This class adapts the TNLP interface so it looks like an NLP interface. More...
#include <IpTNLPAdapter.hpp>
Public Types | |
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... | |
Public Member Functions | |
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... | |
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... | |
Solution Reporting Methods | |
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... | |
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, bool clearorig=true) |
Provides values for lower and upper bounds on variables for given Ipopt-internal vectors. More... | |
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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 |
Static Public Member Functions | |
static void | RegisterOptions (SmartPtr< RegisteredOptions > roptions) |
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 | |
TNLP::IndexStyleEnum | index_style_ |
Numbering style of variables and constraints. More... | |
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... | |
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... | |
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, | ||
bool | clearorig = true |
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Provides values for lower and upper bounds on variables for given Ipopt-internal vectors.
Similar to ResortX, but does so for two arrays and does not set any values for fixed variables.
x_L | internal values for lower bounds on x |
x_L_orig | vector to fill with values from x_L |
x_U | internal values for upper bounds on x |
x_U_orig | vector to fill with values from x_U |
clearorig | whether to initialize complete x_L_orig and x_U_orig to 0.0 before setting values for non-fixed variables |
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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 309 of file IpTNLPAdapter.hpp.
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Definition at line 312 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 315 of file IpTNLPAdapter.hpp.
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Value for a lower bound that denotes -infinity.
Definition at line 320 of file IpTNLPAdapter.hpp.
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Value for a upper bound that denotes infinity.
Definition at line 322 of file IpTNLPAdapter.hpp.
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Flag indicating how fixed variables should be handled.
Definition at line 324 of file IpTNLPAdapter.hpp.
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Determines relaxation of fixing bound for RELAX_BOUNDS.
Definition at line 326 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 333 of file IpTNLPAdapter.hpp.
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Size of the perturbation for the derivative test.
Definition at line 335 of file IpTNLPAdapter.hpp.
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Relative threshold for marking deviation from finite difference test.
Definition at line 337 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 339 of file IpTNLPAdapter.hpp.
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Index of first quantity to be checked.
Definition at line 341 of file IpTNLPAdapter.hpp.
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Flag indicating whether the TNLP with identical structure has already been solved before.
Definition at line 343 of file IpTNLPAdapter.hpp.
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Flag indicating what Hessian information is to be used.
Definition at line 345 of file IpTNLPAdapter.hpp.
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Number of linear variables.
Definition at line 347 of file IpTNLPAdapter.hpp.
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Flag indicating how Jacobian is computed.
Definition at line 349 of file IpTNLPAdapter.hpp.
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Size of the perturbation for the derivative approximation.
Definition at line 351 of file IpTNLPAdapter.hpp.
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Maximal perturbation of the initial point.
Definition at line 353 of file IpTNLPAdapter.hpp.
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Flag indicating if rhs should be considered during dependency detection.
Definition at line 355 of file IpTNLPAdapter.hpp.
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Overall convergence tolerance.
Definition at line 358 of file IpTNLPAdapter.hpp.
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full dimension of x (fixed + non-fixed)
Definition at line 364 of file IpTNLPAdapter.hpp.
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full dimension of g (c + d)
Definition at line 366 of file IpTNLPAdapter.hpp.
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non-zeros of the jacobian of c
Definition at line 368 of file IpTNLPAdapter.hpp.
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non-zeros of the jacobian of c without added constraints for fixed variables.
Definition at line 370 of file IpTNLPAdapter.hpp.
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non-zeros of the jacobian of d
Definition at line 372 of file IpTNLPAdapter.hpp.
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number of non-zeros in full-size Jacobian of g
Definition at line 374 of file IpTNLPAdapter.hpp.
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number of non-zeros in full-size Hessian
Definition at line 376 of file IpTNLPAdapter.hpp.
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number of non-zeros in the non-fixed-size Hessian
Definition at line 378 of file IpTNLPAdapter.hpp.
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Number of fixed variables.
Definition at line 380 of file IpTNLPAdapter.hpp.
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Numbering style of variables and constraints.
Definition at line 384 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 397 of file IpTNLPAdapter.hpp.
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Definition at line 398 of file IpTNLPAdapter.hpp.
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Definition at line 399 of file IpTNLPAdapter.hpp.
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Definition at line 400 of file IpTNLPAdapter.hpp.
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Definition at line 401 of file IpTNLPAdapter.hpp.
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Definition at line 406 of file IpTNLPAdapter.hpp.
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copy of the full x vector (fixed & non-fixed)
Definition at line 407 of file IpTNLPAdapter.hpp.
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copy of lambda (yc & yd)
Definition at line 408 of file IpTNLPAdapter.hpp.
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copy of g (c & d)
Definition at line 409 of file IpTNLPAdapter.hpp.
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the values for the full jacobian of g
Definition at line 410 of file IpTNLPAdapter.hpp.
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Definition at line 415 of file IpTNLPAdapter.hpp.
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Definition at line 416 of file IpTNLPAdapter.hpp.
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Definition at line 417 of file IpTNLPAdapter.hpp.
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Definition at line 418 of file IpTNLPAdapter.hpp.
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Definition at line 419 of file IpTNLPAdapter.hpp.
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Expansion from fixed x (ipopt) to full x.
Definition at line 447 of file IpTNLPAdapter.hpp.
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Definition at line 448 of file IpTNLPAdapter.hpp.
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Expansion from fixed x_L (ipopt) to full x.
Definition at line 451 of file IpTNLPAdapter.hpp.
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Definition at line 452 of file IpTNLPAdapter.hpp.
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Expansion from fixed x_U (ipopt) to full x.
Definition at line 455 of file IpTNLPAdapter.hpp.
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Definition at line 456 of file IpTNLPAdapter.hpp.
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Expansion from c only (ipopt) to full ampl c.
Definition at line 459 of file IpTNLPAdapter.hpp.
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Definition at line 460 of file IpTNLPAdapter.hpp.
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Expansion from d only (ipopt) to full ampl d.
Definition at line 463 of file IpTNLPAdapter.hpp.
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Definition at line 464 of file IpTNLPAdapter.hpp.
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Definition at line 466 of file IpTNLPAdapter.hpp.
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Definition at line 467 of file IpTNLPAdapter.hpp.
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Position of fixed variables.
This is required for a warm start
Definition at line 470 of file IpTNLPAdapter.hpp.
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Number of unique nonzeros in constraint Jacobian.
Definition at line 476 of file IpTNLPAdapter.hpp.
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Start position for nonzero indices in ja for each column of Jacobian.
Definition at line 478 of file IpTNLPAdapter.hpp.
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Ordered by columns, for each column the row indices in Jacobian.
Definition at line 480 of file IpTNLPAdapter.hpp.
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Position of entry in original triplet matrix.
Definition at line 482 of file IpTNLPAdapter.hpp.
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Copy of the lower bounds.
Definition at line 484 of file IpTNLPAdapter.hpp.
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Copy of the upper bounds.
Definition at line 486 of file IpTNLPAdapter.hpp.