OPTPP::NLP Class Reference

#include <NLP.h>

List of all members.

Public Member Functions

 NLP ()
 NLP (NLPBase *base)
void setX (const int i, const real &x)
 Set the ith component of the vector x.
void setX (const NEWMAT::ColumnVector &x)
 Set the current point.
void setF (const real &fx)
 Set the function value.
void setIsExpensive (const int e)
void setFcnAccrcy (const int i, const real &accrcy)
 Set the ith component of the function accuracy.
void setFcnAccrcy (const NEWMAT::ColumnVector &accrcy)
 Set the function accuracy.
int getDim () const
int getFevals () const
int getIsExpensive () const
real getF () const
NEWMAT::ColumnVector getFcnAccrcy () const
NEWMAT::ColumnVector getXc () const
real getFcnTime () const
int getNumOfCons () const
int getNumOfNLCons () const
bool hasConstraints ()
void printConstraints ()
 Print value of constraints to the screen.
void setDebug ()
 Set debug parameter = true.
bool getDebug () const
void reset ()
 Reset parameter values.
void initFcn ()
 Initialize selected function.
real evalF ()
 Evaluate the function.
real evalF (const NEWMAT::ColumnVector &x)
 Evaluate the function at x.
NEWMAT::ColumnVector evalG ()
 Evaluate the gradient.
NEWMAT::ColumnVector evalG (const NEWMAT::ColumnVector &x)
 Evaluate the gradient at x.
NEWMAT::SymmetricMatrix evalH ()
 Evaluate Hessian.
NEWMAT::SymmetricMatrix evalH (NEWMAT::ColumnVector &x)
 Evaluate Hessian at x.
void eval ()
 Evaluate the function, gradient, and Hessian.
NEWMAT::ColumnVector evalCF (const NEWMAT::ColumnVector &x)
 Evaluate the constraints at x.
NEWMAT::Matrix evalCG (const NEWMAT::ColumnVector &x)
 Evaluate the constraint gradient at x.
NEWMAT::SymmetricMatrix evalCH (NEWMAT::ColumnVector &x)
 Evaluate the constraint Hessian at x.
OptppArray< NEWMAT::SymmetricMatrix > evalCH (NEWMAT::ColumnVector &x, int darg)
 Evaluate the constraint Hessian at x.
void evalC (const NEWMAT::ColumnVector &x)
void printState (char *)
 Print status of the nonlinear function to the screen.
void fPrintState (ostream *, char *)
 Print status of the nonlinear function to file.

Private Attributes

SmartPtr< NLPBaseptr_
 Pointer to an NLPBase object.


Detailed Description

NLP is a handle class for NLPBase. This class is an interface to NLP0-2 for evaluating nonlinear functions.

Author:
P.J. Williams, Sandia National Laboratories, pwillia@sandia.gov
Date:
Last modified 03/2007


Constructor & Destructor Documentation

OPTPP::NLP::NLP (  ) 

Default Constructor

OPTPP::NLP::NLP ( NLPBase base  ) 

Parameters:
base pointer to an NLPBase object


Member Function Documentation

void OPTPP::NLP::eval (  ) 

Evaluate the function, gradient, and Hessian.

void OPTPP::NLP::evalC ( const NEWMAT::ColumnVector &  x  ) 

NEWMAT::ColumnVector OPTPP::NLP::evalCF ( const NEWMAT::ColumnVector &  x  ) 

Evaluate the constraints at x.

NEWMAT::Matrix OPTPP::NLP::evalCG ( const NEWMAT::ColumnVector &  x  ) 

Evaluate the constraint gradient at x.

OptppArray<NEWMAT::SymmetricMatrix> OPTPP::NLP::evalCH ( NEWMAT::ColumnVector &  x,
int  darg 
)

Evaluate the constraint Hessian at x.

NEWMAT::SymmetricMatrix OPTPP::NLP::evalCH ( NEWMAT::ColumnVector &  x  ) 

Evaluate the constraint Hessian at x.

real OPTPP::NLP::evalF ( const NEWMAT::ColumnVector &  x  ) 

Evaluate the function at x.

real OPTPP::NLP::evalF (  ) 

Evaluate the function.

NEWMAT::ColumnVector OPTPP::NLP::evalG ( const NEWMAT::ColumnVector &  x  ) 

Evaluate the gradient at x.

ColumnVector OPTPP::NLP::evalG (  ) 

Evaluate the gradient.

NEWMAT::SymmetricMatrix OPTPP::NLP::evalH ( NEWMAT::ColumnVector &  x  ) 

Evaluate Hessian at x.

SymmetricMatrix OPTPP::NLP::evalH (  ) 

Evaluate Hessian.

void OPTPP::NLP::fPrintState ( ostream *  ,
char *   
)

Print status of the nonlinear function to file.

bool OPTPP::NLP::getDebug (  )  const

Returns:
= true, debug output statements printed

= false, debug output statements are not printed

int OPTPP::NLP::getDim (  )  const

Returns:
Problem Dimension

real OPTPP::NLP::getF (  )  const

Returns:
The current value of function

ColumnVector OPTPP::NLP::getFcnAccrcy (  )  const

Returns:
User-specified function accuracy

real OPTPP::NLP::getFcnTime (  )  const

Returns:
CPU time used

int OPTPP::NLP::getFevals (  )  const

Returns:
Number of function evaluations taken

int OPTPP::NLP::getIsExpensive (  )  const

Returns:
1, Function evaluation is expensive

= 0, Function evaluation is inexpensive

int OPTPP::NLP::getNumOfCons (  )  const

Returns:
Total number of constraints

int OPTPP::NLP::getNumOfNLCons (  )  const

Returns:
Total number of nonlinear constraints

ColumnVector OPTPP::NLP::getXc (  )  const

Returns:
The current value of x

bool OPTPP::NLP::hasConstraints (  ) 

Returns:
= true, Problem is constrained

= false, Problem is unconstrained

void OPTPP::NLP::initFcn (  ) 

Initialize selected function.

void OPTPP::NLP::printConstraints (  ) 

Print value of constraints to the screen.

void OPTPP::NLP::printState ( char *   ) 

Print status of the nonlinear function to the screen.

void OPTPP::NLP::reset (  ) 

Reset parameter values.

void OPTPP::NLP::setDebug (  ) 

Set debug parameter = true.

void OPTPP::NLP::setF ( const real fx  ) 

Set the function value.

void OPTPP::NLP::setFcnAccrcy ( const NEWMAT::ColumnVector &  accrcy  ) 

Set the function accuracy.

void OPTPP::NLP::setFcnAccrcy ( const int  i,
const real accrcy 
)

Set the ith component of the function accuracy.

void OPTPP::NLP::setIsExpensive ( const int  e  ) 

e = 1, simple backtracking linesearch is used in opt. algorithm

e = 0, More-Thuente linesearch is used in opt. algorithm

void OPTPP::NLP::setX ( const NEWMAT::ColumnVector &  x  ) 

Set the current point.

void OPTPP::NLP::setX ( const int  i,
const real x 
)

Set the ith component of the vector x.


Member Data Documentation

SmartPtr<NLPBase> OPTPP::NLP::ptr_ [private]

Pointer to an NLPBase object.


The documentation for this class was generated from the following files:
Bug Reports    OPT++ Developers    Copyright Information    GNU Lesser General Public License
Documentation, generated by , last revised August 30, 2006.