madness::QuasiNewton Class Reference

Optimization via quasi-Newton (BFGS or SR1 update) More...

#include <solvers.h>

Inheritance diagram for madness::QuasiNewton:

Collaboration diagram for madness::QuasiNewton:

Public Member Functions
	QuasiNewton (const std::shared_ptr< OptimizationTargetInterface > &tar, int maxiter=20, double tol=1e-6, double value_precision=1e-12, double gradient_precision=1e-12)
void	set_update (const std::string &method)
	Choose update method (currently only "BFGS" or "SR1") More...
void	set_test (const bool &test_level)
	Choose update method (currently only "BFGS" or "SR1") More...
bool	optimize (Tensor< double > &x)
	Runs the optimizer. More...
bool	converged () const
	After running the optimizer returns true if converged. More...
double	value () const
	Value of objective function. More...
void	reset_hessian ()
	Resets Hessian to default guess. More...
void	set_hessian (const Tensor< double > &matrix)
	Sets Hessian to given matrix. More...
double	gradient_norm () const
	Value of gradient norm. More...
virtual	~QuasiNewton ()
Public Member Functions inherited from madness::OptimizerInterface
virtual	~OptimizerInterface ()

Detailed Description

Optimization via quasi-Newton (BFGS or SR1 update)

This is presently not a low memory algorithm ... we really need one!

Constructor & Destructor Documentation

QuasiNewton::QuasiNewton	(	const std::shared_ptr< OptimizationTargetInterface > &	tar,
		int	maxiter = 20,
		double	tol = 1e-6,
		double	value_precision = 1e-12,
		double	gradient_precision = 1e-12
	)

References madness::OptimizationTargetInterface::provides_gradient().

virtual madness::QuasiNewton::~QuasiNewton ( )

inlinevirtual

Member Function Documentation

bool QuasiNewton::converged ( ) const

virtual

After running the optimizer returns true if converged.

Returns

True if converged

Implements madness::OptimizerInterface.

Referenced by optimize().

double QuasiNewton::gradient_norm ( ) const

virtual

Value of gradient norm.

Returns

Norm of gradient of objective function

Implements madness::OptimizerInterface.

bool QuasiNewton::optimize ( Tensor< double > &  x )

virtual

Runs the optimizer.

Returns

True if converged

Implements madness::OptimizerInterface.

References converged(), madness::g, madness::print(), madness::OptimizationTargetInterface::test_gradient(), and madness::OptimizationTargetInterface::value_and_gradient().

Referenced by main().

void madness::QuasiNewton::reset_hessian ( )

inline

Resets Hessian to default guess.

Referenced by main().

void madness::QuasiNewton::set_hessian ( const Tensor< double > &  matrix )

inline

Sets Hessian to given matrix.

References madness::copy().

Referenced by main().

void QuasiNewton::set_test

(

const bool &

test_level

)

Choose update method (currently only "BFGS" or "SR1")

Referenced by main().

void QuasiNewton::set_update

(

const std::string &

method

)

Choose update method (currently only "BFGS" or "SR1")

Referenced by main().

double QuasiNewton::value ( ) const

virtual

Value of objective function.

Returns

Value of objective function

Implements madness::OptimizerInterface.

---

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

• solvers.h
• solvers.cc