#include <ls_minimizer2.h>

Classes
struct	observation
struct	observation_nn
	Pre-defined structure for users that prefer function pointers to class heritage. More...

Public Types
enum	{ MAX_B_SIZE = 4 }
typedef double	flt_t
typedef void(*	callback_function )(flt_t state, void *user_data)
typedef void(*	func_nn_ptr )(const flt_t state, const flt_t data, int data_size, flt_t b, flt_t J, void **user_data)
	Function pointer type used by observation_nn.
typedef bool(*	sample_consensus_func )(flt_t computed_state, observation obs, int nobs, void *user_data)

Public Member Functions
	ls_minimizer2 (int state_size=0)
	~ls_minimizer2 ()
void	set_state_size (int size)
	Defines the optimization space dimentionality, i.e. the number of optimized parameters.
void	set_scales (flt_t *scales)
void	desactivate_automated_scaling (void)
void	set_verbose_level (int vl)
void	set_user_data (int slot_index, void *ptr)
void	reset_observations (void)
	call that before adding observations for a new optimization.
void	erase_observations (int a, int b=-1)
	Remove some observations. a=0, b=-1 is equivalent to reset_observation.
void	add_observation (observation *obs, bool to_delete, bool to_array_delete)
void	add_observation_2data_1measure (func_nn_ptr f, const flt_t data[2], const flt_t goal)
void	add_observation_3data_1measure (func_nn_ptr f, const flt_t data[3], const flt_t goal)
void	add_observation_2data_2measures (func_nn_ptr f, const flt_t data[2], const flt_t goal[2])
void	add_observation_3data_2measures (func_nn_ptr f, const flt_t data[3], const flt_t goal[2])
void	set_new_iteration_callback (callback_function callback)
	this callback is called at the end of every iteration
void	set_state_change_callback (callback_function callback)
	this callback is called each time the state vector changes.
void	set_default_c (flt_t c)
void	set_last_observation_c (flt_t c)
void	set_last_observation_c_max_c_min (flt_t c_max, flt_t c_min)
	For robust estimation using Julien' method (default = +inf for both):
void	set_last_observation_weight (flt_t weight)
	Set observation weight (default = 1):
void	set_last_observation_confidence (flt_t confidence)
	Set observation confidence (default = 1). Only used for PROSAC and cat tail.
int	minimize_using_steepest_descent_from (flt_t *initial_state)
int	minimize_using_levenberg_marquardt_from (flt_t *initial_state)
	Levenberg-Marquardt minimization.
void	lm_set_max_iterations (int it)
void	lm_set_max_failures_in_a_row (int f)
	if f iterations do not decrease the function, stop.
void	lm_set_tol_cos (flt_t t)
	stop condition. Very restrictive: 0.999 less restrictive: 0.9
void	lm_set_initial_lambda (flt_t l)
bool	minimize_using_gauss_newton_from (flt_t *initial_state)
int	minimize_using_dogleg_from (flt_t *initial_state)
	Dogleg (not convincing).
int	minimize_using_cattail_from (flt_t *initial_state)
void	ct_set_max_iterations (int it)
void	set_line_search_parameters (flt_t lambda0, flt_t k_rough, flt_t k_fine)
flt_t	minimize_using_prosac (sample_consensus_func f, int nb_samples, int min_number_of_inliers, int max_number_of_iterations)
flt_t	minimize_using_julien_method_from (const flt_t *state, int nb_steps, int nb_iterations_per_step)
void	check_jacobians_around (flt_t *state, flt_t state_step)
void	set_last_observation_as_outlier (void)
void	set_ground_truth (flt_t *state)
void	compare_outliers_with_ground_truth (void)
void	compare_state_with_ground_truth (void)
void	reserve (int max_obs)
int	count_measures ()

Public Attributes
flt_t *	state
	state vector
bool	use_user_scaling
bool	use_automated_scaling
int	lm_max_iterations
int	lm_max_failures_in_a_row
flt_t	lm_initial_lambda
flt_t	lm_tol_cos
int	verbose_level

Detailed Description

Non-linear Minimizer, modified API

Author: Vincent Lepetit, Julien Pilet

Definition at line 39 of file ls_minimizer2.h.

Member Typedef Documentation

typedef void(* ls_minimizer2::callback_function)(flt_t *state, void **user_data)

Definition at line 44 of file ls_minimizer2.h.

typedef double ls_minimizer2::flt_t

Definition at line 43 of file ls_minimizer2.h.

typedef void(* ls_minimizer2::func_nn_ptr)(const flt_t *state, const flt_t *data, int data_size, flt_t *b, flt_t *J, void **user_data)

Function pointer type used by observation_nn.

Definition at line 83 of file ls_minimizer2.h.

typedef bool(* ls_minimizer2::sample_consensus_func)(flt_t *computed_state, observation **obs, int nobs, void **user_data)

Definition at line 206 of file ls_minimizer2.h.

Member Enumeration Documentation

anonymous enum

Enumerator:

MAX_B_SIZE

Definition at line 49 of file ls_minimizer2.h.

Constructor & Destructor Documentation

ls_minimizer2::ls_minimizer2 ( int state_size = 0 )

Definition at line 33 of file ls_minimizer2.cpp.

ls_minimizer2::~ls_minimizer2 ( )

Definition at line 104 of file ls_minimizer2.cpp.

Member Function Documentation

void ls_minimizer2::add_observation	(	observation *	obs,
		bool	to_delete,
		bool	to_array_delete
	)

Definition at line 262 of file ls_minimizer2.cpp.

References ls_minimizer2::observation::array_delete_me, ls_minimizer2::observation::delete_me, ls_minimizer2::observation::sqrt_weight, and ls_minimizer2::observation::weight.

void ls_minimizer2::add_observation_2data_1measure	(	func_nn_ptr	f,
		const flt_t	data[2],
		const flt_t	goal
	)

Definition at line 1132 of file ls_minimizer2.cpp.

References ls_minimizer2::observation::set_default_values().

void ls_minimizer2::add_observation_2data_2measures	(	func_nn_ptr	f,
		const flt_t	data[2],
		const flt_t	goal[2]
	)

Definition at line 1146 of file ls_minimizer2.cpp.

References ls_minimizer2::observation::set_default_values().

void ls_minimizer2::add_observation_3data_1measure	(	func_nn_ptr	f,
		const flt_t	data[3],
		const flt_t	goal
	)

Definition at line 1139 of file ls_minimizer2.cpp.

References ls_minimizer2::observation::set_default_values().

void ls_minimizer2::add_observation_3data_2measures	(	func_nn_ptr	f,
		const flt_t	data[3],
		const flt_t	goal[2]
	)

Definition at line 1153 of file ls_minimizer2.cpp.

References ls_minimizer2::observation::set_default_values().

void ls_minimizer2::check_jacobians_around	(	flt_t *	state,
		flt_t	state_step
	)

Checking derivatives: compares finite difference jacobian and analytical jacobian computed by the user provided functions.

Definition at line 1091 of file ls_minimizer2.cpp.

References ls_minimizer2::observation::eval_func(), and ls_minimizer2::observation::get_nb_measures().

void ls_minimizer2::compare_outliers_with_ground_truth ( void )

Definition at line 351 of file ls_minimizer2.cpp.

References ls_minimizer2::observation::eval_func(), ls_minimizer2::observation::ground_truth_outlier, ls_minimizer2::observation::residual(), and ls_minimizer2::observation::squared_c.

void ls_minimizer2::compare_state_with_ground_truth ( void )

Definition at line 339 of file ls_minimizer2.cpp.

int ls_minimizer2::count_measures ( )

Definition at line 557 of file ls_minimizer2.cpp.

References msg.

void ls_minimizer2::ct_set_max_iterations ( int it )

inline

Definition at line 202 of file ls_minimizer2.h.

void ls_minimizer2::desactivate_automated_scaling ( void )

inline

Definition at line 122 of file ls_minimizer2.h.

References use_automated_scaling.

void ls_minimizer2::erase_observations	(	int	a,
		int	b = `-1`
	)

Remove some observations. a=0, b=-1 is equivalent to reset_observation.

Definition at line 242 of file ls_minimizer2.cpp.

void ls_minimizer2::lm_set_initial_lambda ( flt_t l )

Definition at line 206 of file ls_minimizer2.cpp.

void ls_minimizer2::lm_set_max_failures_in_a_row ( int f )

if f iterations do not decrease the function, stop.

Definition at line 196 of file ls_minimizer2.cpp.

void ls_minimizer2::lm_set_max_iterations ( int it )

Definition at line 191 of file ls_minimizer2.cpp.

void ls_minimizer2::lm_set_tol_cos ( flt_t t )

stop condition. Very restrictive: 0.999 less restrictive: 0.9

Definition at line 201 of file ls_minimizer2.cpp.

int ls_minimizer2::minimize_using_cattail_from ( flt_t * initial_state )

Cat Tail (experimental) a mix between gauss-newton and line search.

Definition at line 898 of file ls_minimizer2.cpp.

References confidence_cmp(), and msg.

int ls_minimizer2::minimize_using_dogleg_from ( flt_t * initial_state )

Dogleg (not convincing).

TODO looks wrong..

Definition at line 718 of file ls_minimizer2.cpp.

References msg, and solve_deg2().

bool ls_minimizer2::minimize_using_gauss_newton_from ( flt_t * initial_state )

ls_minimizer2::flt_t ls_minimizer2::minimize_using_julien_method_from	(	const flt_t *	state,
		int	nb_steps,
		int	nb_iterations_per_step
	)

Definition at line 1065 of file ls_minimizer2.cpp.

References msg.

int ls_minimizer2::minimize_using_levenberg_marquardt_from ( flt_t * initial_state )

Levenberg-Marquardt minimization.

Returns: an error code <0 if something went wrong. 2: unable to improve result after N iterations. 3: termination criterion reached. 4: iterations limit exceeded.

Julien new_state actually contains the old state

Definition at line 579 of file ls_minimizer2.cpp.

References msg.

ls_minimizer2::flt_t ls_minimizer2::minimize_using_prosac	(	sample_consensus_func	f,
		int	nb_samples,
		int	min_number_of_inliers,
		int	max_number_of_iterations
	)

TODO <Julien> I modified this. It may be wrong.

Definition at line 1008 of file ls_minimizer2.cpp.

References confidence_cmp(), and mymin().

int ls_minimizer2::minimize_using_steepest_descent_from ( flt_t * initial_state )

void ls_minimizer2::reserve ( int max_obs )

inline

Definition at line 224 of file ls_minimizer2.h.

void ls_minimizer2::reset_observations ( void )

call that before adding observations for a new optimization.

Definition at line 238 of file ls_minimizer2.cpp.

void ls_minimizer2::set_default_c ( flt_t c )

For robust estimation (default = +inf) residual = max( ||b-f(d,state)||^2, c^2 ) This value will be applied to next added observations

Definition at line 257 of file ls_minimizer2.cpp.

void ls_minimizer2::set_ground_truth ( flt_t * state )

Definition at line 219 of file ls_minimizer2.cpp.

void ls_minimizer2::set_last_observation_as_outlier ( void )

Definition at line 305 of file ls_minimizer2.cpp.

References ls_minimizer2::observation::outlier.

void ls_minimizer2::set_last_observation_c ( flt_t c )

For robust estimation (default = +inf): change the last added observation robust estimator value

Definition at line 274 of file ls_minimizer2.cpp.

References ls_minimizer2::observation::squared_c.

void ls_minimizer2::set_last_observation_c_max_c_min	(	flt_t	c_max,
		flt_t	c_min
	)

For robust estimation using Julien' method (default = +inf for both):

Definition at line 282 of file ls_minimizer2.cpp.

References ls_minimizer2::observation::c_max, and ls_minimizer2::observation::c_min.

void ls_minimizer2::set_last_observation_confidence ( flt_t confidence )

Set observation confidence (default = 1). Only used for PROSAC and cat tail.

Definition at line 298 of file ls_minimizer2.cpp.

References ls_minimizer2::observation::confidence.

void ls_minimizer2::set_last_observation_weight ( flt_t weight )

Set observation weight (default = 1):

Definition at line 290 of file ls_minimizer2.cpp.

References ls_minimizer2::observation::sqrt_weight, and ls_minimizer2::observation::weight.

void ls_minimizer2::set_line_search_parameters	(	flt_t	lambda0,
		flt_t	k_rough,
		flt_t	k_fine
	)

Definition at line 211 of file ls_minimizer2.cpp.

void ls_minimizer2::set_new_iteration_callback ( callback_function callback )

this callback is called at the end of every iteration

Definition at line 228 of file ls_minimizer2.cpp.

void ls_minimizer2::set_scales ( flt_t * scales )

Scale applied to each optimized parameter (each dimension of the optimization space). Not used by default, but an automated method is used.

Definition at line 156 of file ls_minimizer2.cpp.

void ls_minimizer2::set_state_change_callback ( callback_function callback )

this callback is called each time the state vector changes.

Definition at line 233 of file ls_minimizer2.cpp.

void ls_minimizer2::set_state_size ( int size )

Defines the optimization space dimentionality, i.e. the number of optimized parameters.

Definition at line 50 of file ls_minimizer2.cpp.

void ls_minimizer2::set_user_data	(	int	slot_index,
		void *	ptr
	)

user arbitrary pointers. slot_index should be in [0,9] this pointer array is passed to the callback functions

Definition at line 149 of file ls_minimizer2.cpp.

void ls_minimizer2::set_verbose_level ( int vl )

0 = nothing 1 = messages before and after minimization 2 = message at each iteration. 3 = debug

Definition at line 186 of file ls_minimizer2.cpp.

Member Data Documentation

flt_t ls_minimizer2::lm_initial_lambda

Definition at line 284 of file ls_minimizer2.h.

int ls_minimizer2::lm_max_failures_in_a_row

Definition at line 283 of file ls_minimizer2.h.

int ls_minimizer2::lm_max_iterations

Definition at line 282 of file ls_minimizer2.h.

flt_t ls_minimizer2::lm_tol_cos

Definition at line 285 of file ls_minimizer2.h.

flt_t* ls_minimizer2::state

state vector

Definition at line 176 of file ls_minimizer2.h.

bool ls_minimizer2::use_automated_scaling

Definition at line 274 of file ls_minimizer2.h.

Referenced by desactivate_automated_scaling().

bool ls_minimizer2::use_user_scaling

Definition at line 274 of file ls_minimizer2.h.

int ls_minimizer2::verbose_level

Definition at line 308 of file ls_minimizer2.h.

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

/home/adrien/Téléchargements/bazar/bazar-1.3.1/starter/optimization/ls_minimizer2.h
/home/adrien/Téléchargements/bazar/bazar-1.3.1/starter/optimization/ls_minimizer2.cpp

Classes

Public Types

Public Member Functions

Public Attributes

Detailed Description

Member Typedef Documentation

Member Enumeration Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation