1#ifndef STAN_MATH_FWD_FUN_MDIVIDE_LEFT_TRI_LOW_HPP
2#define STAN_MATH_FWD_FUN_MDIVIDE_LEFT_TRI_LOW_HPP
16template <
typename T1,
typename T2,
17 require_all_eigen_vt<is_fvar, T1, T2>* =
nullptr,
18 require_vt_same<T1, T2>* =
nullptr>
19inline Eigen::Matrix<value_type_t<T1>, T1::RowsAtCompileTime,
20 T2::ColsAtCompileTime>
23 constexpr int S1 = T1::RowsAtCompileTime;
24 constexpr int C2 = T2::ColsAtCompileTime;
32 Eigen::Matrix<T, S1, S1> val_A(A.rows(), A.cols());
33 Eigen::Matrix<T, S1, S1> deriv_A(A.rows(), A.cols());
37 const Eigen::Ref<const plain_type_t<T2>>& b_ref = b;
38 const Eigen::Ref<const plain_type_t<T1>>& A_ref = A;
39 for (
size_type j = 0; j < A.cols(); j++) {
40 for (
size_type i = j; i < A.rows(); i++) {
41 val_A(i, j) = A_ref(i, j).val_;
42 deriv_A(i, j) = A_ref(i, j).d_;
46 Eigen::Matrix<T, S1, C2> inv_A_mult_b =
mdivide_left(val_A, b_ref.val());
53template <
typename T1,
typename T2, require_eigen_t<T1>* =
nullptr,
54 require_vt_same<
double, T1>* =
nullptr,
55 require_eigen_vt<is_fvar, T2>* =
nullptr>
56inline Eigen::Matrix<value_type_t<T2>, T1::RowsAtCompileTime,
57 T2::ColsAtCompileTime>
59 constexpr int S1 = T1::RowsAtCompileTime;
67 Eigen::Matrix<double, S1, S1> val_A(A.rows(), A.cols());
70 const Eigen::Ref<const plain_type_t<T2>>& b_ref = b;
71 const Eigen::Ref<const plain_type_t<T1>>& A_ref = A;
72 for (
size_type j = 0; j < A.cols(); j++) {
73 for (
size_type i = j; i < A.rows(); i++) {
74 val_A(i, j) = A_ref(i, j);
82template <
typename T1,
typename T2, require_eigen_vt<is_fvar, T1>* =
nullptr,
83 require_eigen_t<T2>* =
nullptr,
84 require_vt_same<
double, T2>* =
nullptr>
85inline Eigen::Matrix<value_type_t<T1>, T1::RowsAtCompileTime,
86 T2::ColsAtCompileTime>
89 constexpr int S1 = T1::RowsAtCompileTime;
90 constexpr int C2 = T2::ColsAtCompileTime;
98 Eigen::Matrix<T, S1, S1> val_A(A.rows(), A.cols());
99 Eigen::Matrix<T, S1, S1> deriv_A(A.rows(), A.cols());
103 const Eigen::Ref<const plain_type_t<T1>>& A_ref = A;
104 for (
size_type j = 0; j < A.cols(); j++) {
105 for (
size_type i = j; i < A.rows(); i++) {
106 val_A(i, j) = A_ref(i, j).val_;
107 deriv_A(i, j) = A_ref(i, j).d_;
111 Eigen::Matrix<T, S1, C2> inv_A_mult_b =
mdivide_left(val_A, b);
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.
auto multiply(const Mat1 &m1, const Mat2 &m2)
Return the product of the specified matrices.
Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic >::Index size_type
Type for sizes and indexes in an Eigen matrix with double elements.
fvar< T > to_fvar(const T &x)
Eigen::Matrix< value_type_t< T1 >, T1::RowsAtCompileTime, T2::ColsAtCompileTime > mdivide_left(const T1 &A, const T2 &b)
Eigen::Matrix< value_type_t< T1 >, T1::RowsAtCompileTime, T2::ColsAtCompileTime > mdivide_left_tri_low(const T1 &A, const T2 &b)
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...