Brent 1D minimizer (deprecated). More...
#include <vnl_brent.h>
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_brent (vnl_cost_function *functor) | |
~vnl_brent () | |
double | minimize (double ax) |
Find a minimum of f(x) near to ax. | |
double | minimize_given_bounds (double ax, double bx, double cx, double tol, double *xmin) |
Find the minimum value of f(x) within a<= x <= c. | |
double | minimize_given_bounds_and_1st_f (double ax, double bx, double fb, double cx, double tol, double *xmin) |
Save time over minimize_given_bounds() if you know f(b). | |
void | bracket_minimum (double *ax, double *bx, double *cx, double *fa, double *fb, double *fc) |
Given distinct points ax, and bx, find a bracket for the minimum. | |
void | bracket_minimum (double *ax, double *bx, double *cx) |
Given distinct points ax, and bx, find a bracket for the minimum. | |
double | f_at_last_minimum () const |
Function evaluation at value returned by minimize(x). | |
double | minimize_golden (double ax, double bx, double cx, double fa, double fb, double fc) |
Find the minimum x of f(x) within a<= x <= c using pure golden section. | |
double | minimize_given_bounds (double ax, double bx, double cx) |
Find the minimum value of f(x) within a<= x <= c. | |
double | minimize_given_bounds_and_one_f (double ax, double bx, double cx, double fb) |
Find the minimum value of f(x) within a<= x <= c. | |
double | minimize_given_bounds_and_all_f (double ax, double bx, double cx, double fa, double fb, double fc) |
Find the minimum value of f(x) within a<= x <= c. | |
void | set_f_tolerance (double v) |
Set the convergence tolerance on F (sum of squared residuals). | |
double | get_f_tolerance () const |
void | set_x_tolerance (double v) |
Set the convergence tolerance on X. | |
double | get_x_tolerance () const |
void | set_g_tolerance (double v) |
Set the convergence tolerance on Grad(F)' * F. | |
double | get_g_tolerance () const |
void | set_max_function_evals (int v) |
Set the termination maximum number of iterations. | |
int | get_max_function_evals () const |
void | set_epsilon_function (double v) |
Set the step length for FD Jacobian. | |
double | get_epsilon_function () const |
void | set_trace (bool on) |
Turn on per-iteration printouts. | |
bool | get_trace () const |
void | set_verbose (bool verb) |
Set verbose flag. | |
bool | get_verbose () const |
void | set_check_derivatives (int cd) |
Set check_derivatives flag. Negative values may mean fewer checks. | |
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. | |
double | get_end_error () const |
Return the best error that was achieved by the last minimization, corresponding to the returned x. | |
int | get_num_evaluations () const |
Return the total number of times the function was evaluated by the last minimization. | |
int | get_num_iterations () const |
Return the number of {iterations} in the last minimization. | |
bool | obj_value_reduced () |
Whether the error reduced in the last minimization. | |
virtual vnl_matrix< double > const & | get_covariance () |
Return the covariance of the estimate at the end. | |
virtual vcl_string | is_a () const |
Return the name of the class. | |
virtual bool | is_class (vcl_string const &s) const |
Return true if the name of the class matches the argument. | |
ReturnCodes | get_failure_code () const |
Return the failure code of the last minimization. | |
Protected Member Functions | |
void | reset () |
void | report_eval (double f) |
Called by derived classes after each function evaluation. | |
virtual bool | report_iter () |
Called by derived classes after each iteration. | |
Protected Attributes | |
vnl_cost_function * | f_ |
double | f_at_last_minimum_ |
Function evaluation at value returned by minimize(x). | |
double | xtol |
Termination tolerance on X (solution vector) | |
long | maxfev |
Termination maximum number of iterations. | |
double | ftol |
Termination tolerance on F (sum of squared residuals) | |
double | gtol |
Termination tolerance on Grad(F)' * F = 0. | |
double | epsfcn |
Step length for FD Jacobian. | |
unsigned | num_iterations_ |
long | num_evaluations_ |
double | start_error_ |
double | end_error_ |
bool | trace |
bool | verbose_ |
int | check_derivatives_ |
ReturnCodes | failure_code_ |
Brent 1D minimizer (deprecated).
Please use vnl_brent_minimizer instead.
This routine used to contain copyrighted code, and is deprecated. It is now simply a wrapper around vnl_brent_minimizer.
Definition at line 27 of file vnl_brent.h.
enum vnl_nonlinear_minimizer::ReturnCodes [inherited] |
Some generic return codes that apply to all minimizers.
Definition at line 102 of file vnl_nonlinear_minimizer.h.
vnl_brent::vnl_brent | ( | vnl_cost_function * | functor | ) |
Definition at line 13 of file vnl_brent.cxx.
vnl_brent::~vnl_brent | ( | ) |
Definition at line 18 of file vnl_brent.cxx.
void vnl_brent::bracket_minimum | ( | double * | ax, |
double * | bx, | ||
double * | cx, | ||
double * | fa, | ||
double * | fb, | ||
double * | fc | ||
) |
Given distinct points ax, and bx, find a bracket for the minimum.
Return a bracket ax > bx > cx, f(b) < f(a), f(b) < f(c) for minimum. Also returns fa = f(a), etc.
You should probably use vnl_bracket_minimum instead of this function.
Definition at line 49 of file vnl_brent.cxx.
void vnl_brent::bracket_minimum | ( | double * | ax, |
double * | bx, | ||
double * | cx | ||
) |
Given distinct points ax, and bx, find a bracket for the minimum.
Return a bracket ax > bx > cx, f(b) < f(a), f(b) < f(c) for minimum.
You should probably use vnl_bracket_minimum instead of this function.
Definition at line 43 of file vnl_brent.cxx.
double vnl_brent_minimizer::f_at_last_minimum | ( | ) | const [inline, inherited] |
Function evaluation at value returned by minimize(x).
Definition at line 66 of file vnl_brent_minimizer.h.
int vnl_nonlinear_minimizer::get_check_derivatives | ( | ) | const [inline, inherited] |
Definition at line 82 of file vnl_nonlinear_minimizer.h.
vnl_matrix< double > const & vnl_nonlinear_minimizer::get_covariance | ( | ) | [virtual, inherited] |
Return the covariance of the estimate at the end.
Definition at line 35 of file vnl_nonlinear_minimizer.cxx.
double vnl_nonlinear_minimizer::get_end_error | ( | ) | const [inline, inherited] |
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.
double vnl_nonlinear_minimizer::get_epsilon_function | ( | ) | const [inline, inherited] |
Definition at line 70 of file vnl_nonlinear_minimizer.h.
double vnl_nonlinear_minimizer::get_f_tolerance | ( | ) | const [inline, inherited] |
Definition at line 46 of file vnl_nonlinear_minimizer.h.
ReturnCodes vnl_nonlinear_minimizer::get_failure_code | ( | ) | const [inline, inherited] |
Return the failure code of the last minimization.
Definition at line 132 of file vnl_nonlinear_minimizer.h.
double vnl_nonlinear_minimizer::get_g_tolerance | ( | ) | const [inline, inherited] |
Definition at line 60 of file vnl_nonlinear_minimizer.h.
int vnl_nonlinear_minimizer::get_max_function_evals | ( | ) | const [inline, inherited] |
Definition at line 64 of file vnl_nonlinear_minimizer.h.
int vnl_nonlinear_minimizer::get_num_evaluations | ( | ) | const [inline, inherited] |
Return the total number of times the function was evaluated by the last minimization.
Definition at line 95 of file vnl_nonlinear_minimizer.h.
int vnl_nonlinear_minimizer::get_num_iterations | ( | ) | const [inline, inherited] |
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.
double vnl_nonlinear_minimizer::get_start_error | ( | ) | const [inline, inherited] |
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.
bool vnl_nonlinear_minimizer::get_trace | ( | ) | const [inline, inherited] |
Definition at line 74 of file vnl_nonlinear_minimizer.h.
bool vnl_nonlinear_minimizer::get_verbose | ( | ) | const [inline, inherited] |
Definition at line 78 of file vnl_nonlinear_minimizer.h.
double vnl_nonlinear_minimizer::get_x_tolerance | ( | ) | const [inline, inherited] |
Definition at line 56 of file vnl_nonlinear_minimizer.h.
vcl_string vnl_nonlinear_minimizer::is_a | ( | ) | const [virtual, inherited] |
Return the name of the class.
Used by polymorphic IO
Definition at line 75 of file vnl_nonlinear_minimizer.cxx.
bool vnl_nonlinear_minimizer::is_class | ( | vcl_string const & | s | ) | const [virtual, inherited] |
Return true if the name of the class matches the argument.
Used by polymorphic IO
Definition at line 83 of file vnl_nonlinear_minimizer.cxx.
double vnl_brent::minimize | ( | double | ax | ) |
Find a minimum of f(x) near to ax.
Reimplemented from vnl_brent_minimizer.
Definition at line 56 of file vnl_brent.cxx.
double vnl_brent::minimize_given_bounds | ( | double | ax, |
double | bx, | ||
double | cx, | ||
double | tol, | ||
double * | xmin | ||
) |
Find the minimum value of f(x) within a<= x <= c.
The minimum value is the return value, and *xmin the relevant value of x. You need to provide a bracket for the minimum Also returns fa = f(a), etc.
Definition at line 22 of file vnl_brent.cxx.
double vnl_brent_minimizer::minimize_given_bounds | ( | double | ax, |
double | bx, | ||
double | cx | ||
) | [inherited] |
Find the minimum value of f(x) within a<= x <= c.
The | position,x, of the minimum x. You need to provide a bracket for the minimum (a<b<c s.t. f(a)>f(b)<f(c). The tolerance can be set using prior call to set_x_tolerance(tol). Use f_at_last_minimum() to get function evaluation at the returned minima. |
The minimum x is the return value. You need to provide a bracket for the minimum (a<b<c s.t. f(a)>f(b)<f(c). The tolerance can be set using prior call to set_x_tolerance(tol). Use f_at_last_minimum() to get function evaluation at the returned minima.
Definition at line 131 of file vnl_brent_minimizer.cxx.
double vnl_brent::minimize_given_bounds_and_1st_f | ( | double | ax, |
double | bx, | ||
double | fb, | ||
double | cx, | ||
double | tol, | ||
double * | xmin | ||
) |
Save time over minimize_given_bounds() if you know f(b).
This function avoids a single computation of f, if you already know it.
Definition at line 32 of file vnl_brent.cxx.
double vnl_brent_minimizer::minimize_given_bounds_and_all_f | ( | double | ax, |
double | bx, | ||
double | cx, | ||
double | fa, | ||
double | fb, | ||
double | fc | ||
) | [inherited] |
Find the minimum value of f(x) within a<= x <= c.
The | position,x, of the minimum x. You need to provide a bracket for the minimum (a<b<c s.t. f(a)>f(b)<f(c)), and the values fa=f(a), fb=f(b), fc=f(c). This avoids recalculating them if you have them already. If you don't have them, it is probably better to use minimize_given_bounds(a,b,c). |
The tolerance can be set using prior call to set_x_tolerance(tol). Use f_at_last_minimum() to get function evaluation at the returned minima.
The minimum x is the return value. You need to provide a bracket for the minimum (a<b<c s.t. f(a)>f(b)<f(c)), and the values fa=f(a), fb=f(b), fc=f(c). This avoids recalculating them if you have them already. The tolerance can be set using prior call to set_x_tolerance(tol). Use f_at_last_minimum() to get function evaluation at the returned minima.
Definition at line 255 of file vnl_brent_minimizer.cxx.
double vnl_brent_minimizer::minimize_given_bounds_and_one_f | ( | double | ax, |
double | bx, | ||
double | cx, | ||
double | fb | ||
) | [inherited] |
Find the minimum value of f(x) within a<= x <= c.
The | position,x, of the minimum x. You need to provide a bracket for the minimum (a<b<c s.t. f(a)>f(b)<f(c), and the known value at b (fb=f(b)). The tolerance can be set using prior call to set_x_tolerance(tol). Use f_at_last_minimum() to get function evaluation at the returned minima. |
The minimum x is the return value. You need to provide a bracket for the minimum (a<b<c s.t. f(a)>f(b)<f(c), and the known value at b (fb=f(b)). The tolerance can be set using prior call to set_x_tolerance(tol). Use f_at_last_minimum() to get function evaluation at the returned minima.
Definition at line 145 of file vnl_brent_minimizer.cxx.
double vnl_brent_minimizer::minimize_golden | ( | double | a, |
double | b, | ||
double | c, | ||
double | fa, | ||
double | fb, | ||
double | fc | ||
) | [inherited] |
Find the minimum x of f(x) within a<= x <= c using pure golden section.
The | position,x, of the minimum x. You need to provide a bracket for the minimum (a<b<c s.t. f(a)>f(b)<f(c). The tolerance can be set using prior call to set_x_tolerance(tol). Use f_at_last_minimum() to get function evaluation at the returned minima. |
The minimum x is the return value. You need to provide a bracket for the minimum (a<b<c s.t. f(a)>f(b)<f(c). The tolerance can be set using prior call to set_x_tolerance(tol). Use f_at_last_minimum() to get function evaluation at the returned minima.
Definition at line 48 of file vnl_brent_minimizer.cxx.
bool vnl_nonlinear_minimizer::obj_value_reduced | ( | ) | [inline, inherited] |
Whether the error reduced in the last minimization.
Definition at line 118 of file vnl_nonlinear_minimizer.h.
void vnl_nonlinear_minimizer::report_eval | ( | double | f | ) | [protected, inherited] |
Called by derived classes after each function evaluation.
Definition at line 50 of file vnl_nonlinear_minimizer.cxx.
bool vnl_nonlinear_minimizer::report_iter | ( | ) | [protected, virtual, inherited] |
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 63 of file vnl_nonlinear_minimizer.cxx.
void vnl_nonlinear_minimizer::reset | ( | ) | [protected, inherited] |
Definition at line 41 of file vnl_nonlinear_minimizer.cxx.
void vnl_nonlinear_minimizer::set_check_derivatives | ( | int | cd | ) | [inline, inherited] |
Set check_derivatives flag. Negative values may mean fewer checks.
Definition at line 81 of file vnl_nonlinear_minimizer.h.
void vnl_nonlinear_minimizer::set_epsilon_function | ( | double | v | ) | [inline, inherited] |
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.
void vnl_nonlinear_minimizer::set_f_tolerance | ( | double | v | ) | [inline, inherited] |
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.
void vnl_nonlinear_minimizer::set_g_tolerance | ( | double | v | ) | [inline, inherited] |
Set the convergence tolerance on Grad(F)' * F.
Definition at line 59 of file vnl_nonlinear_minimizer.h.
void vnl_nonlinear_minimizer::set_max_function_evals | ( | int | v | ) | [inline, inherited] |
Set the termination maximum number of iterations.
Definition at line 63 of file vnl_nonlinear_minimizer.h.
void vnl_nonlinear_minimizer::set_trace | ( | bool | on | ) | [inline, inherited] |
Turn on per-iteration printouts.
Definition at line 73 of file vnl_nonlinear_minimizer.h.
void vnl_nonlinear_minimizer::set_verbose | ( | bool | verb | ) | [inline, inherited] |
Set verbose flag.
Definition at line 77 of file vnl_nonlinear_minimizer.h.
void vnl_nonlinear_minimizer::set_x_tolerance | ( | double | v | ) | [inline, inherited] |
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.
int vnl_nonlinear_minimizer::check_derivatives_ [protected, inherited] |
Definition at line 153 of file vnl_nonlinear_minimizer.h.
double vnl_nonlinear_minimizer::end_error_ [protected, inherited] |
Definition at line 147 of file vnl_nonlinear_minimizer.h.
double vnl_nonlinear_minimizer::epsfcn [protected, inherited] |
Step length for FD Jacobian.
Definition at line 141 of file vnl_nonlinear_minimizer.h.
vnl_cost_function* vnl_brent_minimizer::f_ [protected, inherited] |
Definition at line 53 of file vnl_brent_minimizer.h.
double vnl_brent_minimizer::f_at_last_minimum_ [protected, inherited] |
Function evaluation at value returned by minimize(x).
Definition at line 55 of file vnl_brent_minimizer.h.
ReturnCodes vnl_nonlinear_minimizer::failure_code_ [protected, inherited] |
Definition at line 154 of file vnl_nonlinear_minimizer.h.
double vnl_nonlinear_minimizer::ftol [protected, inherited] |
Termination tolerance on F (sum of squared residuals)
Definition at line 139 of file vnl_nonlinear_minimizer.h.
double vnl_nonlinear_minimizer::gtol [protected, inherited] |
Termination tolerance on Grad(F)' * F = 0.
Definition at line 140 of file vnl_nonlinear_minimizer.h.
long vnl_nonlinear_minimizer::maxfev [protected, inherited] |
Termination maximum number of iterations.
Definition at line 138 of file vnl_nonlinear_minimizer.h.
long vnl_nonlinear_minimizer::num_evaluations_ [protected, inherited] |
Definition at line 145 of file vnl_nonlinear_minimizer.h.
unsigned vnl_nonlinear_minimizer::num_iterations_ [protected, inherited] |
Definition at line 144 of file vnl_nonlinear_minimizer.h.
double vnl_nonlinear_minimizer::start_error_ [protected, inherited] |
Definition at line 146 of file vnl_nonlinear_minimizer.h.
bool vnl_nonlinear_minimizer::trace [protected, inherited] |
Definition at line 149 of file vnl_nonlinear_minimizer.h.
bool vnl_nonlinear_minimizer::verbose_ [protected, inherited] |
Definition at line 152 of file vnl_nonlinear_minimizer.h.
double vnl_nonlinear_minimizer::xtol [protected, inherited] |
Termination tolerance on X (solution vector)
Definition at line 137 of file vnl_nonlinear_minimizer.h.