Base class for techniques of approximating second-order derivatives within NLPsolvers.
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virtual returnValue | apply (BlockMatrix &B, const BlockMatrix &x, const BlockMatrix &y)=0 |
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virtual NLPderivativeApproximation * | clone () const =0 |
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double | getHessianScaling () const |
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virtual returnValue | initHessian (BlockMatrix &B, uint N, const OCPiterate &iter)=0 |
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virtual returnValue | initScaling (BlockMatrix &B, const BlockMatrix &x, const BlockMatrix &y)=0 |
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| NLPderivativeApproximation () |
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| NLPderivativeApproximation (UserInteraction *_userInteraction) |
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| NLPderivativeApproximation (const NLPderivativeApproximation &rhs) |
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NLPderivativeApproximation & | operator= (const NLPderivativeApproximation &rhs) |
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virtual | ~NLPderivativeApproximation () |
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int | addLogRecord (LogRecord &_record) |
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returnValue | addOption (OptionsName name, int value) |
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returnValue | addOption (OptionsName name, double value) |
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returnValue | addOption (uint idx, OptionsName name, int value) |
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returnValue | addOption (uint idx, OptionsName name, double value) |
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returnValue | addOptionsList () |
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| AlgorithmicBase () |
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| AlgorithmicBase (UserInteraction *_userInteraction) |
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| AlgorithmicBase (const AlgorithmicBase &rhs) |
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returnValue | get (OptionsName name, int &value) const |
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returnValue | get (OptionsName name, double &value) const |
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returnValue | get (OptionsName name, std::string &value) const |
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returnValue | get (uint idx, OptionsName name, int &value) const |
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returnValue | get (uint idx, OptionsName name, double &value) const |
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returnValue | getAll (LogName _name, MatrixVariablesGrid &values) const |
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returnValue | getFirst (LogName _name, DMatrix &firstValue) const |
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returnValue | getFirst (LogName _name, VariablesGrid &firstValue) const |
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returnValue | getLast (LogName _name, DMatrix &lastValue) const |
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returnValue | getLast (LogName _name, VariablesGrid &lastValue) const |
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Options | getOptions (uint idx) const |
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BooleanType | haveOptionsChanged () const |
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BooleanType | haveOptionsChanged (uint idx) const |
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AlgorithmicBase & | operator= (const AlgorithmicBase &rhs) |
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returnValue | plot (PlotFrequency _frequency=PLOT_IN_ANY_CASE) |
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returnValue | printLogRecord (std::ostream &_stream, int idx, LogPrintMode _mode=PRINT_ITEM_BY_ITEM) const |
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returnValue | replot (PlotFrequency _frequency=PLOT_IN_ANY_CASE) |
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returnValue | set (OptionsName name, int value) |
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returnValue | set (OptionsName name, double value) |
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returnValue | set (OptionsName name, const std::string &value) |
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returnValue | set (uint idx, OptionsName name, int value) |
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returnValue | set (uint idx, OptionsName name, double value) |
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returnValue | setAll (LogName _name, const MatrixVariablesGrid &values) |
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returnValue | setLast (LogName _name, int lastValue, double time=-INFTY) |
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returnValue | setLast (LogName _name, double lastValue, double time=-INFTY) |
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returnValue | setLast (LogName _name, const DVector &lastValue, double time=-INFTY) |
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returnValue | setLast (LogName _name, const DMatrix &lastValue, double time=-INFTY) |
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returnValue | setLast (LogName _name, const VariablesGrid &lastValue, double time=-INFTY) |
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returnValue | setOptions (const Options &arg) |
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returnValue | setOptions (uint idx, const Options &arg) |
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virtual | ~AlgorithmicBase () |
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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.