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NLPInterfacePack::NLPDirect Class Referenceabstract

Interface providing only direct first order sensitivity information. More...

#include <NLPInterfacePack_NLPDirect.hpp>

Inheritance diagram for NLPInterfacePack::NLPDirect:
Inheritance graph
[legend]

Public Types

typedef Teuchos::RCP< const
Teuchos::AbstractFactory
< MatrixOp > > 
mat_fcty_ptr_t
 
typedef Teuchos::RCP< const
Teuchos::AbstractFactory
< MatrixSymOp > > 
mat_sym_fcty_ptr_t
 
typedef Teuchos::RCP< const
Teuchos::AbstractFactory
< MatrixSymOpNonsing > > 
mat_sym_nonsing_fcty_ptr_t
 
- Public Types inherited from NLPInterfacePack::NLP
typedef AbstractLinAlgPack::Vector Vector
 
typedef
AbstractLinAlgPack::VectorMutable 
VectorMutable
 
typedef Teuchos::RCP< const
VectorSpace > 
vec_space_ptr_t
 
typedef Teuchos::RCP< const
OptionsFromStreamPack::OptionsFromStream
options_ptr_t
 

Public Member Functions

void set_factories (const mat_sym_fcty_ptr_t &factory_transDtD, const mat_sym_nonsing_fcty_ptr_t &factory_S)
 Initialize the factory objects for the special matrices for D'*D and S = I + D'*D. More...
 
- Public Member Functions inherited from NLPInterfacePack::NLPObjGrad
 NLPObjGrad ()
 Initialize to no reference set to calculation quanities. More...
 
void initialize (bool test_setup)
 Initialize the NLP for its first use. More...
 
virtual bool supports_Gf () const
 Determine if the objective gradient is supported or not. More...
 
virtual bool supports_Gf_prod () const
 Determine if the objective gradient product is supported or not. More...
 
virtual void set_Gf (VectorMutable *Gf)
 Set a pointer to a vector to be updated when this->calc_Gf() is called. More...
 
virtual VectorMutableget_Gf ()
 Return pointer passed to this->set_Gf(). More...
 
virtual VectorMutableGf ()
 Returns non-const *this->get_Gf(). More...
 
virtual const VectorGf () const
 Returns const *this->get_Gf(). More...
 
void unset_quantities ()
 Call to unset all storage quantities (both in this class and all subclasses). More...
 
virtual void calc_Gf (const Vector &x, bool newx=true) const
 Update the vector for Gf at the point x and put it in the stored reference. More...
 
virtual value_type calc_Gf_prod (const Vector &x, const Vector &d, bool newx=true) const
 Calculate the inner product Gf(x)'*d at the point x and put it in the stored reference. More...
 
virtual size_type num_Gf_evals () const
 Objective gradient evaluations count. More...
 
- Public Member Functions inherited from NLPInterfacePack::NLP
const ZeroOrderInfo zero_order_info () const
 Return pointer to set quantities. More...
 
const ZeroOrderInfo zero_order_info_breve () const
 Return pointer to set hat quantities. More...
 
 NLP ()
 Initialize to no reference set to calculation quanities. More...
 
virtual ~NLP ()
 Destructor that cleans all the memory it owns. More...
 
virtual void force_xinit_in_bounds (bool force_xinit_in_bounds)=0
 Set if the initial point must be within the bounds. More...
 
virtual bool force_xinit_in_bounds () const =0
 Returns if the initial point must be within the bounds. More...
 
virtual void set_options (const options_ptr_t &options)
 Set the options that this NLP may be interested in. More...
 
virtual const options_ptr_tget_options () const
 Get the OptionsFromStream object being used to extract the options from. More...
 
virtual bool is_initialized () const =0
 Return if this is initialized. More...
 
virtual size_type n () const
 Return the number of variables. More...
 
virtual size_type m () const
 Return the number of general equality constraints. More...
 
virtual vec_space_ptr_t space_x () const =0
 Vector space object for unknown variables x (dimension n). More...
 
virtual vec_space_ptr_t space_c () const =0
 Vector space object for general equality constraints c(x) (dimension m). More...
 
virtual size_type num_bounded_x () const =0
 Returns the number of variables in x(i) for which xl(i)> -infinite_bound() or xu(i) < +infinite_bound(). More...
 
virtual const Vectorxl () const =0
 Returns the lower bounds on the variables x. More...
 
virtual const Vectorxu () const =0
 Returns a reference to the vector of upper bounds on the variables x. More...
 
virtual value_type max_var_bounds_viol () const =0
 Set the maximum absolute value for which the variable bounds may be violated by when computing function and gradient values. More...
 
virtual const Vectorxinit () const =0
 Returns a reference to the vector of the initial guess for the solution x. More...
 
virtual void get_init_lagrange_mult (VectorMutable *lambda, VectorMutable *nu) const
 Get the initial value of the Lagrange multipliers lambda. More...
 
virtual void set_f (value_type *f)
 Set a pointer to an value to be updated when this->calc_f() is called. More...
 
virtual value_type * get_f ()
 Return pointer passed to this->set_f(). More...
 
virtual value_type & f ()
 Returns non-const *this->get_f(). More...
 
virtual const value_type & f () const
 Returns const *this->get_f(). More...
 
virtual void set_c (VectorMutable *c)
 Set a pointer to a vector to be updated when this->calc_c() is called. More...
 
virtual VectorMutableget_c ()
 Return pointer passed to this->set_c(). More...
 
virtual VectorMutablec ()
 Returns non-const *this->get_c(). More...
 
virtual const Vectorc () const
 Returns const *this->get_c(). More...
 
virtual void scale_f (value_type scale_f)=0
 Set the scaling of the objective function. More...
 
virtual value_type scale_f () const =0
 Return the scaling being used for the objective function. More...
 
virtual void calc_f (const Vector &x, bool newx=true) const
 Update the value for the objective f at the point x and put it in the stored reference. More...
 
virtual void calc_c (const Vector &x, bool newx=true) const
 Update the constraint residual vector for c at the point x and put it in the stored reference. More...
 
virtual void report_final_solution (const Vector &x, const Vector *lambda, const Vector *nu, bool is_optimal)
 Used by the solver to report the final solution and multipliers. More...
 
virtual size_type num_f_evals () const
 Gives the number of object function f(x) evaluations called by the solver since initialize() was called. More...
 
virtual size_type num_c_evals () const
 Gives the number of constraint function c(x) evaluations called by the solver since initialize() was called. Throws exception if this->m() == 0. More...
 
virtual size_type ns () const
 Return the number of slack variables (i.e. number of general inequalities). More...
 
virtual vec_space_ptr_t space_c_breve () const
 Vector space object for the original equalities c_breve(x_breve) More...
 
virtual vec_space_ptr_t space_h_breve () const
 Vector space object for the original inequalities h_breve(x_breve) More...
 
virtual const Vectorhl_breve () const
 Returns a reference to the vector of lower bounds on the general inequality constraints h_breve(x_breve). More...
 
virtual const Vectorhu_breve () const
 Returns a reference to the vector of upper bounds on the general inequality constraints h_breve(x_breve). More...
 
virtual void set_c_breve (VectorMutable *c_breve)
 Set a pointer to a vector to be updated when this->calc_c_breve() is called. More...
 
virtual VectorMutableget_c_breve ()
 Return pointer passed to this->set_c_breve(). More...
 
virtual VectorMutablec_breve ()
 Returns non-const *this->get_c_breve(). More...
 
virtual const Vectorc_breve () const
 Returns const *this->get_c_breve(). More...
 
virtual void set_h_breve (VectorMutable *h_breve)
 Set a pointer to a vector to be updated when this->calc_h_breve() is called. More...
 
virtual VectorMutableget_h_breve ()
 Return pointer passed to this->set_h_breve(). More...
 
virtual VectorMutableh_breve ()
 Returns non-const *this->get_h_breve(). More...
 
virtual const Vectorh_breve () const
 Returns const *this->get_h_breve(). More...
 
virtual const Permutation & P_var () const
 Return the permutation object for the variables. More...
 
virtual const Permutation & P_equ () const
 Return the permutation object for the constraints. More...
 
virtual void calc_c_breve (const Vector &x, bool newx=true) const
 Update the constraint residual vector for c_breve at the point x and put it in the stored reference. More...
 
virtual void calc_h_breve (const Vector &x, bool newx=true) const
 Update the constraint residual vector for h_breve at the point x and put it in the stored reference. More...
 
- Public Member Functions inherited from Teuchos::VerboseObject< NLP >
TEUCHOSPARAMETERLIST_LIB_DLL_EXPORT
RCP< const ParameterList
getValidVerboseObjectSublist ()
 
TEUCHOSPARAMETERLIST_LIB_DLL_EXPORT
void 
setupVerboseObjectSublist (ParameterList *paramList)
 
TEUCHOSPARAMETERLIST_LIB_DLL_EXPORT
void 
readVerboseObjectSublist (ParameterList *paramList, RCP< FancyOStream > *oStream, EVerbosityLevel *verbLevel)
 
void readVerboseObjectSublist (ParameterList *paramList, VerboseObject< NLP > *verboseObject)
 
 VerboseObject (const EVerbosityLevel verbLevel=VERB_DEFAULT, const RCP< FancyOStream > &oStream=Teuchos::null)
 
virtual void initializeVerboseObject (const EVerbosityLevel verbLevel=VERB_DEFAULT, const RCP< FancyOStream > &oStream=Teuchos::null)
 
virtual const VerboseObjectsetVerbLevel (const EVerbosityLevel verbLevel) const
 
virtual const VerboseObjectsetOverridingVerbLevel (const EVerbosityLevel verbLevel) const
 
virtual EVerbosityLevel getVerbLevel () const
 

Private Attributes

mat_sym_fcty_ptr_t factory_transDtD_
 
mat_sym_nonsing_fcty_ptr_t factory_S_
 

Dimensionality

virtual size_type r () const
 Returns the number of decomposed equality constraints (r <= m). More...
 

Ranges for dependent and independent variables and decomposed and undecomposed equalities

virtual Range1D var_dep () const
 Return the range of dependent (i.e. basic) variables. More...
 
virtual Range1D var_indep () const
 Return the range of independent (i.e. nonbasic) variables. More...
 
virtual Range1D con_decomp () const
 Return the range of decomposed equality constraints. More...
 
virtual Range1D con_undecomp () const
 Return the range of undecomposed equality constraints. More...
 

Matrix factory objects

virtual const mat_fcty_ptr_t factory_GcU () const
 Return a matrix factory object for creating GcU. More...
 
virtual const mat_fcty_ptr_t factory_D () const =0
 Return a matrix factory object for D = -inv(C)*N {abstract}. More...
 
virtual const mat_fcty_ptr_t factory_Uz () const
 Return a matrix factory object for Uz = F + E * D. More...
 
virtual const mat_fcty_ptr_t factory_GcUD () const
 Return a matrix factory object for a mutable matrix compatible with GcU(var_dep). More...
 
virtual const mat_sym_fcty_ptr_t factory_transDtD () const
 Returns a matrix factory for the result of J = D'*D More...
 
virtual const
mat_sym_nonsing_fcty_ptr_t 
factory_S () const
 Returns a matrix factory for the result of S = I + D'*D More...
 

Calculation members

virtual void calc_point (const Vector &x, value_type *f, VectorMutable *c, bool recalc_c, VectorMutable *Gf, VectorMutable *py, VectorMutable *rGf, MatrixOp *GcU, MatrixOp *D, MatrixOp *Uz) const =0
 Compute all of the needed quanities for direct sensitivities. More...
 
virtual void calc_semi_newton_step (const Vector &x, VectorMutable *c, bool recalc_c, VectorMutable *py) const =0
 Calculate an approximate newton step given the Jacobian computed for the last call to calc_point(). More...
 

Overridden from NLP

void initialize (bool test_setup)
 Initialize the NLP for its first use. More...
 

Additional Inherited Members

- Static Public Member Functions inherited from NLPInterfacePack::NLP
static value_type infinite_bound ()
 Value for an infinite bound. More...
 
- Static Public Member Functions inherited from Teuchos::VerboseObject< NLP >
static void setDefaultVerbLevel (const EVerbosityLevel defaultVerbLevel)
 
static EVerbosityLevel getDefaultVerbLevel ()
 
- Protected Member Functions inherited from NLPInterfacePack::NLPObjGrad
const ObjGradInfo obj_grad_info () const
 Return objective gradient and zero order information. More...
 
virtual void imp_calc_Gf (const Vector &x, bool newx, const ObjGradInfo &obj_grad_info) const =0
 Overridden to compute f(x) and perhaps c(x) (if multiple calculaiton = true). More...
 
- Protected Member Functions inherited from NLPInterfacePack::NLP
template<class T >
void assert_ref_set (T *p, std::string info) const
 Assert referece has been set for a quanity. More...
 
virtual void imp_calc_f (const Vector &x, bool newx, const ZeroOrderInfo &zero_order_info) const =0
 Overridden to compute f(x) (and perhaps other quantities if set). More...
 
virtual void imp_calc_c (const Vector &x, bool newx, const ZeroOrderInfo &zero_order_info) const =0
 Overridden to compute c(x) and perhaps f(x) and/or h(x) (if multiple calculaiton = true). More...
 
virtual void imp_calc_c_breve (const Vector &x, bool newx, const ZeroOrderInfo &zero_order_info_breve) const
 Overridden to compute c_breve(x_breve) and perhaps f(x) and/or h_breve(x_breve) More...
 
virtual void imp_calc_h_breve (const Vector &x, bool newx, const ZeroOrderInfo &zero_order_info_breve) const
 Overridden to compute h_breve(x_breve) and perhaps f(x) and/or c_breve(x_breve). More...
 

Detailed Description

Interface providing only direct first order sensitivity information.

Overview:

This interface defines a basis for the equality constriants and then only certain linear systems with this basis are solved for. This interface is useful in reduced space SQP-type and other related optimization algorithms.

Specifically, the variables are partitioned into dependent and independent sets x = [ x_dep' x_indep' ]' and Jacobians of the constraints c(x) at the point x are:

 del(c,x) = Gc' = [ del(c(con_decomp))   ] = [ GcD' ] = [ GcDD'  GcDI' ] = [ C  N ]
                  [ del(c(con_undecomp)) ]   [ GcU' ]   [ GcUD'  GcUI' ]   [ E  F ]

   where:
     C <: R^(r x r) is nonsingular
     N <: R^(r x (n-r))
     E <: R^((m-r) x r)
     F <: R^((m-r) x (n-r))

This partitions the general equality constraints c(x) into two sets; decomposed c(con_decomp) and undecomposed c(con_undecomp). It is therefore expected that sub-vectors and subspaces from space_x().sub_space(var_dep), space_x().sub_space(var_indep), space_c().sub_space(con_decomp) and space_c().sub_space(con_undecomp) can all be accessed. Other sub-vectors and sub-spaces may not be available (but the algorithm should not need access to other sub-spaces).

Free access to solves with the basis C is not given however and instead this interface computes, for the current point x, the direct sensitivity matrice D = -inv(C)*N, the auxiliary matrices Uz = F + E * D and GcU = [ GcUD; GcUI ] = [ E'; F' ], and the Newton step py = -inv(C)*c(con_decomp). In general, linear solves with the transpose with C are not possible and therefore are not avalible. A number of very specialized applications can only provide this information but this is all that is needed by many numerical optimization (and related) algorithms.

Client Usage:

The dimension of the basis matrix C is returned by r(). The ranges for the dependent and independent varaibles are returned by var_dep() and var_indep(). The ranges for the decomposed and undecomposed equality constraints are con_decomp() and con_undecomp(). Note that con_undecomp() will return an invalid range if there are no undecomposed equalities.

Note that the matrix objects returned from factory_GcU(), factory_D() and factory_Uz() can not be expected to be usable until they are passed to the calculation routines or have been intialized in some other way.

Subclass Developer's Notes:

The default implementation of this interface assumes that there are no undecomposed equality constraints (i.e. this->con_decomp().size() == this->m()).

ToDo: Finish Documentation!

Definition at line 111 of file NLPInterfacePack_NLPDirect.hpp.

Member Typedef Documentation

Definition at line 117 of file NLPInterfacePack_NLPDirect.hpp.

Definition at line 120 of file NLPInterfacePack_NLPDirect.hpp.

Definition at line 123 of file NLPInterfacePack_NLPDirect.hpp.

Member Function Documentation

void NLPInterfacePack::NLPDirect::set_factories ( const mat_sym_fcty_ptr_t factory_transDtD,
const mat_sym_nonsing_fcty_ptr_t factory_S 
)

Initialize the factory objects for the special matrices for D'*D and S = I + D'*D.

Postconditions:

Definition at line 53 of file NLPInterfacePack_NLPDirect.cpp.

size_type NLPInterfacePack::NLPDirect::r ( ) const
virtual

Returns the number of decomposed equality constraints (r <= m).

Preconditions:

The default implementation returns this->con_decomp().size(). This implementation will work for all implementations.

Definition at line 62 of file NLPInterfacePack_NLPDirect.cpp.

Range1D NLPInterfacePack::NLPDirect::var_dep ( ) const
virtual

Return the range of dependent (i.e. basic) variables.

Preconditions:

The default implementation returns Range1D(1,this->m()).

Reimplemented in NLPInterfacePack::ExampleNLPDirect, and NLPInterfacePack::NLPDirectThyraModelEvaluator.

Definition at line 67 of file NLPInterfacePack_NLPDirect.cpp.

Range1D NLPInterfacePack::NLPDirect::var_indep ( ) const
virtual

Return the range of independent (i.e. nonbasic) variables.

Preconditions:

The default implementation returns Range1D(this->m()+1,this->n()).

Reimplemented in NLPInterfacePack::ExampleNLPDirect, and NLPInterfacePack::NLPDirectThyraModelEvaluator.

Definition at line 71 of file NLPInterfacePack_NLPDirect.cpp.

Range1D NLPInterfacePack::NLPDirect::con_decomp ( ) const
virtual

Return the range of decomposed equality constraints.

Preconditions:

The default implementation returns Range1D(1,this->m()).

Definition at line 75 of file NLPInterfacePack_NLPDirect.cpp.

Range1D NLPInterfacePack::NLPDirect::con_undecomp ( ) const
virtual

Return the range of undecomposed equality constraints.

Preconditions:

The default implementation returns Range1D::Invalid.

Definition at line 80 of file NLPInterfacePack_NLPDirect.cpp.

const NLPDirect::mat_fcty_ptr_t NLPInterfacePack::NLPDirect::factory_GcU ( ) const
virtual

Return a matrix factory object for creating GcU.

Preconditions:

The default implementation is to return return.get() == NULL. This is the proper implementation when m() == r(). When m() > r() then the subclass must override this method to return a valid matrix factory object. Moreover, the returned matrix object from this->factory_GcU()->create()->get_sub_view(rng,Range1D()) must be non-null for rng == this->var_dep() or rng == this->var_indep(). This gives access to the matrices E' and F' as shown above.

Definition at line 86 of file NLPInterfacePack_NLPDirect.cpp.

virtual const mat_fcty_ptr_t NLPInterfacePack::NLPDirect::factory_D ( ) const
pure virtual

Return a matrix factory object for D = -inv(C)*N {abstract}.

Preconditions:

Implemented in NLPInterfacePack::ExampleNLPDirect, and NLPInterfacePack::NLPDirectThyraModelEvaluator.

const NLPDirect::mat_fcty_ptr_t NLPInterfacePack::NLPDirect::factory_Uz ( ) const
virtual

Return a matrix factory object for Uz = F + E * D.

Preconditions:

The default implementation is to return return.get() == NULL. This is the correct implementation when m() == r(). However, when m() > r() this method must be overridden to return a non-null matrix factory object.

Definition at line 92 of file NLPInterfacePack_NLPDirect.cpp.

const NLPDirect::mat_fcty_ptr_t NLPInterfacePack::NLPDirect::factory_GcUD ( ) const
virtual

Return a matrix factory object for a mutable matrix compatible with GcU(var_dep).

This matrix factory object is designed to create mutable matrix objects compatible with GcU(var_dep). For example, a matrix object Uy created by this matrix factory can be used to compute Uy = Gc(var_dep,con_undecomp)' - Gc(var_indep,con_undecomp)'*D' (this is needed by a orthogonal range/null decomposition.

The default implementation is to return return.get() == NULL. This is the correct implementation when m() == r(). However, when m() > r() this method must be overridden to return a non-null matrix factory object.

Definition at line 98 of file NLPInterfacePack_NLPDirect.cpp.

const NLPDirect::mat_sym_fcty_ptr_t NLPInterfacePack::NLPDirect::factory_transDtD ( ) const
virtual

Returns a matrix factory for the result of J = D'*D

The resulting matrix is symmetric but is assumed to be singular.

Definition at line 104 of file NLPInterfacePack_NLPDirect.cpp.

const NLPDirect::mat_sym_nonsing_fcty_ptr_t NLPInterfacePack::NLPDirect::factory_S ( ) const
virtual

Returns a matrix factory for the result of S = I + D'*D

The resulting matrix is symmetric and is guarrenteed to be nonsingular

Reimplemented in NLPInterfacePack::NLPDirectThyraModelEvaluator.

Definition at line 110 of file NLPInterfacePack_NLPDirect.cpp.

virtual void NLPInterfacePack::NLPDirect::calc_point ( const Vector x,
value_type *  f,
VectorMutable c,
bool  recalc_c,
VectorMutable Gf,
VectorMutable py,
VectorMutable rGf,
MatrixOp *  GcU,
MatrixOp *  D,
MatrixOp *  Uz 
) const
pure virtual

Compute all of the needed quanities for direct sensitivities.

Parameters
x[in] (dim == n()) Current value of unkowns. This vector should have been created by this->space_x()->create_member().
f[out] Value of f(x). If f == NULL then this quantity is not computed.
c[in/out] (dim == m()) Value of the equality constraints c(x). If c == NULL then this quantity is not computed. If c != NULL and recalc_c == true then this quantity is recomputed. If c != NULL and recalc_c == false then this quantity is not recomputed and is used in the computation of py if requested (i.e. py != NULL). If c != NULL this this vector should have been created by this->space_c()->create_member().
recalc_c[in] If true then c will be recomputed at x. If false then c will not be recomputed but will be used as stated above.
Gf[out] (dim == n()) Gradient of f(x). If Gf == NULL then this quantity is not computed. If Gf!=NULL this this vector should have been created by this->space_x()->create_member().
py[out] (dim == r()) py = -inv(C)*c(con_decomp). If py == NULL then this quantity is not computed. If recalc_c == false on input then the input c != NULL argument may be used in the computation of py. If py!=NULL this this vector should have been created by this->space_x()->sub_space(this->var_dep())->create_member().
rGf[out] (dim == n()-r()) rGf = Gf(var_indep()) + D'*Gf(var_dep()), which is the reduced gradient of the objective function projected into the manifold of the decomposed equality constraints. If rGf==NULL, this vector is not computed. If rGf!=NULL then this vector should have been created by this->space_x(this->var_indep())->create_member().
GcU[out] (dim = n x (m()-r())) Auxiliary jacobian matrix del(c(con_undecomp),x). If m() == r() then GcU should be set to NULL on input. If GcU == NULL then this quantitiy is not computed. If !=NULL this this matrix should have been created by this->factory_GcU()->create().
D[out] (dim = r() x (n()-r())) D = -inv(C)*N, which is the direct sensitivity of the constraints to the independent variables. If D == NULL then this quantity is not computed. If !=NULL this this matrix should have been created by this->factory_D()->create().
Uz[out] (dim = (m()-r()) x (n()-r())) Uz = F + E * D, which is the an auxiliary sensitivity matrix. If m() == r() then Uz should be set to NULL on input. If Uz==NULL then this quantity is not computed. If !=NULL this this matrix should have been created by this->factory_Uz()->create().

Preconditions:

Implemented in NLPInterfacePack::ExampleNLPDirect, and NLPInterfacePack::NLPDirectThyraModelEvaluator.

virtual void NLPInterfacePack::NLPDirect::calc_semi_newton_step ( const Vector x,
VectorMutable c,
bool  recalc_c,
VectorMutable py 
) const
pure virtual

Calculate an approximate newton step given the Jacobian computed for the last call to calc_point().

The idea behind this method is that with some applications it may be much cheaper to compute an approximate Newton step for the constraints given information computed during the last call to calc_point(). It is assumed that this approximate solution py will still be a descent direction for c(x). Some subclasses may have to perform an equal amount of work as calc_point(...) to perform this calculation but those are the breaks.

Parameters
x[in] (dim == n()) current value of unkowns.
c[out] (dim == m()) Value of the constraints c(x) If c == NULL then this quantity is not computed. If c != NULL and recalc_c == true on input then this quantity is not recomputed and is used in the computation of py if requested (i.e. py!=NULL).
recalc_c
py[out] (size == r() on output) Approximate value of -inv(C)*c Note that py == NULL is not allowed here.

Preconditions:

Implemented in NLPInterfacePack::ExampleNLPDirect, and NLPInterfacePack::NLPDirectThyraModelEvaluator.

void NLPInterfacePack::NLPDirect::initialize ( bool  test_setup)
virtual

Initialize the NLP for its first use.

This function implementation should be called by subclass implementations in order to reset counts for f(x), c(x), h(x) and Gf(x) evaluations. This implementation calls this->NLPObjGrad::initialize()

Postconditions:

Reimplemented from NLPInterfacePack::NLP.

Reimplemented in NLPInterfacePack::ExampleNLPDirect, and NLPInterfacePack::NLPDirectThyraModelEvaluator.

Definition at line 115 of file NLPInterfacePack_NLPDirect.cpp.

Member Data Documentation

mat_sym_fcty_ptr_t NLPInterfacePack::NLPDirect::factory_transDtD_
private

Definition at line 382 of file NLPInterfacePack_NLPDirect.hpp.

mat_sym_nonsing_fcty_ptr_t NLPInterfacePack::NLPDirect::factory_S_
private

Definition at line 383 of file NLPInterfacePack_NLPDirect.hpp.


The documentation for this class was generated from the following files: