1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library
2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra.
3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2009 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_AUTODIFF_SCALAR_H
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_AUTODIFF_SCALAR_H
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace Eigen {
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal {
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename A, typename B>
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct make_coherent_impl {
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static void run(A&, B&) {}
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// resize a to match b is a.size()==0, and conversely.
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename A, typename B>
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid make_coherent(const A& a, const B&b)
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  make_coherent_impl<A,B>::run(a.const_cast_derived(), b.const_cast_derived());
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename _DerType, bool Enable> struct auto_diff_special_op;
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/** \class AutoDiffScalar
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \brief A scalar type replacement with automatic differentation capability
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * \param _DerType the vector type used to store/represent the derivatives. The base scalar type
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *                 as well as the number of derivatives to compute are determined from this type.
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *                 Typical choices include, e.g., \c Vector4f for 4 derivatives, or \c VectorXf
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *                 if the number of derivatives is not known at compile time, and/or, the number
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *                 of derivatives is large.
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *                 Note that _DerType can also be a reference (e.g., \c VectorXf&) to wrap a
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *                 existing vector into an AutoDiffScalar.
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *                 Finally, _DerType can also be any Eigen compatible expression.
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * This class represents a scalar value while tracking its respective derivatives using Eigen's expression
46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * template mechanism.
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * It supports the following list of global math function:
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *  - std::abs, std::sqrt, std::pow, std::exp, std::log, std::sin, std::cos,
507faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  *  - internal::abs, internal::sqrt, numext::pow, internal::exp, internal::log, internal::sin, internal::cos,
517faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  *  - internal::conj, internal::real, internal::imag, numext::abs2.
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * AutoDiffScalar can be used as the scalar type of an Eigen::Matrix object. However,
54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * in that case, the expression template mechanism only occurs at the top Matrix level,
55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  * while derivatives are computed right away.
56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  *
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  */
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename _DerType>
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathclass AutoDiffScalar
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  : public internal::auto_diff_special_op
62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            <_DerType, !internal::is_same<typename internal::traits<typename internal::remove_all<_DerType>::type>::Scalar,
63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                                        typename NumTraits<typename internal::traits<typename internal::remove_all<_DerType>::type>::Scalar>::Real>::value>
64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  public:
66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef internal::auto_diff_special_op
67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            <_DerType, !internal::is_same<typename internal::traits<typename internal::remove_all<_DerType>::type>::Scalar,
68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                       typename NumTraits<typename internal::traits<typename internal::remove_all<_DerType>::type>::Scalar>::Real>::value> Base;
69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename internal::remove_all<_DerType>::type DerType;
70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename internal::traits<DerType>::Scalar Scalar;
71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename NumTraits<Scalar>::Real Real;
72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    using Base::operator+;
74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    using Base::operator*;
75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** Default constructor without any initialization. */
77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    AutoDiffScalar() {}
78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** Constructs an active scalar from its \a value,
80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        and initializes the \a nbDer derivatives such that it corresponds to the \a derNumber -th variable */
81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    AutoDiffScalar(const Scalar& value, int nbDer, int derNumber)
82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      : m_value(value), m_derivatives(DerType::Zero(nbDer))
83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      m_derivatives.coeffRef(derNumber) = Scalar(1);
85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** Conversion from a scalar constant to an active scalar.
88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      * The derivatives are set to zero. */
89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /*explicit*/ AutoDiffScalar(const Real& value)
90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      : m_value(value)
91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      if(m_derivatives.size()>0)
93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        m_derivatives.setZero();
94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    /** Constructs an active scalar from its \a value and derivatives \a der */
97c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    AutoDiffScalar(const Scalar& value, const DerType& der)
98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      : m_value(value), m_derivatives(der)
99c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {}
100c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
101c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerType>
102c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    AutoDiffScalar(const AutoDiffScalar<OtherDerType>& other)
103c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      : m_value(other.value()), m_derivatives(other.derivatives())
104c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {}
105c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
106c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    friend  std::ostream & operator << (std::ostream & s, const AutoDiffScalar& a)
107c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
108c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return s << a.value();
109c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
110c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
111c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    AutoDiffScalar(const AutoDiffScalar& other)
112c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      : m_value(other.value()), m_derivatives(other.derivatives())
113c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {}
114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerType>
116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline AutoDiffScalar& operator=(const AutoDiffScalar<OtherDerType>& other)
117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      m_value = other.value();
119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      m_derivatives = other.derivatives();
120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return *this;
121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline AutoDiffScalar& operator=(const AutoDiffScalar& other)
124c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      m_value = other.value();
126c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      m_derivatives = other.derivatives();
127c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return *this;
128c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     inline operator const Scalar& () const { return m_value; }
131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     inline operator Scalar& () { return m_value; }
132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
133c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline const Scalar& value() const { return m_value; }
134c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline Scalar& value() { return m_value; }
135c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
136c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline const DerType& derivatives() const { return m_derivatives; }
137c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline DerType& derivatives() { return m_derivatives; }
138c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
139c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline bool operator< (const Scalar& other) const  { return m_value <  other; }
140c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline bool operator<=(const Scalar& other) const  { return m_value <= other; }
141c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline bool operator> (const Scalar& other) const  { return m_value >  other; }
142c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline bool operator>=(const Scalar& other) const  { return m_value >= other; }
143c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline bool operator==(const Scalar& other) const  { return m_value == other; }
144c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline bool operator!=(const Scalar& other) const  { return m_value != other; }
145c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
146c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    friend inline bool operator< (const Scalar& a, const AutoDiffScalar& b) { return a <  b.value(); }
147c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    friend inline bool operator<=(const Scalar& a, const AutoDiffScalar& b) { return a <= b.value(); }
148c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    friend inline bool operator> (const Scalar& a, const AutoDiffScalar& b) { return a >  b.value(); }
149c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    friend inline bool operator>=(const Scalar& a, const AutoDiffScalar& b) { return a >= b.value(); }
150c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    friend inline bool operator==(const Scalar& a, const AutoDiffScalar& b) { return a == b.value(); }
151c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    friend inline bool operator!=(const Scalar& a, const AutoDiffScalar& b) { return a != b.value(); }
152c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
153c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerType> inline bool operator< (const AutoDiffScalar<OtherDerType>& b) const  { return m_value <  b.value(); }
154c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerType> inline bool operator<=(const AutoDiffScalar<OtherDerType>& b) const  { return m_value <= b.value(); }
155c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerType> inline bool operator> (const AutoDiffScalar<OtherDerType>& b) const  { return m_value >  b.value(); }
156c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerType> inline bool operator>=(const AutoDiffScalar<OtherDerType>& b) const  { return m_value >= b.value(); }
157c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerType> inline bool operator==(const AutoDiffScalar<OtherDerType>& b) const  { return m_value == b.value(); }
158c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerType> inline bool operator!=(const AutoDiffScalar<OtherDerType>& b) const  { return m_value != b.value(); }
159c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
160c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline const AutoDiffScalar<DerType&> operator+(const Scalar& other) const
161c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
162c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return AutoDiffScalar<DerType&>(m_value + other, m_derivatives);
163c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
164c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
165c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    friend inline const AutoDiffScalar<DerType&> operator+(const Scalar& a, const AutoDiffScalar& b)
166c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
167c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return AutoDiffScalar<DerType&>(a + b.value(), b.derivatives());
168c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
169c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
170c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     inline const AutoDiffScalar<DerType&> operator+(const Real& other) const
171c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     {
172c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//       return AutoDiffScalar<DerType&>(m_value + other, m_derivatives);
173c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     }
174c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
175c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     friend inline const AutoDiffScalar<DerType&> operator+(const Real& a, const AutoDiffScalar& b)
176c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     {
177c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//       return AutoDiffScalar<DerType&>(a + b.value(), b.derivatives());
178c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     }
179c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
180c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline AutoDiffScalar& operator+=(const Scalar& other)
181c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
182c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      value() += other;
183c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return *this;
184c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
185c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
186c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerType>
187c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline const AutoDiffScalar<CwiseBinaryOp<internal::scalar_sum_op<Scalar>,const DerType,const typename internal::remove_all<OtherDerType>::type> >
188c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    operator+(const AutoDiffScalar<OtherDerType>& other) const
189c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
190c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      internal::make_coherent(m_derivatives, other.derivatives());
191c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return AutoDiffScalar<CwiseBinaryOp<internal::scalar_sum_op<Scalar>,const DerType,const typename internal::remove_all<OtherDerType>::type> >(
192c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        m_value + other.value(),
193c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        m_derivatives + other.derivatives());
194c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
195c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
196c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerType>
197c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline AutoDiffScalar&
198c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    operator+=(const AutoDiffScalar<OtherDerType>& other)
199c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
200c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      (*this) = (*this) + other;
201c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return *this;
202c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
203c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
204c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline const AutoDiffScalar<DerType&> operator-(const Scalar& b) const
205c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
206c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return AutoDiffScalar<DerType&>(m_value - b, m_derivatives);
207c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
208c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
209c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    friend inline const AutoDiffScalar<CwiseUnaryOp<internal::scalar_opposite_op<Scalar>, const DerType> >
210c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    operator-(const Scalar& a, const AutoDiffScalar& b)
211c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
212c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return AutoDiffScalar<CwiseUnaryOp<internal::scalar_opposite_op<Scalar>, const DerType> >
213c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath            (a - b.value(), -b.derivatives());
214c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
215c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
216c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline AutoDiffScalar& operator-=(const Scalar& other)
217c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
218c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      value() -= other;
219c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return *this;
220c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
221c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
222c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerType>
223c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline const AutoDiffScalar<CwiseBinaryOp<internal::scalar_difference_op<Scalar>, const DerType,const typename internal::remove_all<OtherDerType>::type> >
224c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    operator-(const AutoDiffScalar<OtherDerType>& other) const
225c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
226c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      internal::make_coherent(m_derivatives, other.derivatives());
227c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return AutoDiffScalar<CwiseBinaryOp<internal::scalar_difference_op<Scalar>, const DerType,const typename internal::remove_all<OtherDerType>::type> >(
228c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        m_value - other.value(),
229c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        m_derivatives - other.derivatives());
230c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
231c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
232c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerType>
233c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline AutoDiffScalar&
234c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    operator-=(const AutoDiffScalar<OtherDerType>& other)
235c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
236c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      *this = *this - other;
237c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return *this;
238c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
239c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
240c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline const AutoDiffScalar<CwiseUnaryOp<internal::scalar_opposite_op<Scalar>, const DerType> >
241c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    operator-() const
242c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
243c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return AutoDiffScalar<CwiseUnaryOp<internal::scalar_opposite_op<Scalar>, const DerType> >(
244c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        -m_value,
245c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        -m_derivatives);
246c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
247c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
248c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline const AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType> >
249c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    operator*(const Scalar& other) const
250c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
251c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType> >(
252c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        m_value * other,
253c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        (m_derivatives * other));
254c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
255c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
256c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    friend inline const AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType> >
257c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    operator*(const Scalar& other, const AutoDiffScalar& a)
258c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
259c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType> >(
260c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        a.value() * other,
261c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        a.derivatives() * other);
262c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
263c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
264c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     inline const AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >
265c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     operator*(const Real& other) const
266c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     {
267c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//       return AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >(
268c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//         m_value * other,
269c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//         (m_derivatives * other));
270c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     }
271c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
272c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     friend inline const AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >
273c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     operator*(const Real& other, const AutoDiffScalar& a)
274c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     {
275c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//       return AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >(
276c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//         a.value() * other,
277c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//         a.derivatives() * other);
278c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     }
279c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
280c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline const AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType> >
281c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    operator/(const Scalar& other) const
282c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
283c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType> >(
284c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        m_value / other,
285c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        (m_derivatives * (Scalar(1)/other)));
286c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
287c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
288c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    friend inline const AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType> >
289c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    operator/(const Scalar& other, const AutoDiffScalar& a)
290c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
291c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType> >(
292c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        other / a.value(),
293c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        a.derivatives() * (Scalar(-other) / (a.value()*a.value())));
294c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
295c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
296c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     inline const AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >
297c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     operator/(const Real& other) const
298c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     {
299c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//       return AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >(
300c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//         m_value / other,
301c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//         (m_derivatives * (Real(1)/other)));
302c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     }
303c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
304c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     friend inline const AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >
305c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     operator/(const Real& other, const AutoDiffScalar& a)
306c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     {
307c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//       return AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >(
308c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//         other / a.value(),
309c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//         a.derivatives() * (-Real(1)/other));
310c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     }
311c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
312c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerType>
313c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline const AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>,
314c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        const CwiseBinaryOp<internal::scalar_difference_op<Scalar>,
315c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType>,
316c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const typename internal::remove_all<OtherDerType>::type > > > >
317c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    operator/(const AutoDiffScalar<OtherDerType>& other) const
318c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
319c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      internal::make_coherent(m_derivatives, other.derivatives());
320c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return AutoDiffScalar<CwiseUnaryOp<internal::scalar_multiple_op<Scalar>,
321c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        const CwiseBinaryOp<internal::scalar_difference_op<Scalar>,
322c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType>,
323c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const typename internal::remove_all<OtherDerType>::type > > > >(
324c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        m_value / other.value(),
325c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          ((m_derivatives * other.value()) - (m_value * other.derivatives()))
326c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        * (Scalar(1)/(other.value()*other.value())));
327c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
328c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
329c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerType>
330c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline const AutoDiffScalar<CwiseBinaryOp<internal::scalar_sum_op<Scalar>,
331c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType>,
332c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const typename internal::remove_all<OtherDerType>::type> > >
333c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    operator*(const AutoDiffScalar<OtherDerType>& other) const
334c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
335c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      internal::make_coherent(m_derivatives, other.derivatives());
336c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return AutoDiffScalar<const CwiseBinaryOp<internal::scalar_sum_op<Scalar>,
337c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DerType>,
338c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const typename internal::remove_all<OtherDerType>::type > > >(
339c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        m_value * other.value(),
340c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        (m_derivatives * other.value()) + (m_value * other.derivatives()));
341c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
342c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
343c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline AutoDiffScalar& operator*=(const Scalar& other)
344c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
345c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      *this = *this * other;
346c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return *this;
347c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
348c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
349c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerType>
350c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline AutoDiffScalar& operator*=(const AutoDiffScalar<OtherDerType>& other)
351c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
352c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      *this = *this * other;
353c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return *this;
354c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
355c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
356c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline AutoDiffScalar& operator/=(const Scalar& other)
357c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
358c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      *this = *this / other;
359c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return *this;
360c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
361c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
362c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    template<typename OtherDerType>
363c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    inline AutoDiffScalar& operator/=(const AutoDiffScalar<OtherDerType>& other)
364c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
365c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      *this = *this / other;
366c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return *this;
367c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
368c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
369c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  protected:
370c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Scalar m_value;
371c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    DerType m_derivatives;
372c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
373c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
374c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
375c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal {
376c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
377c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename _DerType>
378c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct auto_diff_special_op<_DerType, true>
379c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//   : auto_diff_scalar_op<_DerType, typename NumTraits<Scalar>::Real,
380c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//                            is_same<Scalar,typename NumTraits<Scalar>::Real>::value>
381c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
382c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename remove_all<_DerType>::type DerType;
383c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename traits<DerType>::Scalar Scalar;
384c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename NumTraits<Scalar>::Real Real;
385c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
386c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//   typedef auto_diff_scalar_op<_DerType, typename NumTraits<Scalar>::Real,
387c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//                            is_same<Scalar,typename NumTraits<Scalar>::Real>::value> Base;
388c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
389c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//   using Base::operator+;
390c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//   using Base::operator+=;
391c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//   using Base::operator-;
392c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//   using Base::operator-=;
393c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//   using Base::operator*;
394c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//   using Base::operator*=;
395c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
396c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const AutoDiffScalar<_DerType>& derived() const { return *static_cast<const AutoDiffScalar<_DerType>*>(this); }
397c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  AutoDiffScalar<_DerType>& derived() { return *static_cast<AutoDiffScalar<_DerType>*>(this); }
398c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
399c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
400c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline const AutoDiffScalar<DerType&> operator+(const Real& other) const
401c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
402c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return AutoDiffScalar<DerType&>(derived().value() + other, derived().derivatives());
403c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
404c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
405c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  friend inline const AutoDiffScalar<DerType&> operator+(const Real& a, const AutoDiffScalar<_DerType>& b)
406c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
407c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return AutoDiffScalar<DerType&>(a + b.value(), b.derivatives());
408c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
409c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
410c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline AutoDiffScalar<_DerType>& operator+=(const Real& other)
411c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
412c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    derived().value() += other;
413c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return derived();
414c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
415c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
416c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
417c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline const AutoDiffScalar<typename CwiseUnaryOp<scalar_multiple2_op<Scalar,Real>, DerType>::Type >
418c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  operator*(const Real& other) const
419c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
420c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return AutoDiffScalar<typename CwiseUnaryOp<scalar_multiple2_op<Scalar,Real>, DerType>::Type >(
421c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      derived().value() * other,
422c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      derived().derivatives() * other);
423c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
424c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
425c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  friend inline const AutoDiffScalar<typename CwiseUnaryOp<scalar_multiple2_op<Scalar,Real>, DerType>::Type >
426c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  operator*(const Real& other, const AutoDiffScalar<_DerType>& a)
427c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
428c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return AutoDiffScalar<typename CwiseUnaryOp<scalar_multiple2_op<Scalar,Real>, DerType>::Type >(
429c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      a.value() * other,
430c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      a.derivatives() * other);
431c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
432c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
433c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline AutoDiffScalar<_DerType>& operator*=(const Scalar& other)
434c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
435c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    *this = *this * other;
436c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return derived();
437c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
438c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
439c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
440c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename _DerType>
441c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct auto_diff_special_op<_DerType, false>
442c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
443c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  void operator*() const;
444c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  void operator-() const;
445c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  void operator+() const;
446c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
447c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
448c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename A_Scalar, int A_Rows, int A_Cols, int A_Options, int A_MaxRows, int A_MaxCols, typename B>
449c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct make_coherent_impl<Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols>, B> {
450c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols> A;
451c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static void run(A& a, B& b) {
452c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if((A_Rows==Dynamic || A_Cols==Dynamic) && (a.size()==0))
453c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
454c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      a.resize(b.size());
455c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      a.setZero();
456c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
457c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
458c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
459c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
460c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename A, typename B_Scalar, int B_Rows, int B_Cols, int B_Options, int B_MaxRows, int B_MaxCols>
461c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct make_coherent_impl<A, Matrix<B_Scalar, B_Rows, B_Cols, B_Options, B_MaxRows, B_MaxCols> > {
462c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef Matrix<B_Scalar, B_Rows, B_Cols, B_Options, B_MaxRows, B_MaxCols> B;
463c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static void run(A& a, B& b) {
464c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if((B_Rows==Dynamic || B_Cols==Dynamic) && (b.size()==0))
465c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
466c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      b.resize(a.size());
467c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      b.setZero();
468c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
469c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
470c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
471c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
472c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename A_Scalar, int A_Rows, int A_Cols, int A_Options, int A_MaxRows, int A_MaxCols,
473c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         typename B_Scalar, int B_Rows, int B_Cols, int B_Options, int B_MaxRows, int B_MaxCols>
474c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct make_coherent_impl<Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols>,
475c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                             Matrix<B_Scalar, B_Rows, B_Cols, B_Options, B_MaxRows, B_MaxCols> > {
476c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols> A;
477c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef Matrix<B_Scalar, B_Rows, B_Cols, B_Options, B_MaxRows, B_MaxCols> B;
478c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static void run(A& a, B& b) {
479c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if((A_Rows==Dynamic || A_Cols==Dynamic) && (a.size()==0))
480c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
481c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      a.resize(b.size());
482c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      a.setZero();
483c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
484c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    else if((B_Rows==Dynamic || B_Cols==Dynamic) && (b.size()==0))
485c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
486c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      b.resize(a.size());
487c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      b.setZero();
488c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
489c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
490c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
491c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
4927faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandeztemplate<typename A_Scalar, int A_Rows, int A_Cols, int A_Options, int A_MaxRows, int A_MaxCols>
4937faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandezstruct scalar_product_traits<Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols>,A_Scalar>
494c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
4957faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  enum { Defined = 1 };
4967faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  typedef Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols> ReturnType;
497c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
498c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
4997faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandeztemplate<typename A_Scalar, int A_Rows, int A_Cols, int A_Options, int A_MaxRows, int A_MaxCols>
5007faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandezstruct scalar_product_traits<A_Scalar, Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols> >
501c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
5027faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  enum { Defined = 1 };
5037faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  typedef Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols> ReturnType;
504c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
505c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
506c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename DerType>
507c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct scalar_product_traits<AutoDiffScalar<DerType>,typename DerType::Scalar>
508c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
5097faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  enum { Defined = 1 };
5107faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  typedef AutoDiffScalar<DerType> ReturnType;
5117faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez};
5127faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez
5137faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandeztemplate<typename DerType>
5147faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandezstruct scalar_product_traits<typename DerType::Scalar,AutoDiffScalar<DerType> >
5157faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez{
5167faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  enum { Defined = 1 };
5177faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  typedef AutoDiffScalar<DerType> ReturnType;
518c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
519c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
520c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal
521c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
522c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(FUNC,CODE) \
523c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename DerType> \
524c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline const Eigen::AutoDiffScalar<Eigen::CwiseUnaryOp<Eigen::internal::scalar_multiple_op<typename Eigen::internal::traits<typename Eigen::internal::remove_all<DerType>::type>::Scalar>, const typename Eigen::internal::remove_all<DerType>::type> > \
525c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  FUNC(const Eigen::AutoDiffScalar<DerType>& x) { \
526c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    using namespace Eigen; \
527c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename Eigen::internal::traits<typename Eigen::internal::remove_all<DerType>::type>::Scalar Scalar; \
528c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef AutoDiffScalar<CwiseUnaryOp<Eigen::internal::scalar_multiple_op<Scalar>, const typename Eigen::internal::remove_all<DerType>::type> > ReturnType; \
529c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CODE; \
530c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
531c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
532c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename DerType>
533c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline const AutoDiffScalar<DerType>& conj(const AutoDiffScalar<DerType>& x)  { return x; }
534c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename DerType>
535c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline const AutoDiffScalar<DerType>& real(const AutoDiffScalar<DerType>& x)  { return x; }
536c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename DerType>
537c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline typename DerType::Scalar imag(const AutoDiffScalar<DerType>&)    { return 0.; }
538c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename DerType, typename T>
539c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline AutoDiffScalar<DerType> (min)(const AutoDiffScalar<DerType>& x, const T& y)    { return (x <= y ? x : y); }
540c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename DerType, typename T>
541c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline AutoDiffScalar<DerType> (max)(const AutoDiffScalar<DerType>& x, const T& y)    { return (x >= y ? x : y); }
542c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename DerType, typename T>
543c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline AutoDiffScalar<DerType> (min)(const T& x, const AutoDiffScalar<DerType>& y)    { return (x < y ? x : y); }
544c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename DerType, typename T>
545c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline AutoDiffScalar<DerType> (max)(const T& x, const AutoDiffScalar<DerType>& y)    { return (x > y ? x : y); }
546c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
547c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(abs,
548c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using std::abs;
5497faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  return ReturnType(abs(x.value()), x.derivatives() * (x.value()<0 ? -1 : 1) );)
550c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
551c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(abs2,
5527faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  using numext::abs2;
553c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  return ReturnType(abs2(x.value()), x.derivatives() * (Scalar(2)*x.value()));)
554c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
555c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(sqrt,
556c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using std::sqrt;
557c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Scalar sqrtx = sqrt(x.value());
558c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  return ReturnType(sqrtx,x.derivatives() * (Scalar(0.5) / sqrtx));)
559c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
560c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(cos,
561c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using std::cos;
562c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using std::sin;
563c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  return ReturnType(cos(x.value()), x.derivatives() * (-sin(x.value())));)
564c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
565c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(sin,
566c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using std::sin;
567c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using std::cos;
568c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  return ReturnType(sin(x.value()),x.derivatives() * cos(x.value()));)
569c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
570c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(exp,
571c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using std::exp;
572c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Scalar expx = exp(x.value());
573c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  return ReturnType(expx,x.derivatives() * expx);)
574c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
575c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(log,
576c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using std::log;
577c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  return ReturnType(log(x.value()),x.derivatives() * (Scalar(1)/x.value()));)
578c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
579c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename DerType>
580c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline const Eigen::AutoDiffScalar<Eigen::CwiseUnaryOp<Eigen::internal::scalar_multiple_op<typename Eigen::internal::traits<DerType>::Scalar>, const DerType> >
581c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathpow(const Eigen::AutoDiffScalar<DerType>& x, typename Eigen::internal::traits<DerType>::Scalar y)
582c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
583c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using namespace Eigen;
584c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename Eigen::internal::traits<DerType>::Scalar Scalar;
585c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  return AutoDiffScalar<CwiseUnaryOp<Eigen::internal::scalar_multiple_op<Scalar>, const DerType> >(
586c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    std::pow(x.value(),y),
587c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    x.derivatives() * (y * std::pow(x.value(),y-1)));
588c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
589c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
590c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
591c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename DerTypeA,typename DerTypeB>
592c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathinline const AutoDiffScalar<Matrix<typename internal::traits<DerTypeA>::Scalar,Dynamic,1> >
593c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathatan2(const AutoDiffScalar<DerTypeA>& a, const AutoDiffScalar<DerTypeB>& b)
594c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
595c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using std::atan2;
596c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using std::max;
597c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename internal::traits<DerTypeA>::Scalar Scalar;
598c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef AutoDiffScalar<Matrix<Scalar,Dynamic,1> > PlainADS;
599c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  PlainADS ret;
600c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  ret.value() = atan2(a.value(), b.value());
601c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
602c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Scalar tmp2 = a.value() * a.value();
603c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Scalar tmp3 = b.value() * b.value();
604c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Scalar tmp4 = tmp3/(tmp2+tmp3);
605c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
606c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  if (tmp4!=0)
607c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ret.derivatives() = (a.derivatives() * b.value() - a.value() * b.derivatives()) * (tmp2+tmp3);
608c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
609c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  return ret;
610c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
611c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
612c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(tan,
613c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using std::tan;
614c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using std::cos;
6157faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  return ReturnType(tan(x.value()),x.derivatives() * (Scalar(1)/numext::abs2(cos(x.value()))));)
616c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
617c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(asin,
618c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using std::sqrt;
619c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using std::asin;
6207faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  return ReturnType(asin(x.value()),x.derivatives() * (Scalar(1)/sqrt(1-numext::abs2(x.value()))));)
621c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
622c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan KamathEIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(acos,
623c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using std::sqrt;
624c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  using std::acos;
6257faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  return ReturnType(acos(x.value()),x.derivatives() * (Scalar(-1)/sqrt(1-numext::abs2(x.value()))));)
626c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
627c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#undef EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY
628c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
629c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename DerType> struct NumTraits<AutoDiffScalar<DerType> >
630c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  : NumTraits< typename NumTraits<typename DerType::Scalar>::Real >
631c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
632c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef AutoDiffScalar<Matrix<typename NumTraits<typename DerType::Scalar>::Real,DerType::RowsAtCompileTime,DerType::ColsAtCompileTime> > Real;
633c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef AutoDiffScalar<DerType> NonInteger;
634c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef AutoDiffScalar<DerType>& Nested;
635c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum{
636c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    RequireInitialization = 1
637c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  };
638c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
639c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
640c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
641c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
642c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // EIGEN_AUTODIFF_SCALAR_H
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