Automatic Differentiation
 
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ode_store_sensitivities.hpp
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1#ifndef STAN_MATH_PRIM_FUNCTOR_ODE_STORE_SENSITIVITIES_HPP
2#define STAN_MATH_PRIM_FUNCTOR_ODE_STORE_SENSITIVITIES_HPP
3
6#include <ostream>
7#include <vector>
8
9namespace stan {
10namespace math {
11
31template <
32 typename F, typename T_y0_t0, typename T_t0, typename T_t, typename... Args,
33 typename
34 = require_all_arithmetic_t<T_y0_t0, T_t0, T_t, scalar_type_t<Args>...>>
36 const F& f, const std::vector<double>& coupled_state,
37 const Eigen::Matrix<T_y0_t0, Eigen::Dynamic, 1>& y0, T_t0 t0, T_t t,
38 std::ostream* msgs, const Args&... args) {
39 return Eigen::Map<const Eigen::VectorXd>(coupled_state.data(),
40 coupled_state.size());
41}
42
43} // namespace math
44} // namespace stan
45#endif
Eigen::VectorXd ode_store_sensitivities(const F &f, const std::vector< double > &coupled_state, const Eigen::Matrix< T_y0_t0, Eigen::Dynamic, 1 > &y0, T_t0 t0, T_t t, std::ostream *msgs, const Args &... args)
When all arguments are arithmetic, there are no sensitivities to store, so the function just returns ...
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...