Automatic Differentiation
 
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inv.hpp
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1#ifndef STAN_MATH_PRIM_FUN_INV_HPP
2#define STAN_MATH_PRIM_FUN_INV_HPP
3
8
9namespace stan {
10namespace math {
11
12template <typename T, require_arithmetic_t<T>* = nullptr>
13inline auto inv(T x) {
14 return 1.0 / x;
15}
16
24struct inv_fun {
25 template <typename T>
26 static inline auto fun(T&& x) {
27 return 1.0 / x;
28 }
29};
30
39template <
42 require_container_t<T>* = nullptr>
43inline auto inv(T&& x) {
44 return apply_scalar_unary<inv_fun, T>::apply(std::forward<T>(x));
45}
46
55template <typename Container,
58 Container>* = nullptr>
59inline auto inv(Container&& x) {
61 std::forward<Container>(x), [](auto&& v) { return v.array().inverse(); });
62}
63
64} // namespace math
65} // namespace stan
66
67#endif
require_not_t< container_type_check_base< is_container, scalar_type_t, TypeCheck, Check... > > require_not_container_st
Require type does not satisfy is_container.
require_t< container_type_check_base< is_container, scalar_type_t, TypeCheck, Check... > > require_container_st
Require type satisfies is_container.
require_t< is_container< std::decay_t< T > > > require_container_t
Require type satisfies is_container.
require_all_not_t< is_nonscalar_prim_or_rev_kernel_expression< std::decay_t< Types > >... > require_all_not_nonscalar_prim_or_rev_kernel_expression_t
Require none of the types satisfy is_nonscalar_prim_or_rev_kernel_expression.
Eigen::Matrix< value_type_t< EigMat >, EigMat::RowsAtCompileTime, EigMat::ColsAtCompileTime > inverse(const EigMat &m)
Forward mode specialization of calculating the inverse of the matrix.
Definition inverse.hpp:28
fvar< T > inv(const fvar< T > &x)
Definition inv.hpp:13
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...
Base template class for vectorization of unary scalar functions defined by a template class F to a sc...
static auto fun(T &&x)
Definition inv.hpp:26
Structure to wrap 1.0 / x so that it can be vectorized.
Definition inv.hpp:24