Stan Math Library  2.20.0
reverse mode automatic differentiation
scale_matrix_exp_multiply.hpp
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1 #ifndef STAN_MATH_REV_MAT_FUN_SCALE_MATRIX_EXP_MULTIPLY_HPP
2 #define STAN_MATH_REV_MAT_FUN_SCALE_MATRIX_EXP_MULTIPLY_HPP
3 
4 #include <stan/math/rev/meta.hpp>
11 #include <stan/math/rev/core.hpp>
12 
13 namespace stan {
14 namespace math {
15 
28 template <typename Ta, typename Tb, int Cb>
29 inline Eigen::Matrix<typename stan::return_type<Ta, Tb>::type, -1, Cb>
30 scale_matrix_exp_multiply(const double& t, const Eigen::Matrix<Ta, -1, -1>& A,
31  const Eigen::Matrix<Tb, -1, Cb>& B) {
32  check_nonzero_size("scale_matrix_exp_multiply", "input matrix", A);
33  check_nonzero_size("scale_matrix_exp_multiply", "input matrix", B);
34  check_multiplicable("scale_matrix_exp_multiply", "A", A, "B", B);
35  check_square("scale_matrix_exp_multiply", "input matrix", A);
36  return multiply(matrix_exp(multiply(A, t)), B);
37 }
38 
39 } // namespace math
40 } // namespace stan
41 
42 #endif
void check_nonzero_size(const char *function, const char *name, const T_y &y)
Check if the specified matrix/vector is of non-zero size.
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)
Definition: multiply.hpp:14
Eigen::Matrix< double, -1, Cb > scale_matrix_exp_multiply(const double &t, const Eigen::MatrixXd &A, const Eigen::Matrix< double, -1, Cb > &B)
Return product of exp(At) and B, where A is a NxN double matrix, B is a NxCb double matrix...
void check_multiplicable(const char *function, const char *name1, const T1 &y1, const char *name2, const T2 &y2)
Check if the matrices can be multiplied.
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > matrix_exp(const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &A)
Return the matrix exponential of the input matrix.
Definition: matrix_exp.hpp:20

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