ADFun ADFun ADFun ADFun capacity_taylor compare_change_ CompareChange dep_parameter_ dep_taddr_ Dependent Dependent Dependent Domain for_jac_sparse_pack_ for_jac_sparse_set_ ForOne ForOne ForSparseJac ForSparseJacCase ForSparseJacCase ForTwo Forward Forward Hessian Hessian Hessian Hessian ind_taddr_ Jacobian Jacobian Memory operator= optimize Order Parameter play_ Range Reverse RevOne RevOne RevSparseHes RevSparseHesCase RevSparseHesCase RevSparseJac RevSparseJacCase RevSparseJacCase RevTwo Size size_forward_bool size_forward_bool size_forward_set size_forward_set size_op size_op_arg size_op_seq size_par size_taylor size_text size_var size_VecAD SparseHessian SparseHessian SparseHessian SparseHessianCase SparseHessianCase SparseJacobian SparseJacobian SparseJacobianCase SparseJacobianCase taylor_ taylor_col_dim_ taylor_per_var_ taylor_size total_num_var_ use_VecAD ~ADFun

template<class Base > template<class VectorSet > VectorSet ADFun< Base >::RevSparseHes ( size_t  q, const VectorSet &  s  ) User API for Hessian sparsity patterns using reverse mode. The C++ source code corresponding to this operation is h = f.RevSparseHes(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 value of q in the by the previous call of the form f.ForSparseJac(q, r, packed) The value r in this call is a sparsity pattern for the matrix . The type of the element of r for the previous call to ForSparseJac must be the same as the type of the elements of s. 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. Returns: is a vector with size q*n. containing a sparsity pattern for the matrix where is the function corresponding to the operation sequence and x is any argument value. Definition at line 526 of file rev_sparse_hes.hpp.