Automatic Differentiation
 
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◆ apply_scalar_binary() [4/5]

template<typename T1 , typename T2 , typename F , require_eigen_matrix_dynamic_vt< is_stan_scalar, T1 > * = nullptr, require_std_vector_vt< is_std_vector, T2 > * = nullptr, require_std_vector_st< std::is_integral, T2 > * = nullptr>
auto stan::math::apply_scalar_binary ( const T1 &  x,
const T2 &  y,
const F &  f 
)
inline

Specialization for use with one Eigen matrix and a two-dimensional std::vector of integer types.

Specialization for use with a two-dimensional std::vector of integer types and one var_value<Matrix>.

Specialization for use with a two-dimensional std::vector of integer types and one Eigen matrix.

Template Parameters
T1Type of first argument to which functor is applied.
T2Type of second argument to which functor is applied.
FType of functor to apply.
Parameters
xEigen matrix input to which operation is applied.
yNested integer std::vector input to which operation is applied.
ffunctor to apply to inputs.
Returns
Eigen object with result of applying functor to inputs.
Template Parameters
T1Type of first argument to which functor is applied.
T2Type of second argument to which functor is applied.
FType of functor to apply.
Parameters
xNested integer std::vector input to which operation is applied.
yEigen matrix input to which operation is applied.
ffunctor to apply to inputs.
Returns
Eigen object with result of applying functor to inputs.
Template Parameters
T1Type of first argument to which functor is applied.
T2Type of second argument to which functor is applied.
FType of functor to apply.
Parameters
xEither a var matrix or nested integer std::vector input to which operation is applied.
xEither a var matrix or nested integer std::vector input to which operation is applied.
ffunctor to apply to inputs.
Returns
Eigen object with result of applying functor to inputs.

Definition at line 135 of file apply_scalar_binary.hpp.