template<class Base , class VectorSet >

void ForSparseJacBool	(	size_t	q,
		const VectorSet &	r,
		VectorSet &	s,
		size_t	total_num_var,
		CppAD::vector< size_t > &	dep_taddr,
		CppAD::vector< size_t > &	ind_taddr,
		CppAD::player< Base > &	play,
		sparse_pack &	for_jac_sparsity
	)

Calculate Jacobian vector of bools 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 class with elements of type bool.

Parameters:

q	is the number of columns in the matrix .
r	is a sparsity pattern for the matrix .
s	The input value of s must be a vector with size m*q where m is the number of dependent variables corresponding to the operation sequence stored in play. The input value of the components of s does not matter. On output, s is the sparsity pattern for the matrix where is the function corresponding to the operation sequence and x is any argument value.
total_num_var	is the total number of variable in this recording.
dep_taddr	maps dependendent variable index to the corresponding variable in the tape.
ind_taddr	maps independent variable index to the corresponding variable in the tape.
play	is the recording that defines the function we are computing the sparsity pattern for.
for_jac_sparsity	the input value of for_jac_sparsity does not matter. On output, for_jac_sparsity.n_set() == total_num_var and for_jac_sparsity.end() == q. It contains the forward sparsity pattern for all of the variables on the tape (given the sparsity pattern for the independent variables is ).

Definition at line 242 of file for_sparse_jac.hpp.

Referenced by ADFun< Base >::ForSparseJacCase().