template<class Base , class VectorSet >

void CppAD::RevSparseJacBool	(	bool	transpose,
		bool	nz_compare,
		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
	)

Calculate Jacobian vector of bools sparsity patterns using reverse mode.

The C++ source code corresponding to this operation is

	s = f.RevSparseJac(q, r)

Template Parameters:

Base	is the base type for this recording.
VectorSet	is a simple vector class with elements of type bool.

Parameters:

transpose	are the sparsity patterns transposed.
nz_compare	Are the derivatives with respect to left and right of the expression below considered to be non-zero: CondExpRel(left, right, if_true, if_false) This is used by the optimizer to obtain the correct dependency relations.
q	is the number of rows in the matrix .
r	is a sparsity pattern for the matrix .
s	the input value of s must be a vector with size p*n where n is the number of independent 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.

Definition at line 253 of file rev_sparse_jac.hpp.

Referenced by CppAD::ADFun< Base >::RevSparseJacCase().