template<class Base , class VectorSet , class Sparsity >

void RevSparseHesBool	(	size_t	q,
		const VectorSet &	s,
		VectorSet &	h,
		size_t	total_num_var,
		CppAD::vector< size_t > &	dep_taddr,
		CppAD::vector< size_t > &	ind_taddr,
		CppAD::player< Base > &	play,
		Sparsity &	for_jac_sparsity
	)

Calculate Hessian sparsity patterns using reverse mode.

The C++ source code corresponding to this operation is

	h = f.RevSparseHes(q, s)

Template Parameters:

Base	is the base type for this recording.
VectorSet	is a simple vector with elements of type bool.
Sparsity	is either sparse_pack, sparse_set, or sparse_list.

Parameters:

q	is the value of q in the by the previous call of the form f.ForSparseJac(q, r) The value r in this call is a sparsity pattern for the matrix .
s	is a vector with size m that specifies the sparsity pattern for the vector , where m is the number of dependent variables corresponding to the operation sequence stored in play.
h	the input value of h must be a vector with size q*n. The input value of its elements does not matter. On output, h 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 variables 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	is a vector of sets containing the the forward Jacobian sparsity pattern corresponding to $latex R$$ for all of the variables on the tape.

Definition at line 237 of file rev_sparse_hes.hpp.

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