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 >::RevSparseJac ( size_t  p, const VectorSet &  s  ) User API for Jacobian 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 with elements of type bool. or std::set<size_t>. Parameters: p is the number of rows in the matrix . s is a sparsity pattern for the matrix . Returns: If VectorSet::value_type is bool, the return value r is a vector with size p*n where n is the number of independent variables corresponding to the operation sequence stored in f. If VectorSet::value_type is std::set<size_t>, the return value r is a vector of sets with size p and with all its elements between zero and n - 1. The value of r is the sparsity pattern for the matrix where is the function corresponding to the operation sequence and x is any argument value. Definition at line 431 of file rev_sparse_jac.hpp.