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_exp_op<Scalar> >
+{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasExp }; };
+
+/** \internal
+ *
+ * \brief Template functor to compute the logarithm of a scalar
+ *
+ * \sa class CwiseUnaryOp, Cwise::log()
+ */
+template<typename Scalar> struct scalar_log_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_log_op)
+ EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { using std::log; return log(a); }
+ typedef typename packet_traits<Scalar>::type Packet;
+ inline Packet packetOp(const Packet& a) const { return internal::plog(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_log_op<Scalar> >
+{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasLog }; };
+
+
+/** \internal
+ * \brief Template functor to compute the square root of a scalar
+ * \sa class CwiseUnaryOp, Cwise::sqrt()
+ */
+template<typename Scalar> struct scalar_sqrt_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_sqrt_op)
+ EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { using std::sqrt; return sqrt(a); }
+ typedef typename packet_traits<Scalar>::type Packet;
+ inline Packet packetOp(const Packet& a) const { return internal::psqrt(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_sqrt_op<Scalar> >
+{ enum {
+ Cost = 5 * NumTraits<Scalar>::MulCost,
+ PacketAccess = packet_traits<Scalar>::HasSqrt
+ };
+};
+
+/** \internal
+ * \brief Template functor to compute the cosine of a scalar
+ * \sa class CwiseUnaryOp, ArrayBase::cos()
+ */
+template<typename Scalar> struct scalar_cos_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_cos_op)
+ EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { using std::cos; return cos(a); }
+ typedef typename packet_traits<Scalar>::type Packet;
+ inline Packet packetOp(const Packet& a) const { return internal::pcos(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_cos_op<Scalar> >
+{
+ enum {
+ Cost = 5 * NumTraits<Scalar>::MulCost,
+ PacketAccess = packet_traits<Scalar>::HasCos
+ };
+};
+
+/** \internal
+ * \brief Template functor to compute the sine of a scalar
+ * \sa class CwiseUnaryOp, ArrayBase::sin()
+ */
+template<typename Scalar> struct scalar_sin_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_sin_op)
+ EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { using std::sin; return sin(a); }
+ typedef typename packet_traits<Scalar>::type Packet;
+ inline Packet packetOp(const Packet& a) const { return internal::psin(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_sin_op<Scalar> >
+{
+ enum {
+ Cost = 5 * NumTraits<Scalar>::MulCost,
+ PacketAccess = packet_traits<Scalar>::HasSin
+ };
+};
+
+
+/** \internal
+ * \brief Template functor to compute the tan of a scalar
+ * \sa class CwiseUnaryOp, ArrayBase::tan()
+ */
+template<typename Scalar> struct scalar_tan_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_tan_op)
+ EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { using std::tan; return tan(a); }
+ typedef typename packet_traits<Scalar>::type Packet;
+ inline Packet packetOp(const Packet& a) const { return internal::ptan(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_tan_op<Scalar> >
+{
+ enum {
+ Cost = 5 * NumTraits<Scalar>::MulCost,
+ PacketAccess = packet_traits<Scalar>::HasTan
+ };
+};
+
+/** \internal
+ * \brief Template functor to compute the arc cosine of a scalar
+ * \sa class CwiseUnaryOp, ArrayBase::acos()
+ */
+template<typename Scalar> struct scalar_acos_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_acos_op)
+ EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { using std::acos; return acos(a); }
+ typedef typename packet_traits<Scalar>::type Packet;
+ inline Packet packetOp(const Packet& a) const { return internal::pacos(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_acos_op<Scalar> >
+{
+ enum {
+ Cost = 5 * NumTraits<Scalar>::MulCost,
+ PacketAccess = packet_traits<Scalar>::HasACos
+ };
+};
+
+/** \internal
+ * \brief Template functor to compute the arc sine of a scalar
+ * \sa class CwiseUnaryOp, ArrayBase::asin()
+ */
+template<typename Scalar> struct scalar_asin_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_asin_op)
+ EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { using std::asin; return asin(a); }
+ typedef typename packet_traits<Scalar>::type Packet;
+ inline Packet packetOp(const Packet& a) const { return internal::pasin(a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_asin_op<Scalar> >
+{
+ enum {
+ Cost = 5 * NumTraits<Scalar>::MulCost,
+ PacketAccess = packet_traits<Scalar>::HasASin
+ };
+};
+
+/** \internal
+ * \brief Template functor to compute the inverse of a scalar
+ * \sa class CwiseUnaryOp, Cwise::inverse()
+ */
+template<typename Scalar>
+struct scalar_inverse_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_inverse_op)
+ EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { return Scalar(1)/a; }
+ template<typename Packet>
+ inline const Packet packetOp(const Packet& a) const
+ { return internal::pdiv(pset1<Packet>(Scalar(1)),a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_inverse_op<Scalar> >
+{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasDiv }; };
+
+/** \internal
+ * \brief Template functor to compute the square of a scalar
+ * \sa class CwiseUnaryOp, Cwise::square()
+ */
+template<typename Scalar>
+struct scalar_square_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_square_op)
+ EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { return a*a; }
+ template<typename Packet>
+ inline const Packet packetOp(const Packet& a) const
+ { return internal::pmul(a,a); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_square_op<Scalar> >
+{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
+
+/** \internal
+ * \brief Template functor to compute the cube of a scalar
+ * \sa class CwiseUnaryOp, Cwise::cube()
+ */
+template<typename Scalar>
+struct scalar_cube_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_cube_op)
+ EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { return a*a*a; }
+ template<typename Packet>
+ inline const Packet packetOp(const Packet& a) const
+ { return internal::pmul(a,pmul(a,a)); }
+};
+template<typename Scalar>
+struct functor_traits<scalar_cube_op<Scalar> >
+{ enum { Cost = 2*NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
+
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_FUNCTORS_H