Automatic Differentiation
 
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atan2.hpp
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1#ifndef STAN_MATH_FWD_FUN_ATAN2_HPP
2#define STAN_MATH_FWD_FUN_ATAN2_HPP
3
8#include <cmath>
9
10namespace stan {
11namespace math {
12
13template <typename T>
14inline fvar<T> atan2(const fvar<T>& x1, const fvar<T>& x2) {
15 return fvar<T>(atan2(x1.val_, x2.val_),
16 (x1.d_ * x2.val_ - x1.val_ * x2.d_)
17 / (square(x2.val_) + square(x1.val_)));
18}
19
20template <typename T>
21inline fvar<T> atan2(double x1, const fvar<T>& x2) {
22 return fvar<T>(atan2(x1, x2.val_),
23 (-x1 * x2.d_) / (square(x1) + square(x2.val_)));
24}
25
26template <typename T>
27inline fvar<T> atan2(const fvar<T>& x1, double x2) {
28 return fvar<T>(atan2(x1.val_, x2),
29 (x1.d_ * x2) / (square(x2) + square(x1.val_)));
30}
31
32} // namespace math
33} // namespace stan
34#endif
fvar< T > atan2(const fvar< T > &x1, const fvar< T > &x2)
Definition atan2.hpp:14
fvar< T > square(const fvar< T > &x)
Definition square.hpp:12
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...
Scalar val_
The value of this variable.
Definition fvar.hpp:49
Scalar d_
The tangent (derivative) of this variable.
Definition fvar.hpp:61
This template class represents scalars used in forward-mode automatic differentiation,...
Definition fvar.hpp:40