Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 1 | // This file is part of Eigen, a lightweight C++ template library |
| 2 | // for linear algebra. |
| 3 | // |
| 4 | // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr> |
| 5 | // |
| 6 | // This Source Code Form is subject to the terms of the Mozilla |
| 7 | // Public License v. 2.0. If a copy of the MPL was not distributed |
| 8 | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. |
| 9 | |
| 10 | #ifndef EIGEN_AUTODIFF_SCALAR_H |
| 11 | #define EIGEN_AUTODIFF_SCALAR_H |
| 12 | |
| 13 | namespace Eigen { |
| 14 | |
| 15 | namespace internal { |
| 16 | |
| 17 | template<typename A, typename B> |
| 18 | struct make_coherent_impl { |
| 19 | static void run(A&, B&) {} |
| 20 | }; |
| 21 | |
| 22 | // resize a to match b is a.size()==0, and conversely. |
| 23 | template<typename A, typename B> |
| 24 | void make_coherent(const A& a, const B&b) |
| 25 | { |
| 26 | make_coherent_impl<A,B>::run(a.const_cast_derived(), b.const_cast_derived()); |
| 27 | } |
| 28 | |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 29 | template<typename DerivativeType, bool Enable> struct auto_diff_special_op; |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 30 | |
| 31 | } // end namespace internal |
| 32 | |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 33 | template<typename DerivativeType> class AutoDiffScalar; |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 34 | |
| 35 | template<typename NewDerType> |
| 36 | inline AutoDiffScalar<NewDerType> MakeAutoDiffScalar(const typename NewDerType::Scalar& value, const NewDerType &der) { |
| 37 | return AutoDiffScalar<NewDerType>(value,der); |
| 38 | } |
| 39 | |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 40 | /** \class AutoDiffScalar |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 41 | * \brief A scalar type replacement with automatic differentiation capability |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 42 | * |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 43 | * \param DerivativeType the vector type used to store/represent the derivatives. The base scalar type |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 44 | * as well as the number of derivatives to compute are determined from this type. |
| 45 | * Typical choices include, e.g., \c Vector4f for 4 derivatives, or \c VectorXf |
| 46 | * if the number of derivatives is not known at compile time, and/or, the number |
| 47 | * of derivatives is large. |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 48 | * Note that DerivativeType can also be a reference (e.g., \c VectorXf&) to wrap a |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 49 | * existing vector into an AutoDiffScalar. |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 50 | * Finally, DerivativeType can also be any Eigen compatible expression. |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 51 | * |
| 52 | * This class represents a scalar value while tracking its respective derivatives using Eigen's expression |
| 53 | * template mechanism. |
| 54 | * |
| 55 | * It supports the following list of global math function: |
| 56 | * - std::abs, std::sqrt, std::pow, std::exp, std::log, std::sin, std::cos, |
| 57 | * - internal::abs, internal::sqrt, numext::pow, internal::exp, internal::log, internal::sin, internal::cos, |
| 58 | * - internal::conj, internal::real, internal::imag, numext::abs2. |
| 59 | * |
| 60 | * AutoDiffScalar can be used as the scalar type of an Eigen::Matrix object. However, |
| 61 | * in that case, the expression template mechanism only occurs at the top Matrix level, |
| 62 | * while derivatives are computed right away. |
| 63 | * |
| 64 | */ |
| 65 | |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 66 | template<typename DerivativeType> |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 67 | class AutoDiffScalar |
| 68 | : public internal::auto_diff_special_op |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 69 | <DerivativeType, !internal::is_same<typename internal::traits<typename internal::remove_all<DerivativeType>::type>::Scalar, |
| 70 | typename NumTraits<typename internal::traits<typename internal::remove_all<DerivativeType>::type>::Scalar>::Real>::value> |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 71 | { |
| 72 | public: |
| 73 | typedef internal::auto_diff_special_op |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 74 | <DerivativeType, !internal::is_same<typename internal::traits<typename internal::remove_all<DerivativeType>::type>::Scalar, |
| 75 | typename NumTraits<typename internal::traits<typename internal::remove_all<DerivativeType>::type>::Scalar>::Real>::value> Base; |
| 76 | typedef typename internal::remove_all<DerivativeType>::type DerType; |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 77 | typedef typename internal::traits<DerType>::Scalar Scalar; |
| 78 | typedef typename NumTraits<Scalar>::Real Real; |
| 79 | |
| 80 | using Base::operator+; |
| 81 | using Base::operator*; |
| 82 | |
| 83 | /** Default constructor without any initialization. */ |
| 84 | AutoDiffScalar() {} |
| 85 | |
| 86 | /** Constructs an active scalar from its \a value, |
| 87 | and initializes the \a nbDer derivatives such that it corresponds to the \a derNumber -th variable */ |
| 88 | AutoDiffScalar(const Scalar& value, int nbDer, int derNumber) |
| 89 | : m_value(value), m_derivatives(DerType::Zero(nbDer)) |
| 90 | { |
| 91 | m_derivatives.coeffRef(derNumber) = Scalar(1); |
| 92 | } |
| 93 | |
| 94 | /** Conversion from a scalar constant to an active scalar. |
| 95 | * The derivatives are set to zero. */ |
| 96 | /*explicit*/ AutoDiffScalar(const Real& value) |
| 97 | : m_value(value) |
| 98 | { |
| 99 | if(m_derivatives.size()>0) |
| 100 | m_derivatives.setZero(); |
| 101 | } |
| 102 | |
| 103 | /** Constructs an active scalar from its \a value and derivatives \a der */ |
| 104 | AutoDiffScalar(const Scalar& value, const DerType& der) |
| 105 | : m_value(value), m_derivatives(der) |
| 106 | {} |
| 107 | |
| 108 | template<typename OtherDerType> |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 109 | AutoDiffScalar(const AutoDiffScalar<OtherDerType>& other |
| 110 | #ifndef EIGEN_PARSED_BY_DOXYGEN |
| 111 | , typename internal::enable_if< |
| 112 | internal::is_same<Scalar, typename internal::traits<typename internal::remove_all<OtherDerType>::type>::Scalar>::value |
| 113 | && internal::is_convertible<OtherDerType,DerType>::value , void*>::type = 0 |
| 114 | #endif |
| 115 | ) |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 116 | : m_value(other.value()), m_derivatives(other.derivatives()) |
| 117 | {} |
| 118 | |
| 119 | friend std::ostream & operator << (std::ostream & s, const AutoDiffScalar& a) |
| 120 | { |
| 121 | return s << a.value(); |
| 122 | } |
| 123 | |
| 124 | AutoDiffScalar(const AutoDiffScalar& other) |
| 125 | : m_value(other.value()), m_derivatives(other.derivatives()) |
| 126 | {} |
| 127 | |
| 128 | template<typename OtherDerType> |
| 129 | inline AutoDiffScalar& operator=(const AutoDiffScalar<OtherDerType>& other) |
| 130 | { |
| 131 | m_value = other.value(); |
| 132 | m_derivatives = other.derivatives(); |
| 133 | return *this; |
| 134 | } |
| 135 | |
| 136 | inline AutoDiffScalar& operator=(const AutoDiffScalar& other) |
| 137 | { |
| 138 | m_value = other.value(); |
| 139 | m_derivatives = other.derivatives(); |
| 140 | return *this; |
| 141 | } |
| 142 | |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 143 | inline AutoDiffScalar& operator=(const Scalar& other) |
| 144 | { |
| 145 | m_value = other; |
| 146 | if(m_derivatives.size()>0) |
| 147 | m_derivatives.setZero(); |
| 148 | return *this; |
| 149 | } |
| 150 | |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 151 | // inline operator const Scalar& () const { return m_value; } |
| 152 | // inline operator Scalar& () { return m_value; } |
| 153 | |
| 154 | inline const Scalar& value() const { return m_value; } |
| 155 | inline Scalar& value() { return m_value; } |
| 156 | |
| 157 | inline const DerType& derivatives() const { return m_derivatives; } |
| 158 | inline DerType& derivatives() { return m_derivatives; } |
| 159 | |
| 160 | inline bool operator< (const Scalar& other) const { return m_value < other; } |
| 161 | inline bool operator<=(const Scalar& other) const { return m_value <= other; } |
| 162 | inline bool operator> (const Scalar& other) const { return m_value > other; } |
| 163 | inline bool operator>=(const Scalar& other) const { return m_value >= other; } |
| 164 | inline bool operator==(const Scalar& other) const { return m_value == other; } |
| 165 | inline bool operator!=(const Scalar& other) const { return m_value != other; } |
| 166 | |
| 167 | friend inline bool operator< (const Scalar& a, const AutoDiffScalar& b) { return a < b.value(); } |
| 168 | friend inline bool operator<=(const Scalar& a, const AutoDiffScalar& b) { return a <= b.value(); } |
| 169 | friend inline bool operator> (const Scalar& a, const AutoDiffScalar& b) { return a > b.value(); } |
| 170 | friend inline bool operator>=(const Scalar& a, const AutoDiffScalar& b) { return a >= b.value(); } |
| 171 | friend inline bool operator==(const Scalar& a, const AutoDiffScalar& b) { return a == b.value(); } |
| 172 | friend inline bool operator!=(const Scalar& a, const AutoDiffScalar& b) { return a != b.value(); } |
| 173 | |
| 174 | template<typename OtherDerType> inline bool operator< (const AutoDiffScalar<OtherDerType>& b) const { return m_value < b.value(); } |
| 175 | template<typename OtherDerType> inline bool operator<=(const AutoDiffScalar<OtherDerType>& b) const { return m_value <= b.value(); } |
| 176 | template<typename OtherDerType> inline bool operator> (const AutoDiffScalar<OtherDerType>& b) const { return m_value > b.value(); } |
| 177 | template<typename OtherDerType> inline bool operator>=(const AutoDiffScalar<OtherDerType>& b) const { return m_value >= b.value(); } |
| 178 | template<typename OtherDerType> inline bool operator==(const AutoDiffScalar<OtherDerType>& b) const { return m_value == b.value(); } |
| 179 | template<typename OtherDerType> inline bool operator!=(const AutoDiffScalar<OtherDerType>& b) const { return m_value != b.value(); } |
| 180 | |
| 181 | inline const AutoDiffScalar<DerType&> operator+(const Scalar& other) const |
| 182 | { |
| 183 | return AutoDiffScalar<DerType&>(m_value + other, m_derivatives); |
| 184 | } |
| 185 | |
| 186 | friend inline const AutoDiffScalar<DerType&> operator+(const Scalar& a, const AutoDiffScalar& b) |
| 187 | { |
| 188 | return AutoDiffScalar<DerType&>(a + b.value(), b.derivatives()); |
| 189 | } |
| 190 | |
| 191 | // inline const AutoDiffScalar<DerType&> operator+(const Real& other) const |
| 192 | // { |
| 193 | // return AutoDiffScalar<DerType&>(m_value + other, m_derivatives); |
| 194 | // } |
| 195 | |
| 196 | // friend inline const AutoDiffScalar<DerType&> operator+(const Real& a, const AutoDiffScalar& b) |
| 197 | // { |
| 198 | // return AutoDiffScalar<DerType&>(a + b.value(), b.derivatives()); |
| 199 | // } |
| 200 | |
| 201 | inline AutoDiffScalar& operator+=(const Scalar& other) |
| 202 | { |
| 203 | value() += other; |
| 204 | return *this; |
| 205 | } |
| 206 | |
| 207 | template<typename OtherDerType> |
| 208 | inline const AutoDiffScalar<CwiseBinaryOp<internal::scalar_sum_op<Scalar>,const DerType,const typename internal::remove_all<OtherDerType>::type> > |
| 209 | operator+(const AutoDiffScalar<OtherDerType>& other) const |
| 210 | { |
| 211 | internal::make_coherent(m_derivatives, other.derivatives()); |
| 212 | return AutoDiffScalar<CwiseBinaryOp<internal::scalar_sum_op<Scalar>,const DerType,const typename internal::remove_all<OtherDerType>::type> >( |
| 213 | m_value + other.value(), |
| 214 | m_derivatives + other.derivatives()); |
| 215 | } |
| 216 | |
| 217 | template<typename OtherDerType> |
| 218 | inline AutoDiffScalar& |
| 219 | operator+=(const AutoDiffScalar<OtherDerType>& other) |
| 220 | { |
| 221 | (*this) = (*this) + other; |
| 222 | return *this; |
| 223 | } |
| 224 | |
| 225 | inline const AutoDiffScalar<DerType&> operator-(const Scalar& b) const |
| 226 | { |
| 227 | return AutoDiffScalar<DerType&>(m_value - b, m_derivatives); |
| 228 | } |
| 229 | |
| 230 | friend inline const AutoDiffScalar<CwiseUnaryOp<internal::scalar_opposite_op<Scalar>, const DerType> > |
| 231 | operator-(const Scalar& a, const AutoDiffScalar& b) |
| 232 | { |
| 233 | return AutoDiffScalar<CwiseUnaryOp<internal::scalar_opposite_op<Scalar>, const DerType> > |
| 234 | (a - b.value(), -b.derivatives()); |
| 235 | } |
| 236 | |
| 237 | inline AutoDiffScalar& operator-=(const Scalar& other) |
| 238 | { |
| 239 | value() -= other; |
| 240 | return *this; |
| 241 | } |
| 242 | |
| 243 | template<typename OtherDerType> |
| 244 | inline const AutoDiffScalar<CwiseBinaryOp<internal::scalar_difference_op<Scalar>, const DerType,const typename internal::remove_all<OtherDerType>::type> > |
| 245 | operator-(const AutoDiffScalar<OtherDerType>& other) const |
| 246 | { |
| 247 | internal::make_coherent(m_derivatives, other.derivatives()); |
| 248 | return AutoDiffScalar<CwiseBinaryOp<internal::scalar_difference_op<Scalar>, const DerType,const typename internal::remove_all<OtherDerType>::type> >( |
| 249 | m_value - other.value(), |
| 250 | m_derivatives - other.derivatives()); |
| 251 | } |
| 252 | |
| 253 | template<typename OtherDerType> |
| 254 | inline AutoDiffScalar& |
| 255 | operator-=(const AutoDiffScalar<OtherDerType>& other) |
| 256 | { |
| 257 | *this = *this - other; |
| 258 | return *this; |
| 259 | } |
| 260 | |
| 261 | inline const AutoDiffScalar<CwiseUnaryOp<internal::scalar_opposite_op<Scalar>, const DerType> > |
| 262 | operator-() const |
| 263 | { |
| 264 | return AutoDiffScalar<CwiseUnaryOp<internal::scalar_opposite_op<Scalar>, const DerType> >( |
| 265 | -m_value, |
| 266 | -m_derivatives); |
| 267 | } |
| 268 | |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 269 | inline const AutoDiffScalar<EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DerType,Scalar,product) > |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 270 | operator*(const Scalar& other) const |
| 271 | { |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 272 | return MakeAutoDiffScalar(m_value * other, m_derivatives * other); |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 273 | } |
| 274 | |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 275 | friend inline const AutoDiffScalar<EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DerType,Scalar,product) > |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 276 | operator*(const Scalar& other, const AutoDiffScalar& a) |
| 277 | { |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 278 | return MakeAutoDiffScalar(a.value() * other, a.derivatives() * other); |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 279 | } |
| 280 | |
| 281 | // inline const AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type > |
| 282 | // operator*(const Real& other) const |
| 283 | // { |
| 284 | // return AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >( |
| 285 | // m_value * other, |
| 286 | // (m_derivatives * other)); |
| 287 | // } |
| 288 | // |
| 289 | // friend inline const AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type > |
| 290 | // operator*(const Real& other, const AutoDiffScalar& a) |
| 291 | // { |
| 292 | // return AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >( |
| 293 | // a.value() * other, |
| 294 | // a.derivatives() * other); |
| 295 | // } |
| 296 | |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 297 | inline const AutoDiffScalar<EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DerType,Scalar,product) > |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 298 | operator/(const Scalar& other) const |
| 299 | { |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 300 | return MakeAutoDiffScalar(m_value / other, (m_derivatives * (Scalar(1)/other))); |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 301 | } |
| 302 | |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 303 | friend inline const AutoDiffScalar<EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DerType,Scalar,product) > |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 304 | operator/(const Scalar& other, const AutoDiffScalar& a) |
| 305 | { |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 306 | return MakeAutoDiffScalar(other / a.value(), a.derivatives() * (Scalar(-other) / (a.value()*a.value()))); |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 307 | } |
| 308 | |
| 309 | // inline const AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type > |
| 310 | // operator/(const Real& other) const |
| 311 | // { |
| 312 | // return AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >( |
| 313 | // m_value / other, |
| 314 | // (m_derivatives * (Real(1)/other))); |
| 315 | // } |
| 316 | // |
| 317 | // friend inline const AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type > |
| 318 | // operator/(const Real& other, const AutoDiffScalar& a) |
| 319 | // { |
| 320 | // return AutoDiffScalar<typename CwiseUnaryOp<internal::scalar_multiple_op<Real>, DerType>::Type >( |
| 321 | // other / a.value(), |
| 322 | // a.derivatives() * (-Real(1)/other)); |
| 323 | // } |
| 324 | |
| 325 | template<typename OtherDerType> |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 326 | inline const AutoDiffScalar<EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE( |
| 327 | CwiseBinaryOp<internal::scalar_difference_op<Scalar> EIGEN_COMMA |
| 328 | const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DerType,Scalar,product) EIGEN_COMMA |
| 329 | const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(typename internal::remove_all<OtherDerType>::type,Scalar,product) >,Scalar,product) > |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 330 | operator/(const AutoDiffScalar<OtherDerType>& other) const |
| 331 | { |
| 332 | internal::make_coherent(m_derivatives, other.derivatives()); |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 333 | return MakeAutoDiffScalar( |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 334 | m_value / other.value(), |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 335 | ((m_derivatives * other.value()) - (other.derivatives() * m_value)) |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 336 | * (Scalar(1)/(other.value()*other.value()))); |
| 337 | } |
| 338 | |
| 339 | template<typename OtherDerType> |
| 340 | inline const AutoDiffScalar<CwiseBinaryOp<internal::scalar_sum_op<Scalar>, |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 341 | const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DerType,Scalar,product), |
| 342 | const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(typename internal::remove_all<OtherDerType>::type,Scalar,product) > > |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 343 | operator*(const AutoDiffScalar<OtherDerType>& other) const |
| 344 | { |
| 345 | internal::make_coherent(m_derivatives, other.derivatives()); |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 346 | return MakeAutoDiffScalar( |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 347 | m_value * other.value(), |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 348 | (m_derivatives * other.value()) + (other.derivatives() * m_value)); |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 349 | } |
| 350 | |
| 351 | inline AutoDiffScalar& operator*=(const Scalar& other) |
| 352 | { |
| 353 | *this = *this * other; |
| 354 | return *this; |
| 355 | } |
| 356 | |
| 357 | template<typename OtherDerType> |
| 358 | inline AutoDiffScalar& operator*=(const AutoDiffScalar<OtherDerType>& other) |
| 359 | { |
| 360 | *this = *this * other; |
| 361 | return *this; |
| 362 | } |
| 363 | |
| 364 | inline AutoDiffScalar& operator/=(const Scalar& other) |
| 365 | { |
| 366 | *this = *this / other; |
| 367 | return *this; |
| 368 | } |
| 369 | |
| 370 | template<typename OtherDerType> |
| 371 | inline AutoDiffScalar& operator/=(const AutoDiffScalar<OtherDerType>& other) |
| 372 | { |
| 373 | *this = *this / other; |
| 374 | return *this; |
| 375 | } |
| 376 | |
| 377 | protected: |
| 378 | Scalar m_value; |
| 379 | DerType m_derivatives; |
| 380 | |
| 381 | }; |
| 382 | |
| 383 | namespace internal { |
| 384 | |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 385 | template<typename DerivativeType> |
| 386 | struct auto_diff_special_op<DerivativeType, true> |
| 387 | // : auto_diff_scalar_op<DerivativeType, typename NumTraits<Scalar>::Real, |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 388 | // is_same<Scalar,typename NumTraits<Scalar>::Real>::value> |
| 389 | { |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 390 | typedef typename remove_all<DerivativeType>::type DerType; |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 391 | typedef typename traits<DerType>::Scalar Scalar; |
| 392 | typedef typename NumTraits<Scalar>::Real Real; |
| 393 | |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 394 | // typedef auto_diff_scalar_op<DerivativeType, typename NumTraits<Scalar>::Real, |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 395 | // is_same<Scalar,typename NumTraits<Scalar>::Real>::value> Base; |
| 396 | |
| 397 | // using Base::operator+; |
| 398 | // using Base::operator+=; |
| 399 | // using Base::operator-; |
| 400 | // using Base::operator-=; |
| 401 | // using Base::operator*; |
| 402 | // using Base::operator*=; |
| 403 | |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 404 | const AutoDiffScalar<DerivativeType>& derived() const { return *static_cast<const AutoDiffScalar<DerivativeType>*>(this); } |
| 405 | AutoDiffScalar<DerivativeType>& derived() { return *static_cast<AutoDiffScalar<DerivativeType>*>(this); } |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 406 | |
| 407 | |
| 408 | inline const AutoDiffScalar<DerType&> operator+(const Real& other) const |
| 409 | { |
| 410 | return AutoDiffScalar<DerType&>(derived().value() + other, derived().derivatives()); |
| 411 | } |
| 412 | |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 413 | friend inline const AutoDiffScalar<DerType&> operator+(const Real& a, const AutoDiffScalar<DerivativeType>& b) |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 414 | { |
| 415 | return AutoDiffScalar<DerType&>(a + b.value(), b.derivatives()); |
| 416 | } |
| 417 | |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 418 | inline AutoDiffScalar<DerivativeType>& operator+=(const Real& other) |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 419 | { |
| 420 | derived().value() += other; |
| 421 | return derived(); |
| 422 | } |
| 423 | |
| 424 | |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 425 | inline const AutoDiffScalar<typename CwiseUnaryOp<bind2nd_op<scalar_product_op<Scalar,Real> >, DerType>::Type > |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 426 | operator*(const Real& other) const |
| 427 | { |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 428 | return AutoDiffScalar<typename CwiseUnaryOp<bind2nd_op<scalar_product_op<Scalar,Real> >, DerType>::Type >( |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 429 | derived().value() * other, |
| 430 | derived().derivatives() * other); |
| 431 | } |
| 432 | |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 433 | friend inline const AutoDiffScalar<typename CwiseUnaryOp<bind1st_op<scalar_product_op<Real,Scalar> >, DerType>::Type > |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 434 | operator*(const Real& other, const AutoDiffScalar<DerivativeType>& a) |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 435 | { |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 436 | return AutoDiffScalar<typename CwiseUnaryOp<bind1st_op<scalar_product_op<Real,Scalar> >, DerType>::Type >( |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 437 | a.value() * other, |
| 438 | a.derivatives() * other); |
| 439 | } |
| 440 | |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 441 | inline AutoDiffScalar<DerivativeType>& operator*=(const Scalar& other) |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 442 | { |
| 443 | *this = *this * other; |
| 444 | return derived(); |
| 445 | } |
| 446 | }; |
| 447 | |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 448 | template<typename DerivativeType> |
| 449 | struct auto_diff_special_op<DerivativeType, false> |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 450 | { |
| 451 | void operator*() const; |
| 452 | void operator-() const; |
| 453 | void operator+() const; |
| 454 | }; |
| 455 | |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 456 | template<typename BinOp, typename A, typename B, typename RefType> |
| 457 | void make_coherent_expression(CwiseBinaryOp<BinOp,A,B> xpr, const RefType &ref) |
| 458 | { |
| 459 | make_coherent(xpr.const_cast_derived().lhs(), ref); |
| 460 | make_coherent(xpr.const_cast_derived().rhs(), ref); |
| 461 | } |
| 462 | |
| 463 | template<typename UnaryOp, typename A, typename RefType> |
| 464 | void make_coherent_expression(const CwiseUnaryOp<UnaryOp,A> &xpr, const RefType &ref) |
| 465 | { |
| 466 | make_coherent(xpr.nestedExpression().const_cast_derived(), ref); |
| 467 | } |
| 468 | |
| 469 | // needed for compilation only |
| 470 | template<typename UnaryOp, typename A, typename RefType> |
| 471 | void make_coherent_expression(const CwiseNullaryOp<UnaryOp,A> &, const RefType &) |
| 472 | {} |
| 473 | |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 474 | template<typename A_Scalar, int A_Rows, int A_Cols, int A_Options, int A_MaxRows, int A_MaxCols, typename B> |
| 475 | struct make_coherent_impl<Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols>, B> { |
| 476 | typedef Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols> A; |
| 477 | static void run(A& a, B& b) { |
| 478 | if((A_Rows==Dynamic || A_Cols==Dynamic) && (a.size()==0)) |
| 479 | { |
| 480 | a.resize(b.size()); |
| 481 | a.setZero(); |
| 482 | } |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 483 | else if (B::SizeAtCompileTime==Dynamic && a.size()!=0 && b.size()==0) |
| 484 | { |
| 485 | make_coherent_expression(b,a); |
| 486 | } |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 487 | } |
| 488 | }; |
| 489 | |
| 490 | template<typename A, typename B_Scalar, int B_Rows, int B_Cols, int B_Options, int B_MaxRows, int B_MaxCols> |
| 491 | struct make_coherent_impl<A, Matrix<B_Scalar, B_Rows, B_Cols, B_Options, B_MaxRows, B_MaxCols> > { |
| 492 | typedef Matrix<B_Scalar, B_Rows, B_Cols, B_Options, B_MaxRows, B_MaxCols> B; |
| 493 | static void run(A& a, B& b) { |
| 494 | if((B_Rows==Dynamic || B_Cols==Dynamic) && (b.size()==0)) |
| 495 | { |
| 496 | b.resize(a.size()); |
| 497 | b.setZero(); |
| 498 | } |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 499 | else if (A::SizeAtCompileTime==Dynamic && b.size()!=0 && a.size()==0) |
| 500 | { |
| 501 | make_coherent_expression(a,b); |
| 502 | } |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 503 | } |
| 504 | }; |
| 505 | |
| 506 | template<typename A_Scalar, int A_Rows, int A_Cols, int A_Options, int A_MaxRows, int A_MaxCols, |
| 507 | typename B_Scalar, int B_Rows, int B_Cols, int B_Options, int B_MaxRows, int B_MaxCols> |
| 508 | struct make_coherent_impl<Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols>, |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 509 | Matrix<B_Scalar, B_Rows, B_Cols, B_Options, B_MaxRows, B_MaxCols> > { |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 510 | typedef Matrix<A_Scalar, A_Rows, A_Cols, A_Options, A_MaxRows, A_MaxCols> A; |
| 511 | typedef Matrix<B_Scalar, B_Rows, B_Cols, B_Options, B_MaxRows, B_MaxCols> B; |
| 512 | static void run(A& a, B& b) { |
| 513 | if((A_Rows==Dynamic || A_Cols==Dynamic) && (a.size()==0)) |
| 514 | { |
| 515 | a.resize(b.size()); |
| 516 | a.setZero(); |
| 517 | } |
| 518 | else if((B_Rows==Dynamic || B_Cols==Dynamic) && (b.size()==0)) |
| 519 | { |
| 520 | b.resize(a.size()); |
| 521 | b.setZero(); |
| 522 | } |
| 523 | } |
| 524 | }; |
| 525 | |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 526 | } // end namespace internal |
| 527 | |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 528 | template<typename DerType, typename BinOp> |
| 529 | struct ScalarBinaryOpTraits<AutoDiffScalar<DerType>,typename DerType::Scalar,BinOp> |
| 530 | { |
| 531 | typedef AutoDiffScalar<DerType> ReturnType; |
| 532 | }; |
| 533 | |
| 534 | template<typename DerType, typename BinOp> |
| 535 | struct ScalarBinaryOpTraits<typename DerType::Scalar,AutoDiffScalar<DerType>, BinOp> |
| 536 | { |
| 537 | typedef AutoDiffScalar<DerType> ReturnType; |
| 538 | }; |
| 539 | |
| 540 | |
| 541 | // The following is an attempt to let Eigen's known about expression template, but that's more tricky! |
| 542 | |
| 543 | // template<typename DerType, typename BinOp> |
| 544 | // struct ScalarBinaryOpTraits<AutoDiffScalar<DerType>,AutoDiffScalar<DerType>, BinOp> |
| 545 | // { |
| 546 | // enum { Defined = 1 }; |
| 547 | // typedef AutoDiffScalar<typename DerType::PlainObject> ReturnType; |
| 548 | // }; |
| 549 | // |
| 550 | // template<typename DerType1,typename DerType2, typename BinOp> |
| 551 | // struct ScalarBinaryOpTraits<AutoDiffScalar<DerType1>,AutoDiffScalar<DerType2>, BinOp> |
| 552 | // { |
| 553 | // enum { Defined = 1 };//internal::is_same<typename DerType1::Scalar,typename DerType2::Scalar>::value }; |
| 554 | // typedef AutoDiffScalar<typename DerType1::PlainObject> ReturnType; |
| 555 | // }; |
| 556 | |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 557 | #define EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(FUNC,CODE) \ |
| 558 | template<typename DerType> \ |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 559 | inline const Eigen::AutoDiffScalar< \ |
| 560 | EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(typename Eigen::internal::remove_all<DerType>::type, typename Eigen::internal::traits<typename Eigen::internal::remove_all<DerType>::type>::Scalar, product) > \ |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 561 | FUNC(const Eigen::AutoDiffScalar<DerType>& x) { \ |
| 562 | using namespace Eigen; \ |
| 563 | typedef typename Eigen::internal::traits<typename Eigen::internal::remove_all<DerType>::type>::Scalar Scalar; \ |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 564 | EIGEN_UNUSED_VARIABLE(sizeof(Scalar)); \ |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 565 | CODE; \ |
| 566 | } |
| 567 | |
| 568 | template<typename DerType> |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 569 | struct CleanedUpDerType { |
| 570 | typedef AutoDiffScalar<typename Eigen::internal::remove_all<DerType>::type::PlainObject> type; |
| 571 | }; |
| 572 | |
| 573 | template<typename DerType> |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 574 | inline const AutoDiffScalar<DerType>& conj(const AutoDiffScalar<DerType>& x) { return x; } |
| 575 | template<typename DerType> |
| 576 | inline const AutoDiffScalar<DerType>& real(const AutoDiffScalar<DerType>& x) { return x; } |
| 577 | template<typename DerType> |
| 578 | inline typename DerType::Scalar imag(const AutoDiffScalar<DerType>&) { return 0.; } |
| 579 | template<typename DerType, typename T> |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 580 | inline typename CleanedUpDerType<DerType>::type (min)(const AutoDiffScalar<DerType>& x, const T& y) { |
| 581 | typedef typename CleanedUpDerType<DerType>::type ADS; |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 582 | return (x <= y ? ADS(x) : ADS(y)); |
| 583 | } |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 584 | template<typename DerType, typename T> |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 585 | inline typename CleanedUpDerType<DerType>::type (max)(const AutoDiffScalar<DerType>& x, const T& y) { |
| 586 | typedef typename CleanedUpDerType<DerType>::type ADS; |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 587 | return (x >= y ? ADS(x) : ADS(y)); |
| 588 | } |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 589 | template<typename DerType, typename T> |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 590 | inline typename CleanedUpDerType<DerType>::type (min)(const T& x, const AutoDiffScalar<DerType>& y) { |
| 591 | typedef typename CleanedUpDerType<DerType>::type ADS; |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 592 | return (x < y ? ADS(x) : ADS(y)); |
| 593 | } |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 594 | template<typename DerType, typename T> |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 595 | inline typename CleanedUpDerType<DerType>::type (max)(const T& x, const AutoDiffScalar<DerType>& y) { |
| 596 | typedef typename CleanedUpDerType<DerType>::type ADS; |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 597 | return (x > y ? ADS(x) : ADS(y)); |
| 598 | } |
| 599 | template<typename DerType> |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 600 | inline typename CleanedUpDerType<DerType>::type (min)(const AutoDiffScalar<DerType>& x, const AutoDiffScalar<DerType>& y) { |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 601 | return (x.value() < y.value() ? x : y); |
| 602 | } |
| 603 | template<typename DerType> |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 604 | inline typename CleanedUpDerType<DerType>::type (max)(const AutoDiffScalar<DerType>& x, const AutoDiffScalar<DerType>& y) { |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 605 | return (x.value() >= y.value() ? x : y); |
| 606 | } |
| 607 | |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 608 | |
| 609 | EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(abs, |
| 610 | using std::abs; |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 611 | return Eigen::MakeAutoDiffScalar(abs(x.value()), x.derivatives() * (x.value()<0 ? -1 : 1) );) |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 612 | |
| 613 | EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(abs2, |
| 614 | using numext::abs2; |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 615 | return Eigen::MakeAutoDiffScalar(abs2(x.value()), x.derivatives() * (Scalar(2)*x.value()));) |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 616 | |
| 617 | EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(sqrt, |
| 618 | using std::sqrt; |
| 619 | Scalar sqrtx = sqrt(x.value()); |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 620 | return Eigen::MakeAutoDiffScalar(sqrtx,x.derivatives() * (Scalar(0.5) / sqrtx));) |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 621 | |
| 622 | EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(cos, |
| 623 | using std::cos; |
| 624 | using std::sin; |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 625 | return Eigen::MakeAutoDiffScalar(cos(x.value()), x.derivatives() * (-sin(x.value())));) |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 626 | |
| 627 | EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(sin, |
| 628 | using std::sin; |
| 629 | using std::cos; |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 630 | return Eigen::MakeAutoDiffScalar(sin(x.value()),x.derivatives() * cos(x.value()));) |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 631 | |
| 632 | EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(exp, |
| 633 | using std::exp; |
| 634 | Scalar expx = exp(x.value()); |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 635 | return Eigen::MakeAutoDiffScalar(expx,x.derivatives() * expx);) |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 636 | |
| 637 | EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(log, |
| 638 | using std::log; |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 639 | return Eigen::MakeAutoDiffScalar(log(x.value()),x.derivatives() * (Scalar(1)/x.value()));) |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 640 | |
| 641 | template<typename DerType> |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 642 | inline const Eigen::AutoDiffScalar< |
| 643 | EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(typename internal::remove_all<DerType>::type,typename internal::traits<typename internal::remove_all<DerType>::type>::Scalar,product) > |
| 644 | pow(const Eigen::AutoDiffScalar<DerType> &x, const typename internal::traits<typename internal::remove_all<DerType>::type>::Scalar &y) |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 645 | { |
| 646 | using namespace Eigen; |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 647 | using std::pow; |
| 648 | return Eigen::MakeAutoDiffScalar(pow(x.value(),y), x.derivatives() * (y * pow(x.value(),y-1))); |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 649 | } |
| 650 | |
| 651 | |
| 652 | template<typename DerTypeA,typename DerTypeB> |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 653 | inline const AutoDiffScalar<Matrix<typename internal::traits<typename internal::remove_all<DerTypeA>::type>::Scalar,Dynamic,1> > |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 654 | atan2(const AutoDiffScalar<DerTypeA>& a, const AutoDiffScalar<DerTypeB>& b) |
| 655 | { |
| 656 | using std::atan2; |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 657 | typedef typename internal::traits<typename internal::remove_all<DerTypeA>::type>::Scalar Scalar; |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 658 | typedef AutoDiffScalar<Matrix<Scalar,Dynamic,1> > PlainADS; |
| 659 | PlainADS ret; |
| 660 | ret.value() = atan2(a.value(), b.value()); |
| 661 | |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 662 | Scalar squared_hypot = a.value() * a.value() + b.value() * b.value(); |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 663 | |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 664 | // if (squared_hypot==0) the derivation is undefined and the following results in a NaN: |
| 665 | ret.derivatives() = (a.derivatives() * b.value() - a.value() * b.derivatives()) / squared_hypot; |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 666 | |
| 667 | return ret; |
| 668 | } |
| 669 | |
| 670 | EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(tan, |
| 671 | using std::tan; |
| 672 | using std::cos; |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 673 | return Eigen::MakeAutoDiffScalar(tan(x.value()),x.derivatives() * (Scalar(1)/numext::abs2(cos(x.value()))));) |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 674 | |
| 675 | EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(asin, |
| 676 | using std::sqrt; |
| 677 | using std::asin; |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 678 | return Eigen::MakeAutoDiffScalar(asin(x.value()),x.derivatives() * (Scalar(1)/sqrt(1-numext::abs2(x.value()))));) |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 679 | |
| 680 | EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(acos, |
| 681 | using std::sqrt; |
| 682 | using std::acos; |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 683 | return Eigen::MakeAutoDiffScalar(acos(x.value()),x.derivatives() * (Scalar(-1)/sqrt(1-numext::abs2(x.value()))));) |
| 684 | |
| 685 | EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(tanh, |
| 686 | using std::cosh; |
| 687 | using std::tanh; |
| 688 | return Eigen::MakeAutoDiffScalar(tanh(x.value()),x.derivatives() * (Scalar(1)/numext::abs2(cosh(x.value()))));) |
| 689 | |
| 690 | EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(sinh, |
| 691 | using std::sinh; |
| 692 | using std::cosh; |
| 693 | return Eigen::MakeAutoDiffScalar(sinh(x.value()),x.derivatives() * cosh(x.value()));) |
| 694 | |
| 695 | EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(cosh, |
| 696 | using std::sinh; |
| 697 | using std::cosh; |
| 698 | return Eigen::MakeAutoDiffScalar(cosh(x.value()),x.derivatives() * sinh(x.value()));) |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 699 | |
| 700 | #undef EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY |
| 701 | |
| 702 | template<typename DerType> struct NumTraits<AutoDiffScalar<DerType> > |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 703 | : NumTraits< typename NumTraits<typename internal::remove_all<DerType>::type::Scalar>::Real > |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 704 | { |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 705 | typedef typename internal::remove_all<DerType>::type DerTypeCleaned; |
| 706 | typedef AutoDiffScalar<Matrix<typename NumTraits<typename DerTypeCleaned::Scalar>::Real,DerTypeCleaned::RowsAtCompileTime,DerTypeCleaned::ColsAtCompileTime, |
| 707 | 0, DerTypeCleaned::MaxRowsAtCompileTime, DerTypeCleaned::MaxColsAtCompileTime> > Real; |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 708 | typedef AutoDiffScalar<DerType> NonInteger; |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 709 | typedef AutoDiffScalar<DerType> Nested; |
| 710 | typedef typename NumTraits<typename DerTypeCleaned::Scalar>::Literal Literal; |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 711 | enum{ |
| 712 | RequireInitialization = 1 |
| 713 | }; |
| 714 | }; |
| 715 | |
| 716 | } |
| 717 | |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 718 | namespace std { |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 719 | |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 720 | template <typename T> |
| 721 | class numeric_limits<Eigen::AutoDiffScalar<T> > |
| 722 | : public numeric_limits<typename T::Scalar> {}; |
| 723 | |
Austin Schuh | c55b017 | 2022-02-20 17:52:35 -0800 | [diff] [blame^] | 724 | template <typename T> |
| 725 | class numeric_limits<Eigen::AutoDiffScalar<T&> > |
| 726 | : public numeric_limits<typename T::Scalar> {}; |
| 727 | |
Austin Schuh | 189376f | 2018-12-20 22:11:15 +1100 | [diff] [blame] | 728 | } // namespace std |
| 729 | |
Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 730 | #endif // EIGEN_AUTODIFF_SCALAR_H |