1#ifndef STAN_MATH_FWD_FUN_MDIVIDE_RIGHT_HPP
2#define STAN_MATH_FWD_FUN_MDIVIDE_RIGHT_HPP
15template <
typename EigMat1,
typename EigMat2,
16 require_all_eigen_vt<is_fvar, EigMat1, EigMat2>* =
nullptr,
17 require_vt_same<EigMat1, EigMat2>* =
nullptr>
18inline Eigen::Matrix<value_type_t<EigMat1>, EigMat1::RowsAtCompileTime,
19 EigMat2::ColsAtCompileTime>
22 constexpr int R1 = EigMat1::RowsAtCompileTime;
23 constexpr int C1 = EigMat1::ColsAtCompileTime;
24 constexpr int R2 = EigMat2::RowsAtCompileTime;
25 constexpr int C2 = EigMat2::ColsAtCompileTime;
33 Eigen::Matrix<T, R1, C1> val_A(A.rows(), A.cols());
34 Eigen::Matrix<T, R1, C1> deriv_A(A.rows(), A.cols());
35 Eigen::Matrix<T, R2, C2> val_b(b.rows(), b.cols());
36 Eigen::Matrix<T, R2, C2> deriv_b(b.rows(), b.cols());
38 const Eigen::Ref<const plain_type_t<EigMat1>>& A_ref = A;
39 for (
int j = 0; j < A.cols(); j++) {
40 for (
int i = 0; i < A.rows(); i++) {
41 val_A.coeffRef(i, j) = A_ref.coeff(i, j).val_;
42 deriv_A.coeffRef(i, j) = A_ref.coeff(i, j).d_;
46 const Eigen::Ref<const plain_type_t<EigMat2>>& b_ref = b;
47 for (
int j = 0; j < b.cols(); j++) {
48 for (
int i = 0; i < b.rows(); i++) {
49 val_b.coeffRef(i, j) = b_ref.coeff(i, j).val_;
50 deriv_b.coeffRef(i, j) = b_ref.coeff(i, j).d_;
54 Eigen::Matrix<T, R1, C2> A_mult_inv_b =
mdivide_right(val_A, val_b);
61template <
typename EigMat1,
typename EigMat2,
64inline Eigen::Matrix<value_type_t<EigMat1>, EigMat1::RowsAtCompileTime,
65 EigMat2::ColsAtCompileTime>
68 constexpr int R1 = EigMat1::RowsAtCompileTime;
69 constexpr int C1 = EigMat1::ColsAtCompileTime;
77 Eigen::Matrix<T, R1, C1> val_A(A.rows(), A.cols());
78 Eigen::Matrix<T, R1, C1> deriv_A(A.rows(), A.cols());
80 const Eigen::Ref<const plain_type_t<EigMat1>>& A_ref = A;
81 for (
int j = 0; j < A.cols(); j++) {
82 for (
int i = 0; i < A.rows(); i++) {
83 val_A.coeffRef(i, j) = A_ref.coeff(i, j).val_;
84 deriv_A.coeffRef(i, j) = A_ref.coeff(i, j).d_;
91template <
typename EigMat1,
typename EigMat2,
92 require_eigen_vt<std::is_arithmetic, EigMat1>* =
nullptr,
93 require_eigen_vt<is_fvar, EigMat2>* =
nullptr>
94inline Eigen::Matrix<value_type_t<EigMat2>, EigMat1::RowsAtCompileTime,
95 EigMat2::ColsAtCompileTime>
98 constexpr int R1 = EigMat1::RowsAtCompileTime;
99 constexpr int R2 = EigMat2::RowsAtCompileTime;
100 constexpr int C2 = EigMat2::ColsAtCompileTime;
105 return {A.rows(), 0};
108 Eigen::Matrix<T, R2, C2> val_b(b.rows(), b.cols());
109 Eigen::Matrix<T, R2, C2> deriv_b(b.rows(), b.cols());
111 const Eigen::Ref<const plain_type_t<EigMat2>>& b_ref = b;
112 for (
int j = 0; j < b.cols(); j++) {
113 for (
int i = 0; i < b.rows(); i++) {
114 val_b.coeffRef(i, j) = b_ref.coeff(i, j).val_;
115 deriv_b.coeffRef(i, j) = b_ref.coeff(i, j).d_;
119 Eigen::Matrix<T, R1, C2> A_mult_inv_b =
mdivide_right(A, val_b);
require_t< container_type_check_base< is_eigen, value_type_t, TypeCheck, Check... > > require_eigen_vt
Require type satisfies is_eigen.
typename value_type< T >::type value_type_t
Helper function for accessing underlying type.
void check_square(const char *function, const char *name, const T_y &y)
Check if the specified matrix is square.
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< value_type_t< EigMat1 >, EigMat1::RowsAtCompileTime, EigMat2::ColsAtCompileTime > mdivide_right(const EigMat1 &A, const EigMat2 &b)
fvar< T > to_fvar(const T &x)
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...