Base class for techniques of approximating second-order derivatives within NLPsolvers. More...
#include <nlp_derivative_approximation.hpp>
Public Member Functions | |
| virtual returnValue | apply (BlockMatrix &B, const BlockMatrix &x, const BlockMatrix &y)=0 |
| virtual NLPderivativeApproximation * | clone () 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) | |
| NLPderivativeApproximation & | operator= (const NLPderivativeApproximation &rhs) |
| virtual | ~NLPderivativeApproximation () |
Protected Member Functions | |
| virtual returnValue | setupLogging () |
| virtual returnValue | setupOptions () |
Protected Attributes | |
| double | hessianScaling |
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.
Definition at line 61 of file nlp_derivative_approximation.hpp.
Constructor & Destructor Documentation
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.
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:
-
B matrix to be updated x direction x y residuum
Implemented in BFGSupdate, ExactHessian, GaussNewtonApproximationWithBFGS, ConstantHessian, and GaussNewtonApproximation.
| virtual NLPderivativeApproximation* NLPderivativeApproximation::clone | ( | ) | const [pure virtual] |
Implemented in BFGSupdate, GaussNewtonApproximationWithBFGS, ExactHessian, GaussNewtonApproximation, and ConstantHessian.
| double NLPderivativeApproximation::getHessianScaling | ( | ) | const [inline] |
Reimplemented in ExactHessian.
| virtual returnValue NLPderivativeApproximation::initHessian | ( | BlockMatrix & | B, |
| uint | N, | ||
| const OCPiterate & | iter | ||
| ) | [pure virtual] |
- Parameters:
-
B matrix to be initialised N number of intervals iter current iterate
Implemented in BFGSupdate, GaussNewtonApproximationWithBFGS, ExactHessian, GaussNewtonApproximation, and ConstantHessian.
| virtual returnValue NLPderivativeApproximation::initScaling | ( | BlockMatrix & | B, |
| const BlockMatrix & | x, | ||
| const BlockMatrix & | y | ||
| ) | [pure virtual] |
- Parameters:
-
B matrix to be updated x direction x y residuum
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 | ( | ) | [protected, virtual] |
Definition at line 104 of file nlp_derivative_approximation.cpp.
| returnValue NLPderivativeApproximation::setupOptions | ( | ) | [protected, virtual] |
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: