Stan Math Library  2.14.0
reverse mode automatic differentiation
trunc.hpp
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1 #ifndef STAN_MATH_REV_SCAL_FUN_TRUNC_HPP
2 #define STAN_MATH_REV_SCAL_FUN_TRUNC_HPP
3 
4 #include <stan/math/rev/core.hpp>
7 #include <limits>
8 
9 namespace stan {
10  namespace math {
11 
12  namespace {
13  class trunc_vari : public op_v_vari {
14  public:
15  explicit trunc_vari(vari* avi) :
16  op_v_vari(trunc(avi->val_), avi) {
17  }
18  void chain() {
19  if (unlikely(is_nan(avi_->val_)))
20  avi_->adj_ = std::numeric_limits<double>::quiet_NaN();
21  }
22  };
23  }
24 
55  inline var trunc(const var& a) {
56  return var(new trunc_vari(a.vi_));
57  }
58 
59  }
60 }
61 #endif
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:30
fvar< T > trunc(const fvar< T > &x)
Return the nearest integral value that is not larger in magnitude than the specified argument...
Definition: trunc.hpp:19
#define unlikely(x)
Definition: likely.hpp:9
vari * vi_
Pointer to the implementation of this variable.
Definition: var.hpp:42
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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