Ipopt
3.12.9

This is a wrapper around a given TNLP class that takes out a list of constraints that are given to the constructor. More...
#include <IpTNLPReducer.hpp>
Public Member Functions  
Constructors/Destructors  
TNLPReducer (TNLP &tnlp, Index n_g_skip, const Index *index_g_skip, Index n_xL_skip, const Index *index_xL_skip, Index n_xU_skip, const Index *index_xU_skip, Index n_x_fix, const Index *index_f_fix)  
Constructor is given the indices of the constraints that should be taken out of the problem statement, as well as the original TNLP. More...  
virtual  ~TNLPReducer () 
Default destructor. More...  
Overloaded methods from TNLP  
virtual bool  get_nlp_info (Index &n, Index &m, Index &nnz_jac_g, Index &nnz_h_lag, IndexStyleEnum &index_style) 
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. More...  
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. More...  
virtual bool  get_variables_linearity (Index n, LinearityType *var_types) 
overload this method to return the variables linearity (TNLP::LINEAR or TNLP::NON_LINEAR). More...  
virtual bool  get_constraints_linearity (Index m, LinearityType *const_types) 
overload this method to return the constraint linearity. More...  
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. More...  
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) for a warm start. More...  
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 More...  
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. More...  
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 More...  
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. More...  
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. More...  
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. More...  
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. More...  
virtual Index  get_number_of_nonlinear_variables () 
virtual bool  get_list_of_nonlinear_variables (Index num_nonlin_vars, Index *pos_nonlin_vars) 
Public Member Functions inherited from Ipopt::TNLP  
DECLARE_STD_EXCEPTION (INVALID_TNLP)  
TNLP ()  
virtual  ~TNLP () 
Default destructor. More...  
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. More...  
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 More...  
Public Member Functions inherited from Ipopt::ReferencedObject  
ReferencedObject ()  
virtual  ~ReferencedObject () 
Index  ReferenceCount () const 
void  AddRef (const Referencer *referencer) const 
void  ReleaseRef (const Referencer *referencer) const 
Private Member Functions  
Default Compiler Generated Methods  
(Hidden to avoid implicit creation/calling). These methods are not implemented and we do not want the compiler to implement them for us, so we declare them private and do not define them. This ensures that they will not be implicitly created/called.  
TNLPReducer ()  
Default Constructor. More...  
TNLPReducer (const TNLPReducer &)  
Copy Constructor. More...  
void  operator= (const TNLPReducer &) 
Overloaded Equals Operator. More...  
Private Attributes  
Index  n_g_skip_ 
Number of constraints to be skipped. More...  
Index *  index_g_skip_ 
Array of indices of the constraints that are to be skipped. More...  
IndexStyleEnum  index_style_orig_ 
Index style for original problem. More...  
Index *  g_keep_map_ 
Map from original constraints to new constraints. More...  
Index  m_reduced_ 
Number of constraints in reduced NLP. More...  
Index  nnz_jac_g_reduced_ 
Number of Jacobian nonzeros in the reduced NLP. More...  
Index  nnz_jac_g_skipped_ 
Number of Jacobian nonzeros that are skipped. More...  
Index *  jac_g_skipped_ 
Array of Jacobian elements that are to be skipped. More...  
Index  n_xL_skip_ 
Number of lower variable bounds to be skipped. More...  
Index *  index_xL_skip_ 
Array of indices of the lower variable bounds to be skipped. More...  
Index  n_xU_skip_ 
Number of upper variable bounds to be skipped. More...  
Index *  index_xU_skip_ 
Array of indices of the upper variable bounds to be skipped. More...  
Index  n_x_fix_ 
Number of variables that are to be fixed to initial value. More...  
Index *  index_x_fix_ 
Array of indices of the variables that are to be fixed. More...  
original TNLP  
SmartPtr< TNLP >  tnlp_ 
Index  m_orig_ 
Index  nnz_jac_g_orig_ 
Additional Inherited Members  
Public Types inherited from Ipopt::TNLP  
enum  LinearityType { LINEAR, NON_LINEAR } 
Type of the constraints. More...  
enum  IndexStyleEnum { C_STYLE =0, FORTRAN_STYLE =1 } 
overload this method to return the number of variables and constraints, and the number of nonzeros in the jacobian and the hessian. More...  
typedef std::map< std::string, std::vector< std::string > >  StringMetaDataMapType 
typedef std::map< std::string, std::vector< Index > >  IntegerMetaDataMapType 
typedef std::map< std::string, std::vector< Number > >  NumericMetaDataMapType 
This is a wrapper around a given TNLP class that takes out a list of constraints that are given to the constructor.
It is provided for convenience, if one wants to experiment with problems that consist of only a subset of the constraints. But keep in mind that this is not efficient, since behind the scenes we are still evaluation all functions and derivatives, and are making copies of the original data.
Definition at line 23 of file IpTNLPReducer.hpp.
Ipopt::TNLPReducer::TNLPReducer  (  TNLP &  tnlp, 
Index  n_g_skip,  
const Index *  index_g_skip,  
Index  n_xL_skip,  
const Index *  index_xL_skip,  
Index  n_xU_skip,  
const Index *  index_xU_skip,  
Index  n_x_fix,  
const Index *  index_f_fix  
) 
Constructor is given the indices of the constraints that should be taken out of the problem statement, as well as the original TNLP.

virtual 
Default destructor.

private 
Default Constructor.

private 
Copy Constructor.

virtual 
Implements Ipopt::TNLP.

virtual 
overload this method to return the information about the bound on the variables and constraints.
The value that indicates that a bound does not exist is specified in the parameters nlp_lower_bound_inf and nlp_upper_bound_inf. By default, nlp_lower_bound_inf is 1e19 and nlp_upper_bound_inf is 1e19. (see TNLPAdapter)
Implements Ipopt::TNLP.

virtual 
overload this method to return scaling parameters.
This is only called if the options are set to retrieve user scaling. There, use_x_scaling (or use_g_scaling) should get set to true only if the variables (or constraints) are to be scaled. This method should return true only if the scaling parameters could be provided.
Reimplemented from Ipopt::TNLP.

virtual 
overload this method to return the variables linearity (TNLP::LINEAR or TNLP::NON_LINEAR).
The var_types array has been allocated with length at least n. (default implementation just return false and does not fill the array).
Reimplemented from Ipopt::TNLP.

virtual 
overload this method to return the constraint linearity.
array has been allocated with length at least n. (default implementation just return false and does not fill the array).
Reimplemented from Ipopt::TNLP.

virtual 
overload this method to return the starting point.
The bool variables indicate whether the algorithm wants you to initialize x, z_L/z_u, and lambda, respectively. If, for some reason, the algorithm wants you to initialize these and you cannot, return false, which will cause Ipopt to stop. You will have to run Ipopt with different options then.
Implements Ipopt::TNLP.

virtual 
overload this method to provide an Ipopt iterate (already in the form Ipopt requires it internally) for a warm start.
Since this is only for expert users, a default dummy implementation is provided and returns false.
Reimplemented from Ipopt::TNLP.

virtual 
overload this method to return the value of the objective function
Implements Ipopt::TNLP.

virtual 
overload this method to return the vector of the gradient of the objective w.r.t.
x
Implements Ipopt::TNLP.

virtual 
overload this method to return the vector of constraint values
Implements Ipopt::TNLP.

virtual 
overload this method to return the jacobian of the constraints.
The vectors iRow and jCol only need to be set once. The first call is used to set the structure only (iRow and jCol will be nonNULL, and values will be NULL) For subsequent calls, iRow and jCol will be NULL.
Implements Ipopt::TNLP.

virtual 
overload this method to return the hessian of the lagrangian.
The vectors iRow and jCol only need to be set once (during the first call). The first call is used to set the structure only (iRow and jCol will be nonNULL, and values will be NULL) For subsequent calls, iRow and jCol will be NULL. This matrix is symmetric  specify the lower diagonal only. A default implementation is provided, in case the user wants to se quasiNewton approximations to estimate the second derivatives and doesn't not neet to implement this method.
Reimplemented from Ipopt::TNLP.

virtual 
This method is called when the algorithm is complete so the TNLP can store/write the solution.
Implements Ipopt::TNLP.

virtual 
Intermediate Callback method for the user.
Providing dummy default implementation. For details see IntermediateCallBack in IpNLP.hpp.
Reimplemented from Ipopt::TNLP.

virtual 
Reimplemented from Ipopt::TNLP.

virtual 
Reimplemented from Ipopt::TNLP.

private 
Overloaded Equals Operator.
Definition at line 126 of file IpTNLPReducer.hpp.

private 
Definition at line 127 of file IpTNLPReducer.hpp.

private 
Definition at line 128 of file IpTNLPReducer.hpp.

private 
Number of constraints to be skipped.
Definition at line 132 of file IpTNLPReducer.hpp.

private 
Array of indices of the constraints that are to be skipped.
This is provided at the beginning in the constructor.
Definition at line 136 of file IpTNLPReducer.hpp.

private 
Index style for original problem.
Internally, we use CStyle now.
Definition at line 140 of file IpTNLPReducer.hpp.

private 
Map from original constraints to new constraints.
A 1 means that a constraint is skipped.
Definition at line 144 of file IpTNLPReducer.hpp.

private 
Number of constraints in reduced NLP.
Definition at line 147 of file IpTNLPReducer.hpp.

private 
Number of Jacobian nonzeros in the reduced NLP.
Definition at line 150 of file IpTNLPReducer.hpp.

private 
Number of Jacobian nonzeros that are skipped.
Definition at line 153 of file IpTNLPReducer.hpp.

private 
Array of Jacobian elements that are to be skipped.
This is in increasing order.
Definition at line 157 of file IpTNLPReducer.hpp.

private 
Number of lower variable bounds to be skipped.
Definition at line 160 of file IpTNLPReducer.hpp.

private 
Array of indices of the lower variable bounds to be skipped.
Definition at line 163 of file IpTNLPReducer.hpp.

private 
Number of upper variable bounds to be skipped.
Definition at line 166 of file IpTNLPReducer.hpp.

private 
Array of indices of the upper variable bounds to be skipped.
Definition at line 169 of file IpTNLPReducer.hpp.

private 
Number of variables that are to be fixed to initial value.
Definition at line 172 of file IpTNLPReducer.hpp.

private 
Array of indices of the variables that are to be fixed.
Definition at line 175 of file IpTNLPReducer.hpp.