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10 #define __IPTNLP_HPP__
24 class IpoptCalculatedQuantities;
120 bool& use_x_scaling,
Index n,
122 bool& use_g_scaling,
Index m,
154 Index m,
bool init_lambda,
244 Number regularization_size,
273 Index* pos_nonlin_vars)
virtual bool get_list_of_nonlinear_variables(Index num_nonlin_vars, Index *pos_nonlin_vars)
Class to organize all the data required by the algorithm.
virtual bool eval_g(Index n, const Number *x, bool new_x, Index m, Number *g)=0
overload this method to return the vector of constraint values
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)=0
This method is called when the algorithm is complete so the TNLP can store/write the solution.
virtual bool get_constraints_linearity(Index m, LinearityType *const_types)
overload this method to return the constraint linearity.
Class for all IPOPT specific calculated quantities.
virtual bool get_bounds_info(Index n, Number *x_l, Number *x_u, Index m, Number *g_l, Number *g_u)=0
overload this method to return the information about the bound on the variables and constraints.
std::map< std::string, std::vector< Index > > IntegerMetaDataMapType
double Number
Type of all numbers.
@ NON_LINEAR
Constraint/Varaible is non-linear.
virtual bool get_var_con_metadata(Index n, StringMetaDataMapType &var_string_md, IntegerMetaDataMapType &var_integer_md, NumericMetaDataMapType &var_numeric_md, Index m, StringMetaDataMapType &con_string_md, IntegerMetaDataMapType &con_integer_md, NumericMetaDataMapType &con_numeric_md)
overload this method to return any meta data for the variables and the constraints
@ LINEAR
Constraint/Variable is linear.
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...
DECLARE_STD_EXCEPTION(INVALID_TNLP)
Number * x
Input: Starting point Output: Optimal solution.
Number Number Index Number Number Index Index nele_hess
Number of non-zero elements in Hessian of Lagrangian.
void operator=(const TNLP &)
Overloaded Equals Operator.
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.
virtual ~TNLP()
Default destructor.
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)=0
overload this method to return the starting point.
std::map< std::string, std::vector< Number > > NumericMetaDataMapType
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.
virtual bool eval_jac_g(Index n, const Number *x, bool new_x, Index m, Index nele_jac, Index *iRow, Index *jCol, Number *values)=0
overload this method to return the jacobian of the constraints.
LinearityType
Type of the constraints.
std::map< std::string, std::vector< std::string > > StringMetaDataMapType
Base class for all NLP's that use standard triplet matrix form and dense vectors.
Number Number Number * g_scaling
virtual bool eval_grad_f(Index n, const Number *x, bool new_x, Number *grad_f)=0
overload this method to return the vector of the gradient of the objective w.r.t.
virtual bool get_variables_linearity(Index n, LinearityType *var_types)
overload this method to return the variables linearity (TNLP::LINEAR or TNLP::NON_LINEAR).
virtual void finalize_metadata(Index n, const StringMetaDataMapType &var_string_md, const IntegerMetaDataMapType &var_integer_md, const NumericMetaDataMapType &var_numeric_md, Index m, const StringMetaDataMapType &con_string_md, const IntegerMetaDataMapType &con_integer_md, const NumericMetaDataMapType &con_numeric_md)
This method is called just before finalize_solution.
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.
Number Number * g
Values of constraint at final point (output only - ignored if set to NULL)
virtual bool eval_f(Index n, const Number *x, bool new_x, Number &obj_value)=0
overload this method to return the value of the objective function
IndexStyleEnum
overload this method to return the number of variables and constraints, and the number of non-zeros i...
virtual bool get_nlp_info(Index &n, Index &m, Index &nnz_jac_g, Index &nnz_h_lag, IndexStyleEnum &index_style)=0
SolverReturn
enum for the return from the optimize algorithm (obviously we need to add more)
Number Number Index Number Number Index Index Index index_style
indexing style for iRow & jCol, 0 for C style, 1 for Fortran style
virtual Index get_number_of_nonlinear_variables()
AlgorithmMode
enum to indicate the mode in which the algorithm is
Number Number * x_scaling
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.
Specialized CompoundVector class specifically for the algorithm iterates.
Number Number Index m
Number of constraints.