Stan Math Library  2.20.0
reverse mode automatic differentiation
operator_unary_negative.hpp
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1 #ifndef STAN_MATH_REV_CORE_OPERATOR_UNARY_NEGATIVE_HPP
2 #define STAN_MATH_REV_CORE_OPERATOR_UNARY_NEGATIVE_HPP
3 
7 #include <limits>
8 
9 namespace stan {
10 namespace math {
11 
12 namespace internal {
13 class neg_vari : public op_v_vari {
14  public:
15  explicit neg_vari(vari* avi) : op_v_vari(-(avi->val_), avi) {}
16  void chain() {
17  if (unlikely(is_nan(avi_->val_)))
18  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
19  else
20  avi_->adj_ -= adj_;
21  }
22 };
23 } // namespace internal
24 
49 inline var operator-(const var& a) {
50  return var(new internal::neg_vari(a.vi_));
51 }
52 
53 } // namespace math
54 } // namespace stan
55 #endif
fvar< T > operator-(const fvar< T > &x1, const fvar< T > &x2)
Return the difference of the specified arguments.
The variable implementation base class.
Definition: vari.hpp:30
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:33
friend class var
Definition: vari.hpp:32
const double val_
The value of this variable.
Definition: vari.hpp:38
void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...
#define unlikely(x)
Definition: likely.hpp:9
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:45
double adj_
The adjoint of this variable, which is the partial derivative of this variable with respect to the ro...
Definition: vari.hpp:44
int is_nan(const fvar< T > &x)
Returns 1 if the input&#39;s value is NaN and 0 otherwise.
Definition: is_nan.hpp:20

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