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https://gitlab.com/libeigen/eigen.git
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add atan2 support in AutoDiff and remove superfluous std:: specializations
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@@ -503,8 +503,6 @@ struct scalar_product_traits<AutoDiffScalar<DerType>,T>
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} // end namespace internal
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} // end namespace Eigen
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#define EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(FUNC,CODE) \
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template<typename DerType> \
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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> > \
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@@ -515,94 +513,78 @@ struct scalar_product_traits<AutoDiffScalar<DerType>,T>
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CODE; \
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}
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namespace std
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{
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EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(abs,
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return ReturnType(std::abs(x.value()), x.derivatives() * (sign(x.value())));)
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EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(sqrt,
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Scalar sqrtx = std::sqrt(x.value());
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return ReturnType(sqrtx,x.derivatives() * (Scalar(0.5) / sqrtx));)
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EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(cos,
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return ReturnType(std::cos(x.value()), x.derivatives() * (-std::sin(x.value())));)
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EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(sin,
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return ReturnType(std::sin(x.value()),x.derivatives() * std::cos(x.value()));)
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EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(exp,
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Scalar expx = std::exp(x.value());
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return ReturnType(expx,x.derivatives() * expx);)
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EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(log,
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return ReturnType(std::log(x.value()),x.derivatives() * (Scalar(1)/x.value()));)
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template<typename DerType>
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inline const Eigen::AutoDiffScalar<Eigen::CwiseUnaryOp<Eigen::internal::scalar_multiple_op<typename Eigen::internal::traits<DerType>::Scalar>, const DerType> >
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pow(const Eigen::AutoDiffScalar<DerType>& x, typename Eigen::internal::traits<DerType>::Scalar y)
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{
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using namespace Eigen;
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typedef typename Eigen::internal::traits<DerType>::Scalar Scalar;
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return AutoDiffScalar<CwiseUnaryOp<Eigen::internal::scalar_multiple_op<Scalar>, const DerType> >(
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std::pow(x.value(),y),
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x.derivatives() * (y * std::pow(x.value(),y-1)));
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}
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}
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#undef EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY
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#define EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(FUNC,CODE) \
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template<typename DerType> \
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struct FUNC##_impl<Eigen::AutoDiffScalar<DerType> > \
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{ \
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static 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> > \
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run(const Eigen::AutoDiffScalar<DerType>& x) { \
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using namespace Eigen; \
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typedef typename Eigen::internal::traits<typename Eigen::internal::remove_all<DerType>::type>::Scalar Scalar; \
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typedef AutoDiffScalar<CwiseUnaryOp<Eigen::internal::scalar_multiple_op<Scalar>, const typename Eigen::internal::remove_all<DerType>::type> > ReturnType; \
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CODE; \
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} };
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namespace Eigen {
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namespace internal {
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template<typename DerType>
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inline const AutoDiffScalar<DerType>& conj(const AutoDiffScalar<DerType>& x) { return x; }
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template<typename DerType>
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inline const AutoDiffScalar<DerType>& real(const AutoDiffScalar<DerType>& x) { return x; }
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template<typename DerType>
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inline typename DerType::Scalar imag(const AutoDiffScalar<DerType>&) { return 0.; }
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EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(abs,
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using std::abs;
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return ReturnType(abs(x.value()), x.derivatives() * (sign(x.value())));)
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EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(abs2,
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using internal::abs2;
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return ReturnType(abs2(x.value()), x.derivatives() * (Scalar(2)*x.value()));)
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EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(sqrt,
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using std::sqrt;
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Scalar sqrtx = sqrt(x.value());
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return ReturnType(sqrtx,x.derivatives() * (Scalar(0.5) / sqrtx));)
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EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(cos,
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using std::cos;
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using std::sin;
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return ReturnType(cos(x.value()), x.derivatives() * (-sin(x.value())));)
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EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(sin,
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using std::sin;
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using std::cos;
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return ReturnType(sin(x.value()),x.derivatives() * cos(x.value()));)
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EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(exp,
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using std::exp;
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Scalar expx = exp(x.value());
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return ReturnType(expx,x.derivatives() * expx);)
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EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(log,
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using std::log;
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return ReturnType(log(x.value()),x.derivatives() * (Scalar(1)/x.value()));)
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template<typename DerType>
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inline const AutoDiffScalar<CwiseUnaryOp<scalar_multiple_op<typename traits<DerType>::Scalar>, DerType> >
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pow(const AutoDiffScalar<DerType>& x, typename traits<DerType>::Scalar y)
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{ return std::pow(x,y);}
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inline const Eigen::AutoDiffScalar<Eigen::CwiseUnaryOp<Eigen::internal::scalar_multiple_op<typename Eigen::internal::traits<DerType>::Scalar>, const DerType> >
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pow(const Eigen::AutoDiffScalar<DerType>& x, typename Eigen::internal::traits<DerType>::Scalar y)
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{
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using namespace Eigen;
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typedef typename Eigen::internal::traits<DerType>::Scalar Scalar;
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return AutoDiffScalar<CwiseUnaryOp<Eigen::internal::scalar_multiple_op<Scalar>, const DerType> >(
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std::pow(x.value(),y),
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x.derivatives() * (y * std::pow(x.value(),y-1)));
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}
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} // end namespace internal
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template<typename DerTypeA,typename DerTypeB>
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inline const AutoDiffScalar<Matrix<typename internal::traits<DerTypeA>::Scalar,Dynamic,1> >
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atan2(const AutoDiffScalar<DerTypeA>& a, const AutoDiffScalar<DerTypeB>& b)
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{
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using std::atan2;
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typedef typename internal::traits<DerTypeA>::Scalar Scalar;
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typedef AutoDiffScalar<Matrix<Scalar,Dynamic,1> > PlainADS;
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PlainADS ret;
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ret.value() = atan2(a.value(), b.value());
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Scalar tmp2 = a.value() * a.value();
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Scalar tmp3 = b.value() * b.value();
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Scalar tmp4 = tmp3/(tmp2+tmp3);
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if (tmp4!=0)
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ret.derivatives() = (a.derivatives() * b.value() - a.value() * b.derivatives()) * (tmp2+tmp3);
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else
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ret.derivatives().setZero();
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return ret;
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}
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#undef EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY
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