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.
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.
This is the number of first order reverse sweeps used to compute the Jacobian.

Definition at line 480 of file sparse_jac.hpp.