1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library
2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra.
3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This Source Code Form is subject to the terms of the Mozilla
7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Public License v. 2.0. If a copy of the MPL was not distributed
8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifndef EIGEN_FUNCTORS_H
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_FUNCTORS_H
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace Eigen {
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal {
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// associative functors:
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the sum of two scalars
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseBinaryOp, MatrixBase::operator+, class VectorwiseOp, MatrixBase::sum()
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct scalar_sum_op {
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_sum_op)
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { return a + b; }
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Packet>
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::padd(a,b); }
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Packet>
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Scalar predux(const Packet& a) const
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::predux(a); }
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_sum_op<Scalar> > {
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Cost = NumTraits<Scalar>::AddCost,
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    PacketAccess = packet_traits<Scalar>::HasAdd
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the product of two scalars
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseBinaryOp, Cwise::operator*(), class VectorwiseOp, MatrixBase::redux()
46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename LhsScalar,typename RhsScalar> struct scalar_product_op {
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    // TODO vectorize mixed product
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Vectorizable = is_same<LhsScalar,RhsScalar>::value && packet_traits<LhsScalar>::HasMul && packet_traits<RhsScalar>::HasMul
51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename scalar_product_traits<LhsScalar,RhsScalar>::ReturnType result_type;
53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_product_op)
54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const { return a * b; }
55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Packet>
56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::pmul(a,b); }
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Packet>
59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const result_type predux(const Packet& a) const
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::predux_mul(a); }
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename LhsScalar,typename RhsScalar>
63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_product_op<LhsScalar,RhsScalar> > {
64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Cost = (NumTraits<LhsScalar>::MulCost + NumTraits<RhsScalar>::MulCost)/2, // rough estimate!
66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    PacketAccess = scalar_product_op<LhsScalar,RhsScalar>::Vectorizable
67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the conjugate product of two scalars
72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * This is a short cut for conj(x) * y which is needed for optimization purpose; in Eigen2 support mode, this becomes x * conj(y)
74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename LhsScalar,typename RhsScalar> struct scalar_conj_product_op {
76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Conj = NumTraits<LhsScalar>::IsComplex
79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename scalar_product_traits<LhsScalar,RhsScalar>::ReturnType result_type;
82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_conj_product_op)
84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const
85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return conj_helper<LhsScalar,RhsScalar,Conj,false>().pmul(a,b); }
86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Packet>
88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return conj_helper<Packet,Packet,Conj,false>().pmul(a,b); }
90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename LhsScalar,typename RhsScalar>
92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_conj_product_op<LhsScalar,RhsScalar> > {
93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Cost = NumTraits<LhsScalar>::MulCost,
95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    PacketAccess = internal::is_same<LhsScalar, RhsScalar>::value && packet_traits<LhsScalar>::HasMul
96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
97c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
99c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
100c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the min of two scalars
101c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
102c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseBinaryOp, MatrixBase::cwiseMin, class VectorwiseOp, MatrixBase::minCoeff()
103c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
104c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct scalar_min_op {
105c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_min_op)
106c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { using std::min; return (min)(a, b); }
107c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Packet>
108c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
109c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::pmin(a,b); }
110c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Packet>
111c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Scalar predux(const Packet& a) const
112c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::predux_min(a); }
113c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_min_op<Scalar> > {
116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Cost = NumTraits<Scalar>::AddCost,
118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    PacketAccess = packet_traits<Scalar>::HasMin
119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the max of two scalars
124c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseBinaryOp, MatrixBase::cwiseMax, class VectorwiseOp, MatrixBase::maxCoeff()
126c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
127c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct scalar_max_op {
128c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_max_op)
129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { using std::max; return (max)(a, b); }
130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Packet>
131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::pmax(a,b); }
133c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Packet>
134c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Scalar predux(const Packet& a) const
135c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::predux_max(a); }
136c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
137c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
138c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_max_op<Scalar> > {
139c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
140c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Cost = NumTraits<Scalar>::AddCost,
141c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    PacketAccess = packet_traits<Scalar>::HasMax
142c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
143c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
144c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
145c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
146c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the hypot of two scalars
147c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
148c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa MatrixBase::stableNorm(), class Redux
149c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
150c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct scalar_hypot_op {
151c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_hypot_op)
152c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//   typedef typename NumTraits<Scalar>::Real result_type;
153c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& _x, const Scalar& _y) const
154c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
155c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    using std::max;
156c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    using std::min;
157c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Scalar p = (max)(_x, _y);
158c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Scalar q = (min)(_x, _y);
159c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Scalar qp = q/p;
160c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return p * sqrt(Scalar(1) + qp*qp);
161c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
162c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
163c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
164c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_hypot_op<Scalar> > {
165c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess=0 };
166c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
167c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
168c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
169c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the pow of two scalars
170c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
171c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar, typename OtherScalar> struct scalar_binary_pow_op {
172c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_binary_pow_op)
173c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Scalar operator() (const Scalar& a, const OtherScalar& b) const { return internal::pow(a, b); }
174c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
175c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar, typename OtherScalar>
176c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_binary_pow_op<Scalar,OtherScalar> > {
177c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false };
178c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
179c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
180c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// other binary functors:
181c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
182c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
183c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the difference of two scalars
184c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
185c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseBinaryOp, MatrixBase::operator-
186c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
187c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct scalar_difference_op {
188c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_difference_op)
189c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { return a - b; }
190c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Packet>
191c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
192c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::psub(a,b); }
193c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
194c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
195c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_difference_op<Scalar> > {
196c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
197c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Cost = NumTraits<Scalar>::AddCost,
198c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    PacketAccess = packet_traits<Scalar>::HasSub
199c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
200c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
201c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
202c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
203c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the quotient of two scalars
204c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
205c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseBinaryOp, Cwise::operator/()
206c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
207c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct scalar_quotient_op {
208c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_quotient_op)
209c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { return a / b; }
210c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Packet>
211c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
212c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::pdiv(a,b); }
213c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
214c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
215c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_quotient_op<Scalar> > {
216c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
217c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Cost = 2 * NumTraits<Scalar>::MulCost,
218c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    PacketAccess = packet_traits<Scalar>::HasDiv
219c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
220c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
221c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
222c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
223c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the and of two booleans
224c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
225c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseBinaryOp, ArrayBase::operator&&
226c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
227c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_boolean_and_op {
228c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_boolean_and_op)
229c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE bool operator() (const bool& a, const bool& b) const { return a && b; }
230c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
231c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<> struct functor_traits<scalar_boolean_and_op> {
232c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
233c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Cost = NumTraits<bool>::AddCost,
234c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    PacketAccess = false
235c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
236c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
237c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
238c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
239c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the or of two booleans
240c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
241c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseBinaryOp, ArrayBase::operator||
242c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
243c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_boolean_or_op {
244c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_boolean_or_op)
245c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE bool operator() (const bool& a, const bool& b) const { return a || b; }
246c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
247c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<> struct functor_traits<scalar_boolean_or_op> {
248c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
249c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Cost = NumTraits<bool>::AddCost,
250c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    PacketAccess = false
251c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
252c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
253c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
254c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// unary functors:
255c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
256c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
257c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the opposite of a scalar
258c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
259c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, MatrixBase::operator-
260c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
261c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct scalar_opposite_op {
262c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_opposite_op)
263c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return -a; }
264c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Packet>
265c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
266c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::pnegate(a); }
267c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
268c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
269c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_opposite_op<Scalar> >
270c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum {
271c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Cost = NumTraits<Scalar>::AddCost,
272c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    PacketAccess = packet_traits<Scalar>::HasNegate };
273c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
274c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
275c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
276c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the absolute value of a scalar
277c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
278c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, Cwise::abs
279c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
280c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct scalar_abs_op {
281c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_abs_op)
282c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename NumTraits<Scalar>::Real result_type;
283c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return internal::abs(a); }
284c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Packet>
285c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
286c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::pabs(a); }
287c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
288c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
289c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_abs_op<Scalar> >
290c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
291c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
292c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Cost = NumTraits<Scalar>::AddCost,
293c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    PacketAccess = packet_traits<Scalar>::HasAbs
294c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
295c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
296c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
297c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
298c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the squared absolute value of a scalar
299c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
300c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, Cwise::abs2
301c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
302c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct scalar_abs2_op {
303c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_abs2_op)
304c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename NumTraits<Scalar>::Real result_type;
305c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return internal::abs2(a); }
306c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Packet>
307c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
308c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::pmul(a,a); }
309c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
310c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
311c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_abs2_op<Scalar> >
312c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasAbs2 }; };
313c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
314c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
315c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the conjugate of a complex value
316c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
317c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, MatrixBase::conjugate()
318c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
319c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct scalar_conjugate_op {
320c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_conjugate_op)
321c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return internal::conj(a); }
322c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Packet>
323c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const { return internal::pconj(a); }
324c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
325c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
326c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_conjugate_op<Scalar> >
327c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
328c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
329c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Cost = NumTraits<Scalar>::IsComplex ? NumTraits<Scalar>::AddCost : 0,
330c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    PacketAccess = packet_traits<Scalar>::HasConj
331c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
332c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
333c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
334c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
335c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to cast a scalar to another type
336c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
337c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, MatrixBase::cast()
338c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
339c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar, typename NewType>
340c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_cast_op {
341c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_cast_op)
342c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef NewType result_type;
343c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const NewType operator() (const Scalar& a) const { return cast<Scalar, NewType>(a); }
344c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
345c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar, typename NewType>
346c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_cast_op<Scalar,NewType> >
347c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = is_same<Scalar, NewType>::value ? 0 : NumTraits<NewType>::AddCost, PacketAccess = false }; };
348c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
349c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
350c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to extract the real part of a complex
351c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
352c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, MatrixBase::real()
353c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
354c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
355c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_real_op {
356c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_real_op)
357c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename NumTraits<Scalar>::Real result_type;
358c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return internal::real(a); }
359c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
360c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
361c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_real_op<Scalar> >
362c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 0, PacketAccess = false }; };
363c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
364c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
365c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to extract the imaginary part of a complex
366c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
367c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, MatrixBase::imag()
368c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
369c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
370c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_imag_op {
371c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_op)
372c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename NumTraits<Scalar>::Real result_type;
373c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return internal::imag(a); }
374c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
375c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
376c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_imag_op<Scalar> >
377c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 0, PacketAccess = false }; };
378c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
379c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
380c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to extract the real part of a complex as a reference
381c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
382c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, MatrixBase::real()
383c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
384c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
385c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_real_ref_op {
386c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_real_ref_op)
387c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename NumTraits<Scalar>::Real result_type;
388c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return internal::real_ref(*const_cast<Scalar*>(&a)); }
389c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
390c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
391c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_real_ref_op<Scalar> >
392c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 0, PacketAccess = false }; };
393c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
394c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
395c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to extract the imaginary part of a complex as a reference
396c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
397c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, MatrixBase::imag()
398c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
399c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
400c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_imag_ref_op {
401c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_ref_op)
402c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename NumTraits<Scalar>::Real result_type;
403c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return internal::imag_ref(*const_cast<Scalar*>(&a)); }
404c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
405c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
406c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_imag_ref_op<Scalar> >
407c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 0, PacketAccess = false }; };
408c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
409c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
410c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
411c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the exponential of a scalar
412c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
413c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, Cwise::exp()
414c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
415c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct scalar_exp_op {
416c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_exp_op)
417c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline const Scalar operator() (const Scalar& a) const { return internal::exp(a); }
418c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename packet_traits<Scalar>::type Packet;
419c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Packet packetOp(const Packet& a) const { return internal::pexp(a); }
420c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
421c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
422c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_exp_op<Scalar> >
423c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasExp }; };
424c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
425c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
426c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
427c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the logarithm of a scalar
428c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
429c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, Cwise::log()
430c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
431c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct scalar_log_op {
432c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_log_op)
433c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline const Scalar operator() (const Scalar& a) const { return internal::log(a); }
434c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename packet_traits<Scalar>::type Packet;
435c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Packet packetOp(const Packet& a) const { return internal::plog(a); }
436c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
437c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
438c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_log_op<Scalar> >
439c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasLog }; };
440c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
441c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
442c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to multiply a scalar by a fixed other one
443c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
444c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, MatrixBase::operator*, MatrixBase::operator/
445c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
446c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/* NOTE why doing the pset1() in packetOp *is* an optimization ?
447c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * indeed it seems better to declare m_other as a Packet and do the pset1() once
448c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * in the constructor. However, in practice:
449c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath *  - GCC does not like m_other as a Packet and generate a load every time it needs it
450c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath *  - on the other hand GCC is able to moves the pset1() away the loop :)
451c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath *  - simpler code ;)
452c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * (ICC and gcc 4.4 seems to perform well in both cases, the issue is visible with y = a*x + b*y)
453c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath */
454c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
455c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_multiple_op {
456c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename packet_traits<Scalar>::type Packet;
457c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // FIXME default copy constructors seems bugged with std::complex<>
458c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE scalar_multiple_op(const scalar_multiple_op& other) : m_other(other.m_other) { }
459c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE scalar_multiple_op(const Scalar& other) : m_other(other) { }
460c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a * m_other; }
461c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
462c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::pmul(a, pset1<Packet>(m_other)); }
463c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typename add_const_on_value_type<typename NumTraits<Scalar>::Nested>::type m_other;
464c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
465c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
466c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_multiple_op<Scalar> >
467c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
468c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
469c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar1, typename Scalar2>
470c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_multiple2_op {
471c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename scalar_product_traits<Scalar1,Scalar2>::ReturnType result_type;
472c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE scalar_multiple2_op(const scalar_multiple2_op& other) : m_other(other.m_other) { }
473c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE scalar_multiple2_op(const Scalar2& other) : m_other(other) { }
474c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE result_type operator() (const Scalar1& a) const { return a * m_other; }
475c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typename add_const_on_value_type<typename NumTraits<Scalar2>::Nested>::type m_other;
476c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
477c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar1,typename Scalar2>
478c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_multiple2_op<Scalar1,Scalar2> >
479c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = NumTraits<Scalar1>::MulCost, PacketAccess = false }; };
480c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
481c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar, bool IsInteger>
482c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_quotient1_impl {
483c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename packet_traits<Scalar>::type Packet;
484c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // FIXME default copy constructors seems bugged with std::complex<>
485c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE scalar_quotient1_impl(const scalar_quotient1_impl& other) : m_other(other.m_other) { }
486c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE scalar_quotient1_impl(const Scalar& other) : m_other(static_cast<Scalar>(1) / other) {}
487c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a * m_other; }
488c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
489c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::pmul(a, pset1<Packet>(m_other)); }
490c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const Scalar m_other;
491c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
492c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
493c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_quotient1_impl<Scalar,false> >
494c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
495c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
496c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
497c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_quotient1_impl<Scalar,true> {
498c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // FIXME default copy constructors seems bugged with std::complex<>
499c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE scalar_quotient1_impl(const scalar_quotient1_impl& other) : m_other(other.m_other) { }
500c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE scalar_quotient1_impl(const Scalar& other) : m_other(other) {}
501c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a / m_other; }
502c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typename add_const_on_value_type<typename NumTraits<Scalar>::Nested>::type m_other;
503c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
504c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
505c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_quotient1_impl<Scalar,true> >
506c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 2 * NumTraits<Scalar>::MulCost, PacketAccess = false }; };
507c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
508c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
509c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to divide a scalar by a fixed other one
510c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
511c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * This functor is used to implement the quotient of a matrix by
512c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * a scalar where the scalar type is not necessarily a floating point type.
513c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
514c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, MatrixBase::operator/
515c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
516c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
517c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_quotient1_op : scalar_quotient1_impl<Scalar, NumTraits<Scalar>::IsInteger > {
518c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE scalar_quotient1_op(const Scalar& other)
519c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    : scalar_quotient1_impl<Scalar, NumTraits<Scalar>::IsInteger >(other) {}
520c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
521c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
522c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_quotient1_op<Scalar> >
523c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath: functor_traits<scalar_quotient1_impl<Scalar, NumTraits<Scalar>::IsInteger> >
524c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{};
525c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
526c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// nullary functors
527c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
528c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
529c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_constant_op {
530c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename packet_traits<Scalar>::type Packet;
531c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE scalar_constant_op(const scalar_constant_op& other) : m_other(other.m_other) { }
532c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE scalar_constant_op(const Scalar& other) : m_other(other) { }
533c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Index>
534c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Scalar operator() (Index, Index = 0) const { return m_other; }
535c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Index>
536c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Packet packetOp(Index, Index = 0) const { return internal::pset1<Packet>(m_other); }
537c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const Scalar m_other;
538c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
539c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
540c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_constant_op<Scalar> >
541c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// FIXME replace this packet test by a safe one
542c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 1, PacketAccess = packet_traits<Scalar>::Vectorizable, IsRepeatable = true }; };
543c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
544c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct scalar_identity_op {
545c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_identity_op)
546c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Index>
547c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Scalar operator() (Index row, Index col) const { return row==col ? Scalar(1) : Scalar(0); }
548c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
549c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
550c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_identity_op<Scalar> >
551c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = false, IsRepeatable = true }; };
552c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
553c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate <typename Scalar, bool RandomAccess> struct linspaced_op_impl;
554c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
555c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// linear access for packet ops:
556c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 1) initialization
557c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//   base = [low, ..., low] + ([step, ..., step] * [-size, ..., 0])
558c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 2) each step
559c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//   base += [size*step, ..., size*step]
560c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate <typename Scalar>
561c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct linspaced_op_impl<Scalar,false>
562c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
563c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename packet_traits<Scalar>::type Packet;
564c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
565c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  linspaced_op_impl(Scalar low, Scalar step) :
566c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  m_low(low), m_step(step),
567c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  m_packetStep(pset1<Packet>(packet_traits<Scalar>::size*step)),
568c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  m_base(padd(pset1<Packet>(low),pmul(pset1<Packet>(step),plset<Scalar>(-packet_traits<Scalar>::size)))) {}
569c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
570c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Index>
571c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return m_low+i*m_step; }
572c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Index>
573c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Packet packetOp(Index) const { return m_base = padd(m_base,m_packetStep); }
574c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
575c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const Scalar m_low;
576c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const Scalar m_step;
577c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const Packet m_packetStep;
578c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  mutable Packet m_base;
579c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
580c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
581c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// random access for packet ops:
582c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 1) each step
583c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//   [low, ..., low] + ( [step, ..., step] * ( [i, ..., i] + [0, ..., size] ) )
584c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate <typename Scalar>
585c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct linspaced_op_impl<Scalar,true>
586c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
587c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename packet_traits<Scalar>::type Packet;
588c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
589c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  linspaced_op_impl(Scalar low, Scalar step) :
590c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  m_low(low), m_step(step),
591c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  m_lowPacket(pset1<Packet>(m_low)), m_stepPacket(pset1<Packet>(m_step)), m_interPacket(plset<Scalar>(0)) {}
592c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
593c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Index>
594c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return m_low+i*m_step; }
595c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
596c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Index>
597c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Packet packetOp(Index i) const
598c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::padd(m_lowPacket, pmul(m_stepPacket, padd(pset1<Packet>(i),m_interPacket))); }
599c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
600c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const Scalar m_low;
601c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const Scalar m_step;
602c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const Packet m_lowPacket;
603c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const Packet m_stepPacket;
604c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const Packet m_interPacket;
605c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
606c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
607c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// ----- Linspace functor ----------------------------------------------------------------
608c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
609c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Forward declaration (we default to random access which does not really give
610c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// us a speed gain when using packet access but it allows to use the functor in
611c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// nested expressions).
612c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate <typename Scalar, bool RandomAccess = true> struct linspaced_op;
613c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate <typename Scalar, bool RandomAccess> struct functor_traits< linspaced_op<Scalar,RandomAccess> >
614c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 1, PacketAccess = packet_traits<Scalar>::HasSetLinear, IsRepeatable = true }; };
615c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate <typename Scalar, bool RandomAccess> struct linspaced_op
616c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
617c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename packet_traits<Scalar>::type Packet;
618c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  linspaced_op(Scalar low, Scalar high, int num_steps) : impl((num_steps==1 ? high : low), (num_steps==1 ? Scalar() : (high-low)/(num_steps-1))) {}
619c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
620c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Index>
621c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return impl(i); }
622c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
623c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // We need this function when assigning e.g. a RowVectorXd to a MatrixXd since
624c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // there row==0 and col is used for the actual iteration.
625c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Index>
626c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Scalar operator() (Index row, Index col) const
627c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
628c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    eigen_assert(col==0 || row==0);
629c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return impl(col + row);
630c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
631c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
632c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Index>
633c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Packet packetOp(Index i) const { return impl.packetOp(i); }
634c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
635c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // We need this function when assigning e.g. a RowVectorXd to a MatrixXd since
636c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // there row==0 and col is used for the actual iteration.
637c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Index>
638c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_STRONG_INLINE const Packet packetOp(Index row, Index col) const
639c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
640c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    eigen_assert(col==0 || row==0);
641c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return impl.packetOp(col + row);
642c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
643c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
644c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // This proxy object handles the actual required temporaries, the different
645c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // implementations (random vs. sequential access) as well as the
646c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // correct piping to size 2/4 packet operations.
647c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const linspaced_op_impl<Scalar,RandomAccess> impl;
648c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
649c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
650c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// all functors allow linear access, except scalar_identity_op. So we fix here a quick meta
651c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// to indicate whether a functor allows linear access, just always answering 'yes' except for
652c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// scalar_identity_op.
653c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// FIXME move this to functor_traits adding a functor_default
654c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Functor> struct functor_has_linear_access { enum { ret = 1 }; };
655c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct functor_has_linear_access<scalar_identity_op<Scalar> > { enum { ret = 0 }; };
656c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
657c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// in CwiseBinaryOp, we require the Lhs and Rhs to have the same scalar type, except for multiplication
658c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// where we only require them to have the same _real_ scalar type so one may multiply, say, float by complex<float>.
659c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// FIXME move this to functor_traits adding a functor_default
660c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Functor> struct functor_allows_mixing_real_and_complex { enum { ret = 0 }; };
661c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename LhsScalar,typename RhsScalar> struct functor_allows_mixing_real_and_complex<scalar_product_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
662c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename LhsScalar,typename RhsScalar> struct functor_allows_mixing_real_and_complex<scalar_conj_product_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
663c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
664c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
665c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
666c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to add a scalar to a fixed other one
667c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, Array::operator+
668c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
669c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/* If you wonder why doing the pset1() in packetOp() is an optimization check scalar_multiple_op */
670c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
671c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_add_op {
672c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename packet_traits<Scalar>::type Packet;
673c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // FIXME default copy constructors seems bugged with std::complex<>
674c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline scalar_add_op(const scalar_add_op& other) : m_other(other.m_other) { }
675c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline scalar_add_op(const Scalar& other) : m_other(other) { }
676c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Scalar operator() (const Scalar& a) const { return a + m_other; }
677c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline const Packet packetOp(const Packet& a) const
678c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::padd(a, pset1<Packet>(m_other)); }
679c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const Scalar m_other;
680c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
681c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
682c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_add_op<Scalar> >
683c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = packet_traits<Scalar>::HasAdd }; };
684c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
685c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
686c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the square root of a scalar
687c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, Cwise::sqrt()
688c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
689c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct scalar_sqrt_op {
690c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_sqrt_op)
691c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline const Scalar operator() (const Scalar& a) const { return internal::sqrt(a); }
692c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename packet_traits<Scalar>::type Packet;
693c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Packet packetOp(const Packet& a) const { return internal::psqrt(a); }
694c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
695c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
696c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_sqrt_op<Scalar> >
697c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum {
698c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Cost = 5 * NumTraits<Scalar>::MulCost,
699c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    PacketAccess = packet_traits<Scalar>::HasSqrt
700c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
701c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
702c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
703c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
704c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the cosine of a scalar
705c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, ArrayBase::cos()
706c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
707c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct scalar_cos_op {
708c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_cos_op)
709c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Scalar operator() (const Scalar& a) const { return internal::cos(a); }
710c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename packet_traits<Scalar>::type Packet;
711c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Packet packetOp(const Packet& a) const { return internal::pcos(a); }
712c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
713c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
714c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_cos_op<Scalar> >
715c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
716c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
717c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Cost = 5 * NumTraits<Scalar>::MulCost,
718c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    PacketAccess = packet_traits<Scalar>::HasCos
719c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
720c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
721c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
722c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
723c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the sine of a scalar
724c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, ArrayBase::sin()
725c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
726c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct scalar_sin_op {
727c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_sin_op)
728c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline const Scalar operator() (const Scalar& a) const { return internal::sin(a); }
729c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename packet_traits<Scalar>::type Packet;
730c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Packet packetOp(const Packet& a) const { return internal::psin(a); }
731c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
732c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
733c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_sin_op<Scalar> >
734c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
735c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
736c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Cost = 5 * NumTraits<Scalar>::MulCost,
737c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    PacketAccess = packet_traits<Scalar>::HasSin
738c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
739c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
740c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
741c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
742c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
743c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the tan of a scalar
744c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, ArrayBase::tan()
745c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
746c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct scalar_tan_op {
747c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_tan_op)
748c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline const Scalar operator() (const Scalar& a) const { return internal::tan(a); }
749c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename packet_traits<Scalar>::type Packet;
750c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Packet packetOp(const Packet& a) const { return internal::ptan(a); }
751c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
752c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
753c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_tan_op<Scalar> >
754c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
755c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
756c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Cost = 5 * NumTraits<Scalar>::MulCost,
757c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    PacketAccess = packet_traits<Scalar>::HasTan
758c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
759c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
760c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
761c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
762c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the arc cosine of a scalar
763c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, ArrayBase::acos()
764c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
765c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct scalar_acos_op {
766c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_acos_op)
767c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline const Scalar operator() (const Scalar& a) const { return internal::acos(a); }
768c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename packet_traits<Scalar>::type Packet;
769c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Packet packetOp(const Packet& a) const { return internal::pacos(a); }
770c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
771c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
772c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_acos_op<Scalar> >
773c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
774c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
775c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Cost = 5 * NumTraits<Scalar>::MulCost,
776c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    PacketAccess = packet_traits<Scalar>::HasACos
777c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
778c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
779c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
780c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
781c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the arc sine of a scalar
782c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, ArrayBase::asin()
783c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
784c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct scalar_asin_op {
785c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_asin_op)
786c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline const Scalar operator() (const Scalar& a) const { return internal::asin(a); }
787c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename packet_traits<Scalar>::type Packet;
788c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Packet packetOp(const Packet& a) const { return internal::pasin(a); }
789c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
790c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
791c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_asin_op<Scalar> >
792c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
793c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {
794c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Cost = 5 * NumTraits<Scalar>::MulCost,
795c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    PacketAccess = packet_traits<Scalar>::HasASin
796c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
797c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
798c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
799c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
800c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to raise a scalar to a power
801c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, Cwise::pow
802c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
803c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
804c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_pow_op {
805c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // FIXME default copy constructors seems bugged with std::complex<>
806c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline scalar_pow_op(const scalar_pow_op& other) : m_exponent(other.m_exponent) { }
807c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline scalar_pow_op(const Scalar& exponent) : m_exponent(exponent) {}
808c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Scalar operator() (const Scalar& a) const { return internal::pow(a, m_exponent); }
809c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const Scalar m_exponent;
810c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
811c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
812c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_pow_op<Scalar> >
813c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false }; };
814c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
815c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
816c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the quotient between a scalar and array entries.
817c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, Cwise::inverse()
818c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
819c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
820c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_inverse_mult_op {
821c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  scalar_inverse_mult_op(const Scalar& other) : m_other(other) {}
822c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Scalar operator() (const Scalar& a) const { return m_other / a; }
823c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Packet>
824c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline const Packet packetOp(const Packet& a) const
825c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::pdiv(pset1<Packet>(m_other),a); }
826c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Scalar m_other;
827c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
828c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
829c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
830c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the inverse of a scalar
831c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, Cwise::inverse()
832c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
833c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
834c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_inverse_op {
835c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_inverse_op)
836c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Scalar operator() (const Scalar& a) const { return Scalar(1)/a; }
837c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Packet>
838c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline const Packet packetOp(const Packet& a) const
839c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::pdiv(pset1<Packet>(Scalar(1)),a); }
840c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
841c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
842c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_inverse_op<Scalar> >
843c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasDiv }; };
844c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
845c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
846c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the square of a scalar
847c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, Cwise::square()
848c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
849c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
850c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_square_op {
851c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_square_op)
852c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Scalar operator() (const Scalar& a) const { return a*a; }
853c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Packet>
854c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline const Packet packetOp(const Packet& a) const
855c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::pmul(a,a); }
856c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
857c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
858c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_square_op<Scalar> >
859c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
860c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
861c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \internal
862c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief Template functor to compute the cube of a scalar
863c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \sa class CwiseUnaryOp, Cwise::cube()
864c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
865c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
866c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_cube_op {
867c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_EMPTY_STRUCT_CTOR(scalar_cube_op)
868c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Scalar operator() (const Scalar& a) const { return a*a*a; }
869c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Packet>
870c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline const Packet packetOp(const Packet& a) const
871c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  { return internal::pmul(a,pmul(a,a)); }
872c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
873c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar>
874c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<scalar_cube_op<Scalar> >
875c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 2*NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
876c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
877c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// default functor traits for STL functors:
878c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
879c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T>
880c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::multiplies<T> >
881c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = NumTraits<T>::MulCost, PacketAccess = false }; };
882c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
883c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T>
884c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::divides<T> >
885c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = NumTraits<T>::MulCost, PacketAccess = false }; };
886c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
887c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T>
888c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::plus<T> >
889c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
890c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
891c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T>
892c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::minus<T> >
893c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
894c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
895c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T>
896c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::negate<T> >
897c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
898c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
899c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T>
900c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::logical_or<T> >
901c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 1, PacketAccess = false }; };
902c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
903c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T>
904c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::logical_and<T> >
905c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 1, PacketAccess = false }; };
906c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
907c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T>
908c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::logical_not<T> >
909c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 1, PacketAccess = false }; };
910c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
911c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T>
912c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::greater<T> >
913c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 1, PacketAccess = false }; };
914c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
915c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T>
916c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::less<T> >
917c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 1, PacketAccess = false }; };
918c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
919c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T>
920c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::greater_equal<T> >
921c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 1, PacketAccess = false }; };
922c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
923c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T>
924c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::less_equal<T> >
925c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 1, PacketAccess = false }; };
926c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
927c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T>
928c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::equal_to<T> >
929c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 1, PacketAccess = false }; };
930c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
931c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T>
932c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::not_equal_to<T> >
933c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 1, PacketAccess = false }; };
934c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
935c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T>
936c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::binder2nd<T> >
937c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = functor_traits<T>::Cost, PacketAccess = false }; };
938c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
939c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T>
940c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::binder1st<T> >
941c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = functor_traits<T>::Cost, PacketAccess = false }; };
942c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
943c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T>
944c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::unary_negate<T> >
945c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 1 + functor_traits<T>::Cost, PacketAccess = false }; };
946c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
947c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T>
948c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::binary_negate<T> >
949c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 1 + functor_traits<T>::Cost, PacketAccess = false }; };
950c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
951c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifdef EIGEN_STDEXT_SUPPORT
952c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
953c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T0,typename T1>
954c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::project1st<T0,T1> >
955c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 0, PacketAccess = false }; };
956c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
957c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T0,typename T1>
958c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::project2nd<T0,T1> >
959c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 0, PacketAccess = false }; };
960c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
961c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T0,typename T1>
962c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::select2nd<std::pair<T0,T1> > >
963c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 0, PacketAccess = false }; };
964c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
965c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T0,typename T1>
966c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::select1st<std::pair<T0,T1> > >
967c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = 0, PacketAccess = false }; };
968c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
969c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T0,typename T1>
970c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::unary_compose<T0,T1> >
971c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = functor_traits<T0>::Cost + functor_traits<T1>::Cost, PacketAccess = false }; };
972c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
973c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T0,typename T1,typename T2>
974c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct functor_traits<std::binary_compose<T0,T1,T2> >
975c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ enum { Cost = functor_traits<T0>::Cost + functor_traits<T1>::Cost + functor_traits<T2>::Cost, PacketAccess = false }; };
976c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
977c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // EIGEN_STDEXT_SUPPORT
978c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
979c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// allow to add new functors and specializations of functor_traits from outside Eigen.
980c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// this macro is really needed because functor_traits must be specialized after it is declared but before it is used...
981c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifdef EIGEN_FUNCTORS_PLUGIN
982c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include EIGEN_FUNCTORS_PLUGIN
983c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif
984c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
985c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal
986c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
987c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace Eigen
988c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
989c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // EIGEN_FUNCTORS_H
990