Public Member Functions | Protected Member Functions | Protected Attributes | List of all members

Base class for techniques of approximating second-order derivatives within NLPsolvers. More...

#include <nlp_derivative_approximation.hpp>

Inheritance diagram for NLPderivativeApproximation:
Inheritance graph
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Public Member Functions

virtual returnValue apply (BlockMatrix &B, const BlockMatrix &x, const BlockMatrix &y)=0
 
virtual NLPderivativeApproximationclone () const =0
 
double getHessianScaling () const
 
virtual returnValue initHessian (BlockMatrix &B, uint N, const OCPiterate &iter)=0
 
virtual returnValue initScaling (BlockMatrix &B, const BlockMatrix &x, const BlockMatrix &y)=0
 
 NLPderivativeApproximation ()
 
 NLPderivativeApproximation (UserInteraction *_userInteraction)
 
 NLPderivativeApproximation (const NLPderivativeApproximation &rhs)
 
NLPderivativeApproximationoperator= (const NLPderivativeApproximation &rhs)
 
virtual ~NLPderivativeApproximation ()
 
- Public Member Functions inherited from AlgorithmicBase
int addLogRecord (LogRecord &_record)
 
returnValue addOption (OptionsName name, int value)
 
returnValue addOption (OptionsName name, double value)
 
returnValue addOption (uint idx, OptionsName name, int value)
 
returnValue addOption (uint idx, OptionsName name, double value)
 
returnValue addOptionsList ()
 
 AlgorithmicBase ()
 
 AlgorithmicBase (UserInteraction *_userInteraction)
 
 AlgorithmicBase (const AlgorithmicBase &rhs)
 
returnValue get (OptionsName name, int &value) const
 
returnValue get (OptionsName name, double &value) const
 
returnValue get (OptionsName name, std::string &value) const
 
returnValue get (uint idx, OptionsName name, int &value) const
 
returnValue get (uint idx, OptionsName name, double &value) const
 
returnValue getAll (LogName _name, MatrixVariablesGrid &values) const
 
returnValue getFirst (LogName _name, DMatrix &firstValue) const
 
returnValue getFirst (LogName _name, VariablesGrid &firstValue) const
 
returnValue getLast (LogName _name, DMatrix &lastValue) const
 
returnValue getLast (LogName _name, VariablesGrid &lastValue) const
 
Options getOptions (uint idx) const
 
BooleanType haveOptionsChanged () const
 
BooleanType haveOptionsChanged (uint idx) const
 
AlgorithmicBaseoperator= (const AlgorithmicBase &rhs)
 
returnValue plot (PlotFrequency _frequency=PLOT_IN_ANY_CASE)
 
returnValue printLogRecord (std::ostream &_stream, int idx, LogPrintMode _mode=PRINT_ITEM_BY_ITEM) const
 
returnValue replot (PlotFrequency _frequency=PLOT_IN_ANY_CASE)
 
returnValue set (OptionsName name, int value)
 
returnValue set (OptionsName name, double value)
 
returnValue set (OptionsName name, const std::string &value)
 
returnValue set (uint idx, OptionsName name, int value)
 
returnValue set (uint idx, OptionsName name, double value)
 
returnValue setAll (LogName _name, const MatrixVariablesGrid &values)
 
returnValue setLast (LogName _name, int lastValue, double time=-INFTY)
 
returnValue setLast (LogName _name, double lastValue, double time=-INFTY)
 
returnValue setLast (LogName _name, const DVector &lastValue, double time=-INFTY)
 
returnValue setLast (LogName _name, const DMatrix &lastValue, double time=-INFTY)
 
returnValue setLast (LogName _name, const VariablesGrid &lastValue, double time=-INFTY)
 
returnValue setOptions (const Options &arg)
 
returnValue setOptions (uint idx, const Options &arg)
 
virtual ~AlgorithmicBase ()
 

Protected Member Functions

virtual returnValue setupLogging ()
 
virtual returnValue setupOptions ()
 

Protected Attributes

double hessianScaling
 
- Protected Attributes inherited from AlgorithmicBase
int outputLoggingIdx
 
BooleanType useModuleStandalone
 
UserInteractionuserInteraction
 

Detailed Description

Base class for techniques of approximating second-order derivatives within NLPsolvers.

The class NLPderivativeApproximation serves as a base class for different techniques of approximating second-order derivative information within iterative NLPsolvers.

Author
Boris Houska, Hans Joachim Ferreau

Definition at line 61 of file nlp_derivative_approximation.hpp.

Constructor & Destructor Documentation

BEGIN_NAMESPACE_ACADO NLPderivativeApproximation::NLPderivativeApproximation ( )

Default constructor.

Definition at line 45 of file nlp_derivative_approximation.cpp.

NLPderivativeApproximation::NLPderivativeApproximation ( UserInteraction _userInteraction)

Definition at line 54 of file nlp_derivative_approximation.cpp.

NLPderivativeApproximation::NLPderivativeApproximation ( const NLPderivativeApproximation rhs)

Copy constructor (deep copy).

Definition at line 67 of file nlp_derivative_approximation.cpp.

NLPderivativeApproximation::~NLPderivativeApproximation ( )
virtual

Destructor.

Definition at line 73 of file nlp_derivative_approximation.cpp.

Member Function Documentation

virtual returnValue NLPderivativeApproximation::apply ( BlockMatrix B,
const BlockMatrix x,
const BlockMatrix y 
)
pure virtual
Parameters
Bmatrix to be updated
xdirection x
yresiduum

Implemented in BFGSupdate, ExactHessian, GaussNewtonApproximationWithBFGS, GaussNewtonApproximation, and ConstantHessian.

virtual NLPderivativeApproximation* NLPderivativeApproximation::clone ( ) const
pure virtual
double NLPderivativeApproximation::getHessianScaling ( ) const
inline
virtual returnValue NLPderivativeApproximation::initHessian ( BlockMatrix B,
uint  N,
const OCPiterate iter 
)
pure virtual
Parameters
Bmatrix to be initialised
Nnumber of intervals
itercurrent iterate

Implemented in BFGSupdate, GaussNewtonApproximationWithBFGS, ExactHessian, GaussNewtonApproximation, and ConstantHessian.

virtual returnValue NLPderivativeApproximation::initScaling ( BlockMatrix B,
const BlockMatrix x,
const BlockMatrix y 
)
pure virtual
Parameters
Bmatrix to be updated
xdirection x
yresiduum

Implemented in BFGSupdate, GaussNewtonApproximationWithBFGS, ExactHessian, GaussNewtonApproximation, and ConstantHessian.

NLPderivativeApproximation & NLPderivativeApproximation::operator= ( const NLPderivativeApproximation rhs)

Assignment operator (deep copy).

Definition at line 78 of file nlp_derivative_approximation.cpp.

returnValue NLPderivativeApproximation::setupLogging ( )
protectedvirtual

Definition at line 104 of file nlp_derivative_approximation.cpp.

returnValue NLPderivativeApproximation::setupOptions ( )
protectedvirtual

Definition at line 98 of file nlp_derivative_approximation.cpp.

Member Data Documentation

double NLPderivativeApproximation::hessianScaling
protected

Definition at line 123 of file nlp_derivative_approximation.hpp.


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


acado
Author(s): Milan Vukov, Rien Quirynen
autogenerated on Mon Jun 10 2019 12:35:25