1 #ifndef STAN_MATH_REV_SCAL_FUN_FMOD_HPP 2 #define STAN_MATH_REV_SCAL_FUN_FMOD_HPP 20 avi_->
adj_ = std::numeric_limits<double>::quiet_NaN();
21 bvi_->
adj_ = std::numeric_limits<double>::quiet_NaN();
35 avi_->
adj_ = std::numeric_limits<double>::quiet_NaN();
47 bvi_->
adj_ = std::numeric_limits<double>::quiet_NaN();
49 int d =
static_cast<int>(ad_ /
bvi_->
val_);
fmod_vd_vari(vari *avi, double b)
void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...
The variable implementation base class.
bool is_any_nan(const T &x)
Returns true if the input is NaN and false otherwise.
Independent (input) and dependent (output) variables for gradients.
fmod_vv_vari(vari *avi, vari *bvi)
fvar< T > fmod(const fvar< T > &x1, const fvar< T > &x2)
const double val_
The value of this variable.
fmod_dv_vari(double a, vari *bvi)
vari * vi_
Pointer to the implementation of this variable.
void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...
void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...
double adj_
The adjoint of this variable, which is the partial derivative of this variable with respect to the ro...