Automatic Differentiation
 
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multiply_log.hpp
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1#ifndef STAN_MATH_PRIM_FUN_MULTIPLY_LOG_HPP
2#define STAN_MATH_PRIM_FUN_MULTIPLY_LOG_HPP
3
7#include <cmath>
8
9namespace stan {
10namespace math {
11
47template <typename T_a, typename T_b,
48 require_all_arithmetic_t<T_a, T_b>* = nullptr>
49inline return_type_t<T_a, T_b> multiply_log(const T_a a, const T_b b) {
50 using std::log;
51 if (b == 0.0 && a == 0.0) {
52 return 0.0;
53 }
54
55 return a * log(b);
56}
57
68template <typename T1, typename T2, require_any_container_t<T1, T2>* = nullptr,
69 require_all_not_var_matrix_t<T1, T2>* = nullptr>
70inline auto multiply_log(T1&& a, T2&& b) {
72 [](auto&& c, auto&& d) {
73 return multiply_log(std::forward<decltype(c)>(c),
74 std::forward<decltype(d)>(d));
75 },
76 std::forward<T1>(a), std::forward<T2>(b));
77}
78
79} // namespace math
80} // namespace stan
81
82#endif
typename return_type< Ts... >::type return_type_t
Convenience type for the return type of the specified template parameters.
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
auto apply_scalar_binary(F &&f, T1 &&x, T2 &&y)
Base template function for vectorization of binary scalar functions defined by applying a functor to ...
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 ...