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// ***********************************************************************
//
// Moocho: Multi-functional Object-Oriented arCHitecture for Optimization
// Copyright (2003) Sandia Corporation
//
// Under terms of Contract DE-AC04-94AL85000, there is a non-exclusive
// license for use of this work by or on behalf of the U.S. Government.
//
// This library is free software; you can redistribute it and/or modify
// it under the terms of the GNU Lesser General Public License as
// published by the Free Software Foundation; either version 2.1 of the
// License, or (at your option) any later version.
//
// This library is distributed in the hope that it will be useful, but
// WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
// Lesser General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License along with this library; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307
// USA
// Questions? Contact Roscoe A. Bartlett (rabartl@sandia.gov)
//
// ***********************************************************************
// @HEADER
#ifndef NLPIP_NLP_THYRA_MODEL_EVALUATOR_BASE_HPP
#define NLPIP_NLP_THYRA_MODEL_EVALUATOR_BASE_HPP
#include <vector>
#include "NLPInterfacePack_NLPFirstOrder.hpp"
#include "AbstractLinAlgPack_VectorSpace.hpp"
#include "Thyra_ModelEvaluator.hpp"
#include "Teuchos_TestForException.hpp"
#include "Teuchos_StandardMemberCompositionMacros.hpp"
namespace AbstractLinAlgPack { class VectorSpaceThyra; }
namespace NLPInterfacePack {
/** \brief Implements the base %NLP interface using a
* <tt>Thyra::ModelEvaluator</tt> object.
*
* The nonlinear program is mapped as follows:
\verbatim
min f(x)
s.t. c(x) = 0
xL <= x <= xu
where:
x = [ model.x ]
[ model.p(p_idx) ]
f(x) = model.g(g_idx)
c(x) = model.f()
\endverbatim
* where <tt>p_idx > 0</tt> and <tt>g_idx > 0</tt> are some indexes that
* specificy the indepenent variables and the objective function.
*
* In addition, the client can also override the bounds on <tt>model.x</tt> and
* <tt>model.p(p_idx)</tt> defined in the object <tt>model</tt>.
*
* The current implementation of this class does not allow the use of any of
* the auxiliary functions <tt>model.g()</tt> as undecomposed equality
* constraints or extra general inequality constraints. This type of
* functionality can be added when it is needed (just ask for it).
*
* ToDo: Finish documentation!
*/
class NLPThyraModelEvaluatorBase : virtual public NLPObjGrad {
public:
/** \brief Set if a trace of the model evaluations is shown or not. */
STANDARD_MEMBER_COMPOSITION_MEMBERS( bool, showModelEvaluatorTrace );
/** @name Overridden public members from NLP */
//@{
/** \brief . */
void initialize(bool test_setup);
/** \brief . */
bool is_initialized() const;
/** \brief . */
vec_space_ptr_t space_x() const;
/** \brief . */
vec_space_ptr_t space_c() const;
/** \brief . */
size_type num_bounded_x() const;
/** \brief . */
void force_xinit_in_bounds(bool force_xinit_in_bounds);
/** \brief . */
bool force_xinit_in_bounds() const;
/** \brief . */
const Vector& xinit() const;
/** \brief . */
const Vector& xl() const;
/** \brief . */
const Vector& xu() const;
/** \brief . */
value_type max_var_bounds_viol() const;
/** \brief . */
void set_f(value_type* f);
/** \brief . */
void set_c(VectorMutable* c);
/** \brief . */
void unset_quantities();
/** \brief . */
void scale_f( value_type scale_f );
/** \brief . */
value_type scale_f() const;
/** \brief . */
void report_final_solution(
const Vector& x
,const Vector* lambda
,const Vector* nu
,bool optimal
);
//@}
/** @name Overridden public members from NLPObjGrad */
//@{
/** \brief . */
void set_Gf(VectorMutable* Gf);
//@}
protected:
/** @name Overridden protected members from NLP */
//@{
/** \brief . */
void imp_calc_f(
const Vector& x, bool newx
,const ZeroOrderInfo& zero_order_info) const;
/** \brief . */
void imp_calc_c(
const Vector& x, bool newx
,const ZeroOrderInfo& zero_order_info) const;
//@}
/** @name Overridden protected members from NLPObjGrad */
//@{
/** \brief . */
void imp_calc_Gf(
const Vector& x, bool newx
,const ObjGradInfo& obj_grad_info) const;
//@}
protected:
/** @name Protected functions to be used by subclasses */
//@{
/** Initialize to uninitialized */
NLPThyraModelEvaluatorBase();
/** \brief Initialize given a <tt>Thyra::ModelEvaluator</tt> and
* a description of how to interpret it.
*
* @param model [in] NonlinearProblem that defines all of the functions and variables.
* @param p_idx [in] Index of the subset of parameter vectors to use as the independent
* variables. If <tt>p_idx < 0</tt>, then no extra parameters are added.
* @param g_idx [in] Index of the subset of auxiliary response functions to use as
* the objective function. Note, only the first element <tt>model.g(g_idx)(1)</tt>
* will be used as the objective function value.
* @param model_xL [in] Pointer to upper bounds for the state variables <tt>model.x</tt>. If NULL
* then the default supplied in <tt>model->get_x_lower_bounds()</tt> will be used.
* @param model_xU [in] Pointer to upper bounds for the state variables <tt>x</tt>. If NULL
* then the default supplied in <tt>model->get_x_upper_bounds()</tt> will be used.
* @param model_x0 [in] Pointer to initial guess for the state variables <tt>x</tt>. If NULL
* the the default supplied in <tt>model->get_x_init()</tt> will be used.
*
* ToDo: Finish documentation!
*
* Todo: Add arguments for auxiliary inequalites and equalities
*/
void initializeBase(
const Teuchos::RCP<Thyra::ModelEvaluator<value_type> > &model
,const int p_idx
,const int g_idx
);
/** \brief Update the initial guess and bounds . */
void updateInitialGuessAndBounds() const;
/** \brief . */
void assert_is_initialized() const;
/** \brief . */
void copy_from_model_x( const Thyra::VectorBase<value_type>* model_x, VectorMutable* x_D ) const;
/** \brief . */
void copy_from_model_p( const Thyra::VectorBase<value_type> *model_p, VectorMutable* x_I ) const;
/** \brief . */
void set_x(
const Vector &x
,Thyra::ModelEvaluatorBase::InArgs<value_type> *model_inArgs_inout
) const;
/** \brief . */
void preprocessBaseInOutArgs(
const Vector &x
,bool newx
,const ZeroOrderInfo *zero_order_info
,const ObjGradInfo *obj_grad_info
,const NLPFirstOrder::FirstOrderInfo *first_order_info
,Thyra::ModelEvaluatorBase::InArgs<value_type> *model_inArgs_inout
,Thyra::ModelEvaluatorBase::OutArgs<value_type> *model_outArgs_inout
,MatrixOp* *Gc_out
,VectorMutable* *Gf_out
,value_type* *f_out
,VectorMutable* *c_out
) const;
/** \brief . */
void postprocessBaseOutArgs(
Thyra::ModelEvaluatorBase::OutArgs<value_type> *model_outArgs_inout
,VectorMutable *Gf
,value_type *f
,VectorMutable *c
) const;
//@}
//private: // ToDo: Make these private and refactor the other classes ...
// /////////////////////////////////////////
// Private types
typedef Teuchos::RCP<const AbstractLinAlgPack::VectorSpaceThyra> VectorSpaceThyra_ptr_t;
// /////////////////////////////////////////
// Private data members
bool initialized_; // flag for if initialized has been called.
value_type obj_scale_; // default = 1.0;
bool has_bounds_; // True if has bounds
bool force_xinit_in_bounds_; // default = true.
index_type num_bounded_x_;
Teuchos::RCP<Thyra::ModelEvaluator<value_type> >
model_;
int p_idx_;
int g_idx_;
bool DfDp_supports_op_;
bool DfDp_supports_mv_;
VectorSpace::space_ptr_t space_x_; // Space for the variables
VectorSpaceThyra_ptr_t space_c_; // Space for the constraints
NLPFirstOrder::mat_fcty_ptr_t factory_Gc_; // Factory for Gc
NLPFirstOrder::basis_sys_ptr_t basis_sys_; // The basis system
mutable bool x_guess_bounds_updated_;
VectorSpace::vec_mut_ptr_t xinit_; // Initial guess.
VectorSpace::vec_mut_ptr_t xl_; // lower bounds.
VectorSpace::vec_mut_ptr_t xu_; // upper bounds.
Teuchos::RCP<Thyra::VectorBase<value_type> > model_g_;
mutable bool model_g_updated_;
mutable bool model_Dg_updated_;
mutable bool f_updated_;
mutable bool c_updated_;
mutable bool Gf_updated_;
mutable bool Gc_updated_;
// /////////////////////////////////////////
// Private member functions
/** \brief . */
void evalModel(
const Vector &x
,bool newx
,const ZeroOrderInfo *zero_order_info // != NULL if only zero-order info
,const ObjGradInfo *obj_grad_info // != NULL if obj-grad and below info
) const;
}; // end class NLPThyraModelEvaluatorBase
} // end namespace NLPInterfacePack
#endif // NLPIP_NLP_THYRA_MODEL_EVALUATOR_BASE_HPP
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