Stan Math Library  2.15.0
reverse mode automatic differentiation
floor.hpp
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1 #ifndef STAN_MATH_REV_SCAL_FUN_FLOOR_HPP
2 #define STAN_MATH_REV_SCAL_FUN_FLOOR_HPP
3 
4 #include <stan/math/rev/core.hpp>
7 #include <cmath>
8 #include <limits>
9 
10 namespace stan {
11  namespace math {
12 
13  namespace {
14  class floor_vari : public op_v_vari {
15  public:
16  explicit floor_vari(vari* avi) :
17  op_v_vari(std::floor(avi->val_), avi) {
18  }
19  void chain() {
20  if (unlikely(is_nan(avi_->val_)))
21  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
22  }
23  };
24  }
25 
60  inline var floor(const var& a) {
61  return var(new floor_vari(a.vi_));
62  }
63 
64  }
65 }
66 #endif
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:30
#define unlikely(x)
Definition: likely.hpp:9
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:42
fvar< T > floor(const fvar< T > &x)
Definition: floor.hpp:11
int is_nan(const fvar< T > &x)
Returns 1 if the input&#39;s value is NaN and 0 otherwise.
Definition: is_nan.hpp:21

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