Automatic Differentiation
 
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log.hpp
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1#ifndef STAN_MATH_REV_FUN_LOG_HPP
2#define STAN_MATH_REV_FUN_LOG_HPP
3
16#include <cmath>
17
18namespace stan {
19namespace math {
20
50template <typename T, require_stan_scalar_or_eigen_t<T>* = nullptr>
51inline auto log(const var_value<T>& a) {
52 return make_callback_var(log(a.val()), [a](auto& vi) mutable {
53 as_array_or_scalar(a.adj())
54 += as_array_or_scalar(vi.adj()) / as_array_or_scalar(a.val());
55 });
56}
57
64inline std::complex<var> log(const std::complex<var>& z) {
65 return internal::complex_log(z);
66}
67
68} // namespace math
69} // namespace stan
70#endif
std::complex< V > complex_log(const std::complex< V > &z)
Return the natural logarithm of the complex argument.
Definition log.hpp:98
var_value< plain_type_t< T > > make_callback_var(T &&value, F &&functor)
Creates a new var initialized with a callback_vari with a given value and reverse-pass callback funct...
fvar< T > log(const fvar< T > &x)
Definition log.hpp:18
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...