Stan Math Library  2.20.0
reverse mode automatic differentiation
multiply_log.hpp
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1 #ifndef STAN_MATH_FWD_SCAL_FUN_MULTIPLY_LOG_HPP
2 #define STAN_MATH_FWD_SCAL_FUN_MULTIPLY_LOG_HPP
3 
4 #include <stan/math/fwd/meta.hpp>
5 #include <stan/math/fwd/core.hpp>
7 
8 namespace stan {
9 namespace math {
10 
11 template <typename T>
12 inline fvar<T> multiply_log(const fvar<T>& x1, const fvar<T>& x2) {
13  using std::log;
14  return fvar<T>(multiply_log(x1.val_, x2.val_),
15  x1.d_ * log(x2.val_) + x1.val_ * x2.d_ / x2.val_);
16 }
17 
18 template <typename T>
19 inline fvar<T> multiply_log(double x1, const fvar<T>& x2) {
20  using std::log;
21  return fvar<T>(multiply_log(x1, x2.val_), x1 * x2.d_ / x2.val_);
22 }
23 
24 template <typename T>
25 inline fvar<T> multiply_log(const fvar<T>& x1, double x2) {
26  using std::log;
27  return fvar<T>(multiply_log(x1.val_, x2), x1.d_ * log(x2));
28 }
29 } // namespace math
30 } // namespace stan
31 #endif
T d_
The tangent (derivative) of this variable.
Definition: fvar.hpp:50
fvar< T > log(const fvar< T > &x)
Definition: log.hpp:12
T val_
The value of this variable.
Definition: fvar.hpp:45
fvar< T > multiply_log(const fvar< T > &x1, const fvar< T > &x2)
This template class represents scalars used in forward-mode automatic differentiation, which consist of values and directional derivatives of the specified template type.
Definition: fvar.hpp:41

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