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 VectorBase , class VectorSet > VectorBase ADFun< Base >::SparseJacobian ( const VectorBase &  x, const VectorSet &  p  ) calculate sparse Jacobians Compute a sparse Jacobian. The C++ source code corresponding to this operation is jac = SparseJacobian(x, p) Template Parameters: Base is the base type for the recording that is stored in this ADFun<Base object. VectorBase is a simple vector class with elements of type Base. VectorSet is a simple vector class with elements of type bool or std::set<size_t>. Parameters: x is a vector specifing the point at which to compute the Jacobian. p is the sparsity pattern for the Jacobian that we are calculating. Returns: Will be a vector if size m * n containing the Jacobian at the specified point (in row major order). Definition at line 606 of file sparse_jacobian.hpp.