Stan Math Library  2.9.0
reverse mode automatic differentiation
gradient_dot_vector.hpp
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1 #ifndef STAN_MATH_MIX_MAT_FUNCTOR_GRADIENT_DOT_VECTOR_HPP
2 #define STAN_MATH_MIX_MAT_FUNCTOR_GRADIENT_DOT_VECTOR_HPP
3 
4 #include <stan/math/fwd/core.hpp>
6 #include <stan/math/rev/core.hpp>
7 #include <vector>
8 
9 namespace stan {
10 
11  namespace math {
12 
13  // aka directional derivative (not length normalized)
14  // T2 must be assignable to T1
15  template <typename T1, typename T2, typename F>
16  void
17  gradient_dot_vector(const F& f,
18  const Eigen::Matrix<T1, Eigen::Dynamic, 1>& x,
19  const Eigen::Matrix<T2, Eigen::Dynamic, 1>& v,
20  T1& fx,
21  T1& grad_fx_dot_v) {
22  using stan::math::fvar;
23  using stan::math::var;
24  using Eigen::Matrix;
25  Matrix<fvar<T1>, Eigen::Dynamic, 1> x_fvar(x.size());
26  for (int i = 0; i < x.size(); ++i)
27  x_fvar(i) = fvar<T1>(x(i), v(i));
28  fvar<T1> fx_fvar = f(x_fvar);
29  fx = fx_fvar.val_;
30  grad_fx_dot_v = fx_fvar.d_;
31  }
32 
33  } // namespace math
34 } // namespace stan
35 #endif
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
void gradient_dot_vector(const F &f, const Eigen::Matrix< T1, Eigen::Dynamic, 1 > &x, const Eigen::Matrix< T2, Eigen::Dynamic, 1 > &v, T1 &fx, T1 &grad_fx_dot_v)

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