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 > VectorBase ADFun< Base >::SparseHessian ( const VectorBase &  x, const VectorBase &  w  ) calculate sparse Hessians Compute a sparse Hessian. The C++ source code coresponding to this operation is hes = SparseHessian(x, w) 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 the Base. Parameters: x is a vector specifing the point at which to compute the Hessian. w The Hessian is computed for a weighted sum of the components of the function corresponding to this ADFun<Base> object. The argument w specifies the weights for each component. It must have size equal to the range dimension for this ADFun<Base> object. Returns: Will be a vector of size n * n containing the Hessian of at the point specified by x (where n is the domain dimension for this ADFun<Base> object). Definition at line 537 of file sparse_hessian.hpp.