25 #ifndef UQ_BASE_OPTIMIZER_H 
   26 #define UQ_BASE_OPTIMIZER_H 
   28 #include <queso/ScopedPtr.h> 
   29 #include <queso/OptimizerOptions.h> 
   45 class OptimizerMonitor;
 
  131 #endif // UQ_BASE_OPTIMIZER_H 
BaseOptimizer()
Default constructor. 
 
void setMaxIterations(unsigned int maxIterations)
Sets the maximum number of iterations to be used by the optimizer. 
 
virtual double getFdfstepSize() const 
Gets the step to use in gradient-based solvers. 
 
void setTolerance(double tolerance)
Sets the tolerance the optimizer will use to test for an extremum. 
 
virtual double getLineTolerance() const 
Gets the tolerance to use for line minimisation. 
 
double m_finiteDifferenceStepSize
 
virtual std::string getSolverType() const 
Gets the algorithm to use for minimisation. 
 
ScopedPtr< OptimizerOptions >::Type m_optionsObj
 
unsigned int m_maxIterations
 
A base class for handling optimisation of scalar functions. 
 
virtual void setLineTolerance(double lineTolerance)
Sets the tolerance to use for line minimisation. 
 
virtual void setSolverType(std::string solverType)
Sets the algorithm to use for minimisation. 
 
This class provides options for a Optimizer. 
 
void setFiniteDifferenceStepSize(double h)
Sets the step to use in the finite difference derivative. 
 
virtual double getFstepSize() const 
Gets the step size to use in gradient-free solvers. 
 
double getTolerance() const 
Returns the tolerance used to test for an extremum in the optimizer. 
 
virtual void setFdfstepSize(double fdfstepSize)
Sets the step to use in gradient-based solvers. 
 
virtual void setFstepSize(double fstepSize)
Sets the step size to use in gradient-free solvers. 
 
virtual void minimize(OptimizerMonitor *monitor)=0
Minimize the objective function, starting at m_initialPoint. 
 
Object to monitor convergence of optimizers. 
 
virtual ~BaseOptimizer()
Destructor. 
 
double getFiniteDifferenceStepSize() const 
Returns the step size used in the finite difference formula. 
 
unsigned int getMaxIterations() const 
Returns the maximum number of iterations the optimizer will do.