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9 #ifndef __IPTNLPREDUCER_HPP__
10 #define __IPTNLPREDUCER_HPP__
48 bool& use_x_scaling,
Index n,
50 bool& use_g_scaling,
Index m,
93 Number regularization_size,
102 Index* pos_nonlin_vars);
Index nnz_jac_g_skipped_
Number of Jacobian nonzeros that are skipped.
Class to organize all the data required by the algorithm.
IndexStyleEnum index_style_orig_
Index style for original problem.
virtual Index get_number_of_nonlinear_variables()
Index n_xU_skip_
Number of upper variable bounds to be skipped.
Index * jac_g_skipped_
Array of Jacobian elements that are to be skipped.
Class for all IPOPT specific calculated quantities.
virtual bool get_list_of_nonlinear_variables(Index num_nonlin_vars, Index *pos_nonlin_vars)
virtual bool get_constraints_linearity(Index m, LinearityType *const_types)
overload this method to return the constraint linearity.
Index * index_g_skip_
Array of indices of the constraints that are to be skipped.
double Number
Type of all numbers.
virtual bool get_bounds_info(Index n, Number *x_l, Number *x_u, Index m, Number *g_l, Number *g_u)
overload this method to return the information about the bound on the variables and constraints.
virtual bool eval_jac_g(Index n, const Number *x, bool new_x, Index m, Index nele_jac, Index *iRow, Index *jCol, Number *values)
overload this method to return the jacobian of the constraints.
virtual bool get_variables_linearity(Index n, LinearityType *var_types)
overload this method to return the variables linearity (TNLP::LINEAR or TNLP::NON_LINEAR).
Number * x
Input: Starting point Output: Optimal solution.
virtual bool get_warm_start_iterate(IteratesVector &warm_start_iterate)
overload this method to provide an Ipopt iterate (already in the form Ipopt requires it internally) f...
Number Number Index Number Number Index Index nele_hess
Number of non-zero elements in Hessian of Lagrangian.
Number Number Index Number Number Index nele_jac
Number of non-zero elements in constraint Jacobian.
int Index
Type of all indices of vectors, matrices etc.
Index * index_xL_skip_
Array of indices of the lower variable bounds to be skipped.
Index n_g_skip_
Number of constraints to be skipped.
Template class for Smart Pointers.
virtual bool eval_grad_f(Index n, const Number *x, bool new_x, Number *grad_f)
overload this method to return the vector of the gradient of the objective w.r.t.
virtual bool get_scaling_parameters(Number &obj_scaling, bool &use_x_scaling, Index n, Number *x_scaling, bool &use_g_scaling, Index m, Number *g_scaling)
overload this method to return scaling parameters.
This is a wrapper around a given TNLP class that takes out a list of constraints that are given to th...
TNLPReducer()
Default Constructor.
virtual bool intermediate_callback(AlgorithmMode mode, Index iter, Number obj_value, Number inf_pr, Number inf_du, Number mu, Number d_norm, Number regularization_size, Number alpha_du, Number alpha_pr, Index ls_trials, const IpoptData *ip_data, IpoptCalculatedQuantities *ip_cq)
Intermediate Callback method for the user.
Index m_reduced_
Number of constraints in reduced NLP.
virtual void finalize_solution(SolverReturn status, Index n, const Number *x, const Number *z_L, const Number *z_U, Index m, const Number *g, const Number *lambda, Number obj_value, const IpoptData *ip_data, IpoptCalculatedQuantities *ip_cq)
This method is called when the algorithm is complete so the TNLP can store/write the solution.
LinearityType
Type of the constraints.
Index * g_keep_map_
Map from original constraints to new constraints.
Base class for all NLP's that use standard triplet matrix form and dense vectors.
Number Number Number * g_scaling
Index n_x_fix_
Number of variables that are to be fixed to initial value.
virtual bool eval_f(Index n, const Number *x, bool new_x, Number &obj_value)
overload this method to return the value of the objective function
virtual bool eval_h(Index n, const Number *x, bool new_x, Number obj_factor, Index m, const Number *lambda, bool new_lambda, Index nele_hess, Index *iRow, Index *jCol, Number *values)
overload this method to return the hessian of the lagrangian.
Index n_xL_skip_
Number of lower variable bounds to be skipped.
void operator=(const TNLPReducer &)
Overloaded Equals Operator.
Number Number * g
Values of constraint at final point (output only - ignored if set to NULL)
virtual bool get_nlp_info(Index &n, Index &m, Index &nnz_jac_g, Index &nnz_h_lag, IndexStyleEnum &index_style)
IndexStyleEnum
overload this method to return the number of variables and constraints, and the number of non-zeros i...
Index * index_xU_skip_
Array of indices of the upper variable bounds to be skipped.
SolverReturn
enum for the return from the optimize algorithm (obviously we need to add more)
Index * index_x_fix_
Array of indices of the variables that are to be fixed.
virtual bool eval_g(Index n, const Number *x, bool new_x, Index m, Number *g)
overload this method to return the vector of constraint values
Index nnz_jac_g_reduced_
Number of Jacobian nonzeros in the reduced NLP.
virtual bool get_starting_point(Index n, bool init_x, Number *x, bool init_z, Number *z_L, Number *z_U, Index m, bool init_lambda, Number *lambda)
overload this method to return the starting point.
virtual ~TNLPReducer()
Default destructor.
Number Number Index Number Number Index Index Index index_style
indexing style for iRow & jCol, 0 for C style, 1 for Fortran style
AlgorithmMode
enum to indicate the mode in which the algorithm is
Number Number * x_scaling
Specialized CompoundVector class specifically for the algorithm iterates.
Number Number Index m
Number of constraints.