CppAD: A C++ Algorithmic Differentiation Package  20171217
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template<class Base >
template<class SizeVector , class BaseVector >
size_t CppAD::ADFun< Base >::sparse_jac_rev ( const BaseVector &  x,
sparse_rcv< SizeVector, BaseVector > &  subset,
const sparse_rc< SizeVector > &  pattern,
const std::string &  coloring,
sparse_jac_work work 
)

Calculate sparse Jacobains using reverse mode.

Template Parameters
Basethe base type for the recording that is stored in the ADFun object.
SizeVectora simple vector class with elements of type size_t.
BaseVectora simple vector class with elements of type Base.
Parameters
xa vector of length n, the number of independent variables in f (this ADFun object).
subsetspecifices the subset of the sparsity pattern where the Jacobian is evaluated. subset.nr() == m, subset.nc() == n.
patternis a sparsity pattern for the Jacobian of f; pattern.nr() == m, pattern.nc() == n, where m is number of dependent variables in f.
coloringdetermines which coloring algorithm is used. This must be cppad or colpack.
workthis structure must be empty, or contain the information stored by a previous call to sparse_jac_rev. The previous call must be for the same ADFun object f and the same subset.
Returns
This is the number of first order reverse sweeps used to compute the Jacobian.

Definition at line 480 of file sparse_jac.hpp.