Stan Math Library  2.20.0
reverse mode automatic differentiation
operator_unary_decrement.hpp
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1 #ifndef STAN_MATH_REV_CORE_OPERATOR_UNARY_DECREMENT_HPP
2 #define STAN_MATH_REV_CORE_OPERATOR_UNARY_DECREMENT_HPP
3 
7 #include <limits>
8 
9 namespace stan {
10 namespace math {
11 
12 namespace internal {
13 class decrement_vari : public op_v_vari {
14  public:
15  explicit decrement_vari(vari* avi) : op_v_vari(avi->val_ - 1.0, 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 
38 inline var& operator--(var& a) {
39  a.vi_ = new internal::decrement_vari(a.vi_);
40  return a;
41 }
42 
54 inline var operator--(var& a, int /*dummy*/) {
55  var temp(a);
56  a.vi_ = new internal::decrement_vari(a.vi_);
57  return temp;
58 }
59 
60 } // namespace math
61 } // namespace stan
62 #endif
The variable implementation base class.
Definition: vari.hpp:30
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:33
var & operator--(var &a)
Prefix decrement operator for variables (C++).
const double val_
The value of this variable.
Definition: vari.hpp:38
#define unlikely(x)
Definition: likely.hpp:9
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:45
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...
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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