This class adapts the TNLP interface so it looks like an NLP interface. More...
#include <IpTNLPAdapter.hpp>
Public Member Functions | |
Constructors/Destructors | |
TNLPAdapter (const SmartPtr< TNLP > tnlp, const SmartPtr< const Journalist > jnlst=NULL) | |
Default constructor. More... | |
virtual | ~TNLPAdapter () |
Default destructor. More... | |
Exceptions | |
DECLARE_STD_EXCEPTION (INVALID_TNLP) | |
DECLARE_STD_EXCEPTION (ERROR_IN_TNLP_DERIVATIVE_TEST) | |
TNLPAdapter Initialization. | |
virtual bool | ProcessOptions (const OptionsList &options, const std::string &prefix) |
Overload if you want the chance to process options or parameters that may be specific to the NLP. More... | |
virtual bool | GetSpaces (SmartPtr< const VectorSpace > &x_space, SmartPtr< const VectorSpace > &c_space, SmartPtr< const VectorSpace > &d_space, SmartPtr< const VectorSpace > &x_l_space, SmartPtr< const MatrixSpace > &px_l_space, SmartPtr< const VectorSpace > &x_u_space, SmartPtr< const MatrixSpace > &px_u_space, SmartPtr< const VectorSpace > &d_l_space, SmartPtr< const MatrixSpace > &pd_l_space, SmartPtr< const VectorSpace > &d_u_space, SmartPtr< const MatrixSpace > &pd_u_space, SmartPtr< const MatrixSpace > &Jac_c_space, SmartPtr< const MatrixSpace > &Jac_d_space, SmartPtr< const SymMatrixSpace > &Hess_lagrangian_space) |
Method for creating the derived vector / matrix types. More... | |
virtual bool | GetBoundsInformation (const Matrix &Px_L, Vector &x_L, const Matrix &Px_U, Vector &x_U, const Matrix &Pd_L, Vector &d_L, const Matrix &Pd_U, Vector &d_U) |
Method for obtaining the bounds information. More... | |
virtual bool | GetStartingPoint (SmartPtr< Vector > x, bool need_x, SmartPtr< Vector > y_c, bool need_y_c, SmartPtr< Vector > y_d, bool need_y_d, SmartPtr< Vector > z_L, bool need_z_L, SmartPtr< Vector > z_U, bool need_z_U) |
Method for obtaining the starting point for all the iterates. More... | |
virtual bool | GetWarmStartIterate (IteratesVector &warm_start_iterate) |
Method for obtaining an entire iterate as a warmstart point. More... | |
TNLPAdapter evaluation routines. | |
virtual bool | Eval_f (const Vector &x, Number &f) |
virtual bool | Eval_grad_f (const Vector &x, Vector &g_f) |
virtual bool | Eval_c (const Vector &x, Vector &c) |
virtual bool | Eval_jac_c (const Vector &x, Matrix &jac_c) |
virtual bool | Eval_d (const Vector &x, Vector &d) |
virtual bool | Eval_jac_d (const Vector &x, Matrix &jac_d) |
virtual bool | Eval_h (const Vector &x, Number obj_factor, const Vector &yc, const Vector &yd, SymMatrix &h) |
virtual void | GetScalingParameters (const SmartPtr< const VectorSpace > x_space, const SmartPtr< const VectorSpace > c_space, const SmartPtr< const VectorSpace > d_space, Number &obj_scaling, SmartPtr< Vector > &x_scaling, SmartPtr< Vector > &c_scaling, SmartPtr< Vector > &d_scaling) const |
Routines to get the scaling parameters. More... | |
Methods for translating data for IpoptNLP into the TNLP data. | |
void | ResortX (const Vector &x, Number *x_orig) |
Sort the primal variables, and add the fixed values in x. More... | |
void | ResortG (const Vector &c, const Vector &d, Number *g_orig) |
void | ResortBnds (const Vector &x_L, Number *x_L_orig, const Vector &x_U, Number *x_U_orig) |
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NLP () | |
Default constructor. More... | |
virtual | ~NLP () |
Default destructor. More... | |
DECLARE_STD_EXCEPTION (USER_SCALING_NOT_IMPLEMENTED) | |
Exceptions. More... | |
DECLARE_STD_EXCEPTION (INVALID_NLP) | |
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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. | |
TNLPAdapter (const TNLPAdapter &) | |
Copy Constructor. More... | |
void | operator= (const TNLPAdapter &) |
Default Assignment Operator. More... | |
Methods to update the values in the local copies of vectors | |
bool | update_local_x (const Vector &x) |
bool | update_local_lambda (const Vector &y_c, const Vector &y_d) |
Internal routines for evaluating g and jac_g. | |
Values stored since they are used in both c and d routines. | |
bool | internal_eval_g (bool new_x) |
bool | internal_eval_jac_g (bool new_x) |
Internal methods for dealing with finite difference approximation | |
void | initialize_findiff_jac (const Index *iRow, const Index *jCol) |
Initialize sparsity structure for finite difference Jacobian. More... | |
Private Attributes | |
Algorithmic parameters | |
Number | nlp_lower_bound_inf_ |
Value for a lower bound that denotes -infinity. More... | |
Number | nlp_upper_bound_inf_ |
Value for a upper bound that denotes infinity. More... | |
FixedVariableTreatmentEnum | fixed_variable_treatment_ |
Flag indicating how fixed variables should be handled. More... | |
Number | bound_relax_factor_ |
Determines relaxation of fixing bound for RELAX_BOUNDS. More... | |
DerivativeTestEnum | derivative_test_ |
Maximal slack for one-sidedly bounded variables. More... | |
Number | derivative_test_perturbation_ |
Size of the perturbation for the derivative test. More... | |
Number | derivative_test_tol_ |
Relative threshold for marking deviation from finite difference test. More... | |
bool | derivative_test_print_all_ |
Flag indicating if all test values should be printed, or only those violating the threshold. More... | |
Index | derivative_test_first_index_ |
Index of first quantity to be checked. More... | |
bool | warm_start_same_structure_ |
Flag indicating whether the TNLP with identical structure has already been solved before. More... | |
HessianApproximationType | hessian_approximation_ |
Flag indicating what Hessian information is to be used. More... | |
Index | num_linear_variables_ |
Number of linear variables. More... | |
JacobianApproxEnum | jacobian_approximation_ |
Flag indicating how Jacobian is computed. More... | |
Number | findiff_perturbation_ |
Size of the perturbation for the derivative approximation. More... | |
Number | point_perturbation_radius_ |
Maximal perturbation of the initial point. More... | |
bool | dependency_detection_with_rhs_ |
Flag indicating if rhs should be considered during dependency detection. More... | |
Number | tol_ |
Overall convergence tolerance. More... | |
Problem Size Data | |
Index | n_full_x_ |
full dimension of x (fixed + non-fixed) More... | |
Index | n_full_g_ |
full dimension of g (c + d) More... | |
Index | nz_jac_c_ |
non-zeros of the jacobian of c More... | |
Index | nz_jac_c_no_extra_ |
non-zeros of the jacobian of c without added constraints for fixed variables. More... | |
Index | nz_jac_d_ |
non-zeros of the jacobian of d More... | |
Index | nz_full_jac_g_ |
number of non-zeros in full-size Jacobian of g More... | |
Index | nz_full_h_ |
number of non-zeros in full-size Hessian More... | |
Index | nz_h_ |
number of non-zeros in the non-fixed-size Hessian More... | |
Index | n_x_fixed_ |
Number of fixed variables. More... | |
TNLP::IndexStyleEnum | index_style_ |
Numbering style of variables and constraints. More... | |
Local copy of spaces (for warm start) | |
SmartPtr< const VectorSpace > | x_space_ |
SmartPtr< const VectorSpace > | c_space_ |
SmartPtr< const VectorSpace > | d_space_ |
SmartPtr< const VectorSpace > | x_l_space_ |
SmartPtr< const MatrixSpace > | px_l_space_ |
SmartPtr< const VectorSpace > | x_u_space_ |
SmartPtr< const MatrixSpace > | px_u_space_ |
SmartPtr< const VectorSpace > | d_l_space_ |
SmartPtr< const MatrixSpace > | pd_l_space_ |
SmartPtr< const VectorSpace > | d_u_space_ |
SmartPtr< const MatrixSpace > | pd_u_space_ |
SmartPtr< const MatrixSpace > | Jac_c_space_ |
SmartPtr< const MatrixSpace > | Jac_d_space_ |
SmartPtr< const SymMatrixSpace > | Hess_lagrangian_space_ |
Local Copy of the Data | |
Number * | full_x_ |
Number * | full_lambda_ |
copy of the full x vector (fixed & non-fixed) More... | |
Number * | full_g_ |
copy of lambda (yc & yd) More... | |
Number * | jac_g_ |
copy of g (c & d) More... | |
Number * | c_rhs_ |
the values for the full jacobian of g More... | |
Tags for deciding when to update internal copies of vectors | |
the rhs values of c | |
TaggedObject::Tag | x_tag_for_iterates_ |
TaggedObject::Tag | y_c_tag_for_iterates_ |
TaggedObject::Tag | y_d_tag_for_iterates_ |
TaggedObject::Tag | x_tag_for_g_ |
TaggedObject::Tag | x_tag_for_jac_g_ |
Internal Permutation Spaces and matrices | |
SmartPtr< ExpansionMatrix > | P_x_full_x_ |
Expansion from fixed x (ipopt) to full x. More... | |
SmartPtr< ExpansionMatrixSpace > | P_x_full_x_space_ |
SmartPtr< ExpansionMatrix > | P_x_x_L_ |
Expansion from fixed x_L (ipopt) to full x. More... | |
SmartPtr< ExpansionMatrixSpace > | P_x_x_L_space_ |
SmartPtr< ExpansionMatrix > | P_x_x_U_ |
Expansion from fixed x_U (ipopt) to full x. More... | |
SmartPtr< ExpansionMatrixSpace > | P_x_x_U_space_ |
SmartPtr< ExpansionMatrixSpace > | P_c_g_space_ |
Expansion from c only (ipopt) to full ampl c. More... | |
SmartPtr< ExpansionMatrix > | P_c_g_ |
SmartPtr< ExpansionMatrixSpace > | P_d_g_space_ |
Expansion from d only (ipopt) to full ampl d. More... | |
SmartPtr< ExpansionMatrix > | P_d_g_ |
Index * | jac_idx_map_ |
Index * | h_idx_map_ |
Index * | x_fixed_map_ |
Position of fixed variables. More... | |
Data for finite difference approximations of derivatives | |
Index | findiff_jac_nnz_ |
Number of unique nonzeros in constraint Jacobian. More... | |
Index * | findiff_jac_ia_ |
Start position for nonzero indices in ja for each column of Jacobian. More... | |
Index * | findiff_jac_ja_ |
Ordered by columns, for each column the row indices in Jacobian. More... | |
Index * | findiff_jac_postriplet_ |
Position of entry in original triplet matrix. More... | |
Number * | findiff_x_l_ |
Copy of the lower bounds. More... | |
Number * | findiff_x_u_ |
Copy of the upper bounds. More... | |
Solution Reporting Methods | |
enum | FixedVariableTreatmentEnum { MAKE_PARAMETER = 0, MAKE_CONSTRAINT, RELAX_BOUNDS } |
Enum for treatment of fixed variables option. More... | |
enum | DerivativeTestEnum { NO_TEST = 0, FIRST_ORDER_TEST, SECOND_ORDER_TEST, ONLY_SECOND_ORDER_TEST } |
Enum for specifying which derivative test is to be performed. More... | |
enum | JacobianApproxEnum { JAC_EXACT = 0, JAC_FINDIFF_VALUES } |
Enum for specifying technique for computing Jacobian. More... | |
virtual void | FinalizeSolution (SolverReturn status, const Vector &x, const Vector &z_L, const Vector &z_U, const Vector &c, const Vector &d, const Vector &y_c, const Vector &y_d, Number obj_value, const IpoptData *ip_data, IpoptCalculatedQuantities *ip_cq) |
This method is called at the very end of the optimization. More... | |
virtual bool | IntermediateCallBack (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) |
This method is called once per iteration, after the iteration summary output has been printed. More... | |
virtual void | GetQuasiNewtonApproximationSpaces (SmartPtr< VectorSpace > &approx_space, SmartPtr< Matrix > &P_approx) |
Method returning information on quasi-Newton approximation. More... | |
bool | CheckDerivatives (DerivativeTestEnum deriv_test, Index deriv_test_start_index) |
Method for performing the derivative test. More... | |
SmartPtr< TNLP > | tnlp () const |
Accessor method for the underlying TNLP. More... | |
static void | RegisterOptions (SmartPtr< RegisteredOptions > roptions) |
Method implementing the detection of linearly dependent equality constraints | |
SmartPtr< TNLP > | tnlp_ |
Pointer to the TNLP class (class specific to Number* vectors and triplet matrices) More... | |
SmartPtr< const Journalist > | jnlst_ |
Journalist. More... | |
SmartPtr< TDependencyDetector > | dependency_detector_ |
Object that can be used to detect linearly dependent rows in the equality constraint Jacobian. More... | |
bool | DetermineDependentConstraints (Index n_x_var, const Index *x_not_fixed_map, const Number *x_l, const Number *x_u, const Number *g_l, const Number *g_u, Index n_c, const Index *c_map, std::list< Index > &c_deps) |
This class adapts the TNLP interface so it looks like an NLP interface.
This is an Adapter class (Design Patterns) that converts a TNLP to an NLP. This allows users to write to the "more convenient" TNLP interface.
Definition at line 29 of file IpTNLPAdapter.hpp.
Enum for treatment of fixed variables option.
Enumerator | |
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MAKE_PARAMETER | |
MAKE_CONSTRAINT | |
RELAX_BOUNDS |
Definition at line 204 of file IpTNLPAdapter.hpp.
Enum for specifying which derivative test is to be performed.
Enumerator | |
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NO_TEST | |
FIRST_ORDER_TEST | |
SECOND_ORDER_TEST | |
ONLY_SECOND_ORDER_TEST |
Definition at line 212 of file IpTNLPAdapter.hpp.
Enum for specifying technique for computing Jacobian.
Enumerator | |
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JAC_EXACT | |
JAC_FINDIFF_VALUES |
Definition at line 221 of file IpTNLPAdapter.hpp.
Ipopt::TNLPAdapter::TNLPAdapter | ( | const SmartPtr< TNLP > | tnlp, |
const SmartPtr< const Journalist > | jnlst = NULL |
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Default constructor.
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Default destructor.
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Copy Constructor.
Ipopt::TNLPAdapter::DECLARE_STD_EXCEPTION | ( | INVALID_TNLP | ) |
Ipopt::TNLPAdapter::DECLARE_STD_EXCEPTION | ( | ERROR_IN_TNLP_DERIVATIVE_TEST | ) |
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Overload if you want the chance to process options or parameters that may be specific to the NLP.
Reimplemented from Ipopt::NLP.
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Method for obtaining the bounds information.
Implements Ipopt::NLP.
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Method for obtaining the starting point for all the iterates.
Implements Ipopt::NLP.
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Method for obtaining an entire iterate as a warmstart point.
The incoming IteratesVector has to be filled.
Reimplemented from Ipopt::NLP.
Implements Ipopt::NLP.
Implements Ipopt::NLP.
Implements Ipopt::NLP.
Implements Ipopt::NLP.
Implements Ipopt::NLP.
Implements Ipopt::NLP.
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Implements Ipopt::NLP.
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Routines to get the scaling parameters.
These do not need to be overloaded unless the options are set for user scaling.
Reimplemented from Ipopt::NLP.
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This method is called at the very end of the optimization.
It provides the final iterate to the user, so that it can be stored as the solution. The status flag indicates the outcome of the optimization, where SolverReturn is defined in IpAlgTypes.hpp.
Reimplemented from Ipopt::NLP.
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This method is called once per iteration, after the iteration summary output has been printed.
It provides the current information to the user to do with it anything she wants. It also allows the user to ask for a premature termination of the optimization by returning false, in which case Ipopt will terminate with a corresponding return status. The basic information provided in the argument list has the quantities values printed in the iteration summary line. If more information is required, a user can obtain it from the IpData and IpCalculatedQuantities objects. However, note that the provided quantities are all for the problem that Ipopt sees, i.e., the quantities might be scaled, fixed variables might be sorted out, etc. The status indicates things like whether the algorithm is in the restoration phase... In the restoration phase, the dual variables are probably not not changing.
Reimplemented from Ipopt::NLP.
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Method returning information on quasi-Newton approximation.
Reimplemented from Ipopt::NLP.
bool Ipopt::TNLPAdapter::CheckDerivatives | ( | DerivativeTestEnum | deriv_test, |
Index | deriv_test_start_index | ||
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Method for performing the derivative test.
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Accessor method for the underlying TNLP.
Definition at line 238 of file IpTNLPAdapter.hpp.
Sort the primal variables, and add the fixed values in x.
void Ipopt::TNLPAdapter::ResortBnds | ( | const Vector & | x_L, |
Number * | x_L_orig, | ||
const Vector & | x_U, | ||
Number * | x_U_orig | ||
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Default Assignment Operator.
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Initialize sparsity structure for finite difference Jacobian.
Pointer to the TNLP class (class specific to Number* vectors and triplet matrices)
Definition at line 304 of file IpTNLPAdapter.hpp.
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Definition at line 307 of file IpTNLPAdapter.hpp.
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Object that can be used to detect linearly dependent rows in the equality constraint Jacobian.
Definition at line 310 of file IpTNLPAdapter.hpp.
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Value for a lower bound that denotes -infinity.
Definition at line 315 of file IpTNLPAdapter.hpp.
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Value for a upper bound that denotes infinity.
Definition at line 317 of file IpTNLPAdapter.hpp.
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Flag indicating how fixed variables should be handled.
Definition at line 319 of file IpTNLPAdapter.hpp.
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Determines relaxation of fixing bound for RELAX_BOUNDS.
Definition at line 321 of file IpTNLPAdapter.hpp.
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Maximal slack for one-sidedly bounded variables.
If a variable has only one bound, say a lower bound xL, then an upper bound xL + max_onesided_bound_slack_. If this value is zero, no upper bound is added. Whether and which derivative test should be performed at starting point
Definition at line 328 of file IpTNLPAdapter.hpp.
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Size of the perturbation for the derivative test.
Definition at line 330 of file IpTNLPAdapter.hpp.
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Relative threshold for marking deviation from finite difference test.
Definition at line 332 of file IpTNLPAdapter.hpp.
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Flag indicating if all test values should be printed, or only those violating the threshold.
Definition at line 334 of file IpTNLPAdapter.hpp.
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Index of first quantity to be checked.
Definition at line 336 of file IpTNLPAdapter.hpp.
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Flag indicating whether the TNLP with identical structure has already been solved before.
Definition at line 338 of file IpTNLPAdapter.hpp.
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Flag indicating what Hessian information is to be used.
Definition at line 340 of file IpTNLPAdapter.hpp.
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Number of linear variables.
Definition at line 342 of file IpTNLPAdapter.hpp.
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Flag indicating how Jacobian is computed.
Definition at line 344 of file IpTNLPAdapter.hpp.
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Size of the perturbation for the derivative approximation.
Definition at line 346 of file IpTNLPAdapter.hpp.
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Maximal perturbation of the initial point.
Definition at line 348 of file IpTNLPAdapter.hpp.
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Flag indicating if rhs should be considered during dependency detection.
Definition at line 350 of file IpTNLPAdapter.hpp.
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Overall convergence tolerance.
Definition at line 353 of file IpTNLPAdapter.hpp.
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full dimension of x (fixed + non-fixed)
Definition at line 359 of file IpTNLPAdapter.hpp.
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full dimension of g (c + d)
Definition at line 361 of file IpTNLPAdapter.hpp.
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non-zeros of the jacobian of c
Definition at line 363 of file IpTNLPAdapter.hpp.
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non-zeros of the jacobian of c without added constraints for fixed variables.
Definition at line 365 of file IpTNLPAdapter.hpp.
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non-zeros of the jacobian of d
Definition at line 367 of file IpTNLPAdapter.hpp.
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number of non-zeros in full-size Jacobian of g
Definition at line 369 of file IpTNLPAdapter.hpp.
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number of non-zeros in full-size Hessian
Definition at line 371 of file IpTNLPAdapter.hpp.
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number of non-zeros in the non-fixed-size Hessian
Definition at line 373 of file IpTNLPAdapter.hpp.
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Number of fixed variables.
Definition at line 375 of file IpTNLPAdapter.hpp.
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Numbering style of variables and constraints.
Definition at line 379 of file IpTNLPAdapter.hpp.
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Definition at line 383 of file IpTNLPAdapter.hpp.
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Definition at line 384 of file IpTNLPAdapter.hpp.
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Definition at line 385 of file IpTNLPAdapter.hpp.
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Definition at line 386 of file IpTNLPAdapter.hpp.
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Definition at line 387 of file IpTNLPAdapter.hpp.
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Definition at line 388 of file IpTNLPAdapter.hpp.
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Definition at line 389 of file IpTNLPAdapter.hpp.
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Definition at line 390 of file IpTNLPAdapter.hpp.
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Definition at line 391 of file IpTNLPAdapter.hpp.
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Definition at line 392 of file IpTNLPAdapter.hpp.
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Definition at line 393 of file IpTNLPAdapter.hpp.
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Definition at line 394 of file IpTNLPAdapter.hpp.
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Definition at line 395 of file IpTNLPAdapter.hpp.
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Definition at line 396 of file IpTNLPAdapter.hpp.
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Definition at line 401 of file IpTNLPAdapter.hpp.
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copy of the full x vector (fixed & non-fixed)
Definition at line 402 of file IpTNLPAdapter.hpp.
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copy of lambda (yc & yd)
Definition at line 403 of file IpTNLPAdapter.hpp.
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copy of g (c & d)
Definition at line 404 of file IpTNLPAdapter.hpp.
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the values for the full jacobian of g
Definition at line 405 of file IpTNLPAdapter.hpp.
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Definition at line 410 of file IpTNLPAdapter.hpp.
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Definition at line 411 of file IpTNLPAdapter.hpp.
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Definition at line 412 of file IpTNLPAdapter.hpp.
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Definition at line 413 of file IpTNLPAdapter.hpp.
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Definition at line 414 of file IpTNLPAdapter.hpp.
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Expansion from fixed x (ipopt) to full x.
Definition at line 442 of file IpTNLPAdapter.hpp.
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Definition at line 443 of file IpTNLPAdapter.hpp.
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Expansion from fixed x_L (ipopt) to full x.
Definition at line 446 of file IpTNLPAdapter.hpp.
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Definition at line 447 of file IpTNLPAdapter.hpp.
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Expansion from fixed x_U (ipopt) to full x.
Definition at line 450 of file IpTNLPAdapter.hpp.
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Definition at line 451 of file IpTNLPAdapter.hpp.
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Expansion from c only (ipopt) to full ampl c.
Definition at line 454 of file IpTNLPAdapter.hpp.
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Definition at line 455 of file IpTNLPAdapter.hpp.
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Expansion from d only (ipopt) to full ampl d.
Definition at line 458 of file IpTNLPAdapter.hpp.
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Definition at line 459 of file IpTNLPAdapter.hpp.
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Definition at line 461 of file IpTNLPAdapter.hpp.
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Definition at line 462 of file IpTNLPAdapter.hpp.
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Position of fixed variables.
This is required for a warm start
Definition at line 465 of file IpTNLPAdapter.hpp.
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Number of unique nonzeros in constraint Jacobian.
Definition at line 471 of file IpTNLPAdapter.hpp.
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Start position for nonzero indices in ja for each column of Jacobian.
Definition at line 473 of file IpTNLPAdapter.hpp.
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Ordered by columns, for each column the row indices in Jacobian.
Definition at line 475 of file IpTNLPAdapter.hpp.
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Position of entry in original triplet matrix.
Definition at line 477 of file IpTNLPAdapter.hpp.
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Copy of the lower bounds.
Definition at line 479 of file IpTNLPAdapter.hpp.
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Copy of the upper bounds.
Definition at line 481 of file IpTNLPAdapter.hpp.