Automatic Differentiation
 
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mdivide_right.hpp
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1#ifndef STAN_MATH_FWD_FUN_MDIVIDE_RIGHT_HPP
2#define STAN_MATH_FWD_FUN_MDIVIDE_RIGHT_HPP
3
10#include <vector>
11
12namespace stan {
13namespace math {
14
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>
20mdivide_right(const EigMat1& A, const EigMat2& b) {
21 using T = typename value_type_t<EigMat1>::Scalar;
22 constexpr int R1 = EigMat1::RowsAtCompileTime;
23 constexpr int C1 = EigMat1::ColsAtCompileTime;
24 constexpr int R2 = EigMat2::RowsAtCompileTime;
25 constexpr int C2 = EigMat2::ColsAtCompileTime;
26
27 check_square("mdivide_right", "b", b);
28 check_multiplicable("mdivide_right", "A", A, "b", b);
29 if (b.size() == 0) {
30 return {A.rows(), 0};
31 }
32
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());
37
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_;
43 }
44 }
45
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_;
51 }
52 }
53
54 Eigen::Matrix<T, R1, C2> A_mult_inv_b = mdivide_right(val_A, val_b);
55
56 return to_fvar(A_mult_inv_b,
57 mdivide_right(deriv_A, val_b)
58 - A_mult_inv_b * mdivide_right(deriv_b, val_b));
59}
60
61template <typename EigMat1, typename EigMat2,
64inline Eigen::Matrix<value_type_t<EigMat1>, EigMat1::RowsAtCompileTime,
65 EigMat2::ColsAtCompileTime>
66mdivide_right(const EigMat1& A, const EigMat2& b) {
67 using T = typename value_type_t<EigMat1>::Scalar;
68 constexpr int R1 = EigMat1::RowsAtCompileTime;
69 constexpr int C1 = EigMat1::ColsAtCompileTime;
70
71 check_square("mdivide_right", "b", b);
72 check_multiplicable("mdivide_right", "A", A, "b", b);
73 if (b.size() == 0) {
74 return {A.rows(), 0};
75 }
76
77 Eigen::Matrix<T, R1, C1> val_A(A.rows(), A.cols());
78 Eigen::Matrix<T, R1, C1> deriv_A(A.rows(), A.cols());
79
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_;
85 }
86 }
87
88 return to_fvar(mdivide_right(val_A, b), mdivide_right(deriv_A, b));
89}
90
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>
96mdivide_right(const EigMat1& A, const EigMat2& b) {
97 using T = typename value_type_t<EigMat2>::Scalar;
98 constexpr int R1 = EigMat1::RowsAtCompileTime;
99 constexpr int R2 = EigMat2::RowsAtCompileTime;
100 constexpr int C2 = EigMat2::ColsAtCompileTime;
101
102 check_square("mdivide_right", "b", b);
103 check_multiplicable("mdivide_right", "A", A, "b", b);
104 if (b.size() == 0) {
105 return {A.rows(), 0};
106 }
107
108 Eigen::Matrix<T, R2, C2> val_b(b.rows(), b.cols());
109 Eigen::Matrix<T, R2, C2> deriv_b(b.rows(), b.cols());
110
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_;
116 }
117 }
118
119 Eigen::Matrix<T, R1, C2> A_mult_inv_b = mdivide_right(A, val_b);
120
121 return to_fvar(A_mult_inv_b, -A_mult_inv_b * mdivide_right(deriv_b, val_b));
122}
123
124} // namespace math
125} // namespace stan
126#endif
require_t< container_type_check_base< is_eigen, value_type_t, TypeCheck, Check... > > require_eigen_vt
Require type satisfies is_eigen.
Definition is_eigen.hpp:152
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)
Definition to_fvar.hpp:15
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...