1 #ifndef STAN_MATH_FWD_MAT_FUN_INVERSE_HPP 2 #define STAN_MATH_FWD_MAT_FUN_INVERSE_HPP 15 template <
typename T,
int R,
int C>
16 inline Eigen::Matrix<fvar<T>, R, C>
inverse(
17 const Eigen::Matrix<
fvar<T>, R, C>& m) {
19 Eigen::Matrix<T, R, C> m_deriv(m.rows(), m.cols());
20 Eigen::Matrix<T, R, C> m_inv(m.rows(), m.cols());
22 for (
size_type i = 0; i < m.rows(); i++) {
23 for (
size_type j = 0; j < m.cols(); j++) {
24 m_inv(i, j) = m(i, j).val_;
25 m_deriv(i, j) = m(i, j).d_;
void check_square(const char *function, const char *name, const matrix_cl &y)
Check if the matrix_cl is square.
Eigen::Matrix< fvar< T >, R1, C1 > multiply(const Eigen::Matrix< fvar< T >, R1, C1 > &m, const fvar< T > &c)
std::vector< fvar< T > > to_fvar(const std::vector< T > &v)
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double e.
Eigen::Matrix< fvar< T >, R, C > inverse(const Eigen::Matrix< fvar< T >, R, C > &m)
This template class represents scalars used in forward-mode automatic differentiation, which consist of values and directional derivatives of the specified template type.