template<class Base >

template<class VectorSet >

VectorSet ADFun< Base >::ForSparseJac	(	size_t	q,
		const VectorSet &	r
	)

User API for Jacobian sparsity patterns using forward mode.

The C++ source code corresponding to this operation is

	s = f.ForSparseJac(q, r)

Template Parameters:

Base	is the base type for this recording.
VectorSet	is a simple vector with elements of type bool or std::set<size_t>.

Parameters:

q	is the number of columns in the matrix .
r	is a sparsity pattern for the matrix .

Returns:

If VectorSet::value_type is bool, the return value s is a vector with size m*q where m is the number of dependent variables corresponding to the operation sequence stored in f. If VectorSet::value_type is std::set<size_t>, the return value s is a vector of sets with size m and with all its elements between zero and q - 1. The value of s is the sparsity pattern for the matrix

where is the function corresponding to the operation sequence and x is any argument value.

Side Effects

If VectorSet::value_type is bool, the forward sparsity pattern for all of the variables on the tape is stored in for_jac_sparse_pack__. In this case

	for_jac_sparse_pack_.n_set() == total_num_var_
	for_jac_sparse_pack_.end() == q
	for_jac_sparse_set_.n_set()  == 0
	for_jac_sparse_set_.end()  == 0

If VectorSet::value_type is std::set<size_t>, the forward sparsity pattern for all of the variables on the tape is stored in for_jac_sparse_set__. In this case

	for_jac_sparse_set_.n_set()   == total_num_var_
	for_jac_sparse_set_.end()   == q
	for_jac_sparse_pack_.n_set()  == 0
	for_jac_sparse_pack_.end()  == 0

Definition at line 586 of file for_sparse_jac.hpp.