vnl_nonlinear_minimizer is a base class for nonlinear optimization. More...

#include <vnl_nonlinear_minimizer.h>

Inheritance diagram for vnl_nonlinear_minimizer:

[legend]

Public Types
enum	ReturnCodes { ERROR_FAILURE =-1, ERROR_DODGY_INPUT = 0, CONVERGED_FTOL = 1, CONVERGED_XTOL = 2, CONVERGED_XFTOL = 3, CONVERGED_GTOL = 4, FAILED_TOO_MANY_ITERATIONS = 5, TOO_MANY_ITERATIONS = FAILED_TOO_MANY_ITERATIONS, FAILED_FTOL_TOO_SMALL = 6, FAILED_XTOL_TOO_SMALL = 7, FAILED_GTOL_TOO_SMALL = 8, FAILED_USER_REQUEST = 9 }
	Some generic return codes that apply to all minimizers. More...

Public Member Functions
	vnl_nonlinear_minimizer ()
	Default ctor sets verbosity etc. More...

virtual	~vnl_nonlinear_minimizer ()

void	set_f_tolerance (double v)
	Set the convergence tolerance on F (sum of squared residuals). More...

double	get_f_tolerance () const

void	set_x_tolerance (double v)
	Set the convergence tolerance on X. More...

double	get_x_tolerance () const

void	set_g_tolerance (double v)
	Set the convergence tolerance on Grad(F)' * F. More...

double	get_g_tolerance () const

void	set_max_function_evals (int v)
	Set the termination maximum number of iterations. More...

int	get_max_function_evals () const

void	set_epsilon_function (double v)
	Set the step length for FD Jacobian. More...

double	get_epsilon_function () const

void	set_trace (bool on)
	Turn on per-iteration printouts. More...

bool	get_trace () const

void	set_verbose (bool verb)
	Set verbose flag. More...

bool	get_verbose () const

void	set_check_derivatives (int cd)
	Set check_derivatives flag. Negative values may mean fewer checks. More...

int	get_check_derivatives () const

double	get_start_error () const
	Return the error of the function when it was evaluated at the start point of the last minimization. More...

double	get_end_error () const
	Return the best error that was achieved by the last minimization, corresponding to the returned x. More...

int	get_num_evaluations () const
	Return the total number of times the function was evaluated by the last minimization. More...

int	get_num_iterations () const
	Return the number of {iterations} in the last minimization. More...

bool	obj_value_reduced ()
	Whether the error reduced in the last minimization. More...

virtual vnl_matrix< double > const &	get_covariance ()
	Return the covariance of the estimate at the end. More...

virtual std::string	is_a () const
	Return the name of the class. More...

virtual bool	is_class (std::string const &s) const
	Return true if the name of the class matches the argument. More...

ReturnCodes	get_failure_code () const
	Return the failure code of the last minimization. More...

Protected Member Functions
void	reset ()

void	report_eval (double f)
	Called by derived classes after each function evaluation. More...

virtual bool	report_iter ()
	Called by derived classes after each iteration. More...

Protected Attributes
double	xtol
	Termination tolerance on X (solution vector) More...

long	maxfev
	Termination maximum number of iterations. More...

double	ftol
	Termination tolerance on F (sum of squared residuals) More...

double	gtol
	Termination tolerance on Grad(F)' * F = 0. More...

double	epsfcn
	Step length for FD Jacobian. More...

unsigned	num_iterations_

long	num_evaluations_

double	start_error_

double	end_error_

bool	trace

bool	verbose_

int	check_derivatives_

ReturnCodes	failure_code_

Detailed Description

vnl_nonlinear_minimizer is a base class for nonlinear optimization.

It defines a few common abilities such as get_num_evaluations. Known derived classes are:

Definition at line 31 of file vnl_nonlinear_minimizer.h.

Member Enumeration Documentation

◆ ReturnCodes

enum vnl_nonlinear_minimizer::ReturnCodes

Some generic return codes that apply to all minimizers.

Enumerator
ERROR_FAILURE
ERROR_DODGY_INPUT
CONVERGED_FTOL
CONVERGED_XTOL
CONVERGED_XFTOL
CONVERGED_GTOL
FAILED_TOO_MANY_ITERATIONS
TOO_MANY_ITERATIONS
FAILED_FTOL_TOO_SMALL
FAILED_XTOL_TOO_SMALL
FAILED_GTOL_TOO_SMALL
FAILED_USER_REQUEST

Definition at line 102 of file vnl_nonlinear_minimizer.h.

Constructor & Destructor Documentation

◆ vnl_nonlinear_minimizer()

vnl_nonlinear_minimizer::vnl_nonlinear_minimizer ( )

Default ctor sets verbosity etc.

Definition at line 11 of file vnl_nonlinear_minimizer.cxx.

◆ ~vnl_nonlinear_minimizer()

vnl_nonlinear_minimizer::~vnl_nonlinear_minimizer ( )

virtualdefault

Member Function Documentation

◆ get_check_derivatives()

int vnl_nonlinear_minimizer::get_check_derivatives ( ) const

inline

Definition at line 82 of file vnl_nonlinear_minimizer.h.

◆ get_covariance()

vnl_matrix< double > const & vnl_nonlinear_minimizer::get_covariance ( )

virtual

Return the covariance of the estimate at the end.

Definition at line 30 of file vnl_nonlinear_minimizer.cxx.

◆ get_end_error()

double vnl_nonlinear_minimizer::get_end_error ( ) const

inline

Return the best error that was achieved by the last minimization, corresponding to the returned x.

Definition at line 92 of file vnl_nonlinear_minimizer.h.

◆ get_epsilon_function()

double vnl_nonlinear_minimizer::get_epsilon_function ( ) const

inline

Definition at line 70 of file vnl_nonlinear_minimizer.h.

◆ get_f_tolerance()

double vnl_nonlinear_minimizer::get_f_tolerance ( ) const

inline

Definition at line 46 of file vnl_nonlinear_minimizer.h.

◆ get_failure_code()

ReturnCodes vnl_nonlinear_minimizer::get_failure_code ( ) const

inline

Return the failure code of the last minimization.

Definition at line 132 of file vnl_nonlinear_minimizer.h.

◆ get_g_tolerance()

double vnl_nonlinear_minimizer::get_g_tolerance ( ) const

inline

Definition at line 60 of file vnl_nonlinear_minimizer.h.

◆ get_max_function_evals()

int vnl_nonlinear_minimizer::get_max_function_evals ( ) const

inline

Definition at line 64 of file vnl_nonlinear_minimizer.h.

◆ get_num_evaluations()

int vnl_nonlinear_minimizer::get_num_evaluations ( ) const

inline

Return the total number of times the function was evaluated by the last minimization.

Definition at line 95 of file vnl_nonlinear_minimizer.h.

◆ get_num_iterations()

int vnl_nonlinear_minimizer::get_num_iterations ( ) const

inline

Return the number of {iterations} in the last minimization.

Each iteration may have comprised several function evaluations.

Definition at line 99 of file vnl_nonlinear_minimizer.h.

◆ get_start_error()

double vnl_nonlinear_minimizer::get_start_error ( ) const

inline

Return the error of the function when it was evaluated at the start point of the last minimization.

For minimizers driven by a vnl_least_squares_function (Levenberg-Marquardt) this is usually the RMS error. For those driven by a vnl_cost_function (CG, LBFGS, Amoeba) it is simply the value of the vnl_cost_function at the start (usually the sum of squared residuals).

Definition at line 89 of file vnl_nonlinear_minimizer.h.

◆ get_trace()

bool vnl_nonlinear_minimizer::get_trace ( ) const

inline

Definition at line 74 of file vnl_nonlinear_minimizer.h.

◆ get_verbose()

bool vnl_nonlinear_minimizer::get_verbose ( ) const

inline

Definition at line 78 of file vnl_nonlinear_minimizer.h.

◆ get_x_tolerance()

double vnl_nonlinear_minimizer::get_x_tolerance ( ) const

inline

Definition at line 56 of file vnl_nonlinear_minimizer.h.

◆ is_a()

std::string vnl_nonlinear_minimizer::is_a ( ) const

virtual

Return the name of the class.

Used by polymorphic IO

Definition at line 70 of file vnl_nonlinear_minimizer.cxx.

◆ is_class()

bool vnl_nonlinear_minimizer::is_class ( std::string const & s ) const

virtual

Return true if the name of the class matches the argument.

Used by polymorphic IO

Definition at line 78 of file vnl_nonlinear_minimizer.cxx.

◆ obj_value_reduced()

bool vnl_nonlinear_minimizer::obj_value_reduced ( )

inline

Whether the error reduced in the last minimization.

Definition at line 118 of file vnl_nonlinear_minimizer.h.

◆ report_eval()

void vnl_nonlinear_minimizer::report_eval ( double f )

protected

Called by derived classes after each function evaluation.

Definition at line 45 of file vnl_nonlinear_minimizer.cxx.

◆ report_iter()

bool vnl_nonlinear_minimizer::report_iter ( )

protectedvirtual

Called by derived classes after each iteration.

When true is returned, minimizer should stop with code FAILED_USER_REQUEST. Derived classes can redefine this function to make the optimizer stop when a condition is satisfied.

Definition at line 58 of file vnl_nonlinear_minimizer.cxx.

◆ reset()

void vnl_nonlinear_minimizer::reset ( )

protected

Definition at line 36 of file vnl_nonlinear_minimizer.cxx.

◆ set_check_derivatives()

void vnl_nonlinear_minimizer::set_check_derivatives ( int cd )

inline

Set check_derivatives flag. Negative values may mean fewer checks.

Definition at line 81 of file vnl_nonlinear_minimizer.h.

◆ set_epsilon_function()

void vnl_nonlinear_minimizer::set_epsilon_function ( double v )

inline

Set the step length for FD Jacobian.

Be aware that set_x_tolerance will reset this to xtol * 0.001. The default is 1e-11.

Definition at line 69 of file vnl_nonlinear_minimizer.h.

◆ set_f_tolerance()

void vnl_nonlinear_minimizer::set_f_tolerance ( double v )

inline

Set the convergence tolerance on F (sum of squared residuals).

When the differences in successive RMS errors is less than this, the routine terminates. So this is effectively the desired precision of your minimization. Setting it too low wastes time, too high might cause early convergence. The default of 1e-9 is on the safe side, but if speed is an issue, you can try raising it.

Definition at line 45 of file vnl_nonlinear_minimizer.h.

◆ set_g_tolerance()

void vnl_nonlinear_minimizer::set_g_tolerance ( double v )

inline

Set the convergence tolerance on Grad(F)' * F.

Definition at line 59 of file vnl_nonlinear_minimizer.h.

◆ set_max_function_evals()

void vnl_nonlinear_minimizer::set_max_function_evals ( int v )

inline

Set the termination maximum number of iterations.

Definition at line 63 of file vnl_nonlinear_minimizer.h.

◆ set_trace()

void vnl_nonlinear_minimizer::set_trace ( bool on )

inline

Turn on per-iteration printouts.

Definition at line 73 of file vnl_nonlinear_minimizer.h.

◆ set_verbose()

void vnl_nonlinear_minimizer::set_verbose ( bool verb )

inline

Set verbose flag.

Definition at line 77 of file vnl_nonlinear_minimizer.h.

◆ set_x_tolerance()

void vnl_nonlinear_minimizer::set_x_tolerance ( double v )

inline

Set the convergence tolerance on X.

When the length of the steps taken in X are about this long, the routine terminates. The default is 1e-8, which should work for many problems, but if you can get away with 1e-4, say, minimizations will be much quicker.

Definition at line 52 of file vnl_nonlinear_minimizer.h.

Member Data Documentation

◆ check_derivatives_

int vnl_nonlinear_minimizer::check_derivatives_

protected

Definition at line 153 of file vnl_nonlinear_minimizer.h.

◆ end_error_

double vnl_nonlinear_minimizer::end_error_

protected

Definition at line 147 of file vnl_nonlinear_minimizer.h.

◆ epsfcn

double vnl_nonlinear_minimizer::epsfcn

protected

Step length for FD Jacobian.

Definition at line 141 of file vnl_nonlinear_minimizer.h.

◆ failure_code_

ReturnCodes vnl_nonlinear_minimizer::failure_code_

protected

Definition at line 154 of file vnl_nonlinear_minimizer.h.

◆ ftol

double vnl_nonlinear_minimizer::ftol

protected

Termination tolerance on F (sum of squared residuals)

Definition at line 139 of file vnl_nonlinear_minimizer.h.

◆ gtol

double vnl_nonlinear_minimizer::gtol

protected

Termination tolerance on Grad(F)' * F = 0.

Definition at line 140 of file vnl_nonlinear_minimizer.h.

◆ maxfev

long vnl_nonlinear_minimizer::maxfev

protected

Termination maximum number of iterations.

Definition at line 138 of file vnl_nonlinear_minimizer.h.

◆ num_evaluations_

long vnl_nonlinear_minimizer::num_evaluations_

protected

Definition at line 145 of file vnl_nonlinear_minimizer.h.

◆ num_iterations_

unsigned vnl_nonlinear_minimizer::num_iterations_

protected

Definition at line 144 of file vnl_nonlinear_minimizer.h.

◆ start_error_

double vnl_nonlinear_minimizer::start_error_

protected

Definition at line 146 of file vnl_nonlinear_minimizer.h.

◆ trace

bool vnl_nonlinear_minimizer::trace

protected

Definition at line 149 of file vnl_nonlinear_minimizer.h.

◆ verbose_

bool vnl_nonlinear_minimizer::verbose_

protected

Definition at line 152 of file vnl_nonlinear_minimizer.h.

◆ xtol

double vnl_nonlinear_minimizer::xtol

protected

Termination tolerance on X (solution vector)

Definition at line 137 of file vnl_nonlinear_minimizer.h.

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

core/vnl/vnl_nonlinear_minimizer.h
core/vnl/vnl_nonlinear_minimizer.cxx

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

Member Enumeration Documentation

◆ ReturnCodes

Constructor & Destructor Documentation

◆ vnl_nonlinear_minimizer()

◆ ~vnl_nonlinear_minimizer()

Member Function Documentation

◆ get_check_derivatives()

◆ get_covariance()

◆ get_end_error()

◆ get_epsilon_function()

◆ get_f_tolerance()

◆ get_failure_code()

◆ get_g_tolerance()

◆ get_max_function_evals()

◆ get_num_evaluations()

◆ get_num_iterations()

◆ get_start_error()

◆ get_trace()

◆ get_verbose()

◆ get_x_tolerance()

◆ is_a()

◆ is_class()

◆ obj_value_reduced()

◆ report_eval()

◆ report_iter()

◆ reset()

◆ set_check_derivatives()

◆ set_epsilon_function()

◆ set_f_tolerance()

◆ set_g_tolerance()

◆ set_max_function_evals()

◆ set_trace()

◆ set_verbose()

◆ set_x_tolerance()

Member Data Documentation

◆ check_derivatives_

◆ end_error_

◆ epsfcn

◆ failure_code_

◆ ftol

◆ gtol

◆ maxfev

◆ num_evaluations_

◆ num_iterations_

◆ start_error_

◆ trace

◆ verbose_

◆ xtol