real function minimization. More...
#include <vnl_conjugate_gradient.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_conjugate_gradient (vnl_cost_function &f) | |
Initialize with the function object that is to be minimized. | |
vnl_conjugate_gradient (vnl_cost_function &f, vnl_vector< double > &x) | |
Initialize as above, and then run minimization. | |
void | init (vnl_cost_function &f) |
Initialize all variables. | |
~vnl_conjugate_gradient () | |
Destructor. | |
void | diagnose_outcome (vcl_ostream &) const |
void | diagnose_outcome () const |
bool | minimize (vnl_vector< double > &x) |
Minimize the function supplied in the constructor until convergence or failure. | |
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. | |
Static Protected Member Functions | |
static double | valuecomputer_ (double *x, void *userdata) |
static void | gradientcomputer_ (double *g, double *x, void *userdata) |
static void | valueandgradientcomputer_ (double *v, double *g, double *x, void *userdata) |
static void | preconditioner_ (double *out, double *in, void *userdata) |
Protected Attributes | |
vnl_cost_function * | f_ |
double | final_step_size_ |
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_ |
real function minimization.
Definition at line 30 of file vnl_conjugate_gradient.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_conjugate_gradient::vnl_conjugate_gradient | ( | vnl_cost_function & | f | ) | [inline] |
Initialize with the function object that is to be minimized.
Definition at line 36 of file vnl_conjugate_gradient.h.
vnl_conjugate_gradient::vnl_conjugate_gradient | ( | vnl_cost_function & | f, |
vnl_vector< double > & | x | ||
) | [inline] |
Initialize as above, and then run minimization.
Definition at line 39 of file vnl_conjugate_gradient.h.
vnl_conjugate_gradient::~vnl_conjugate_gradient | ( | ) |
Destructor.
Definition at line 43 of file vnl_conjugate_gradient.cxx.
void vnl_conjugate_gradient::diagnose_outcome | ( | vcl_ostream & | os | ) | const |
Definition at line 197 of file vnl_conjugate_gradient.cxx.
void vnl_conjugate_gradient::diagnose_outcome | ( | ) | const |
Definition at line 211 of file vnl_conjugate_gradient.cxx.
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.
void vnl_conjugate_gradient::gradientcomputer_ | ( | double * | g, |
double * | x, | ||
void * | userdata | ||
) | [static, protected] |
Definition at line 70 of file vnl_conjugate_gradient.cxx.
void vnl_conjugate_gradient::init | ( | vnl_cost_function & | f | ) |
Initialize all variables.
Definition at line 47 of file vnl_conjugate_gradient.cxx.
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.
bool vnl_conjugate_gradient::minimize | ( | vnl_vector< double > & | x | ) |
Minimize the function supplied in the constructor until convergence or failure.
On return, x is such that f(x) is the lowest value achieved. Returns true for convergence, false for failure.
Definition at line 132 of file vnl_conjugate_gradient.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_conjugate_gradient::preconditioner_ | ( | double * | out, |
double * | in, | ||
void * | userdata | ||
) | [static, protected] |
Definition at line 92 of file vnl_conjugate_gradient.cxx.
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.
void vnl_conjugate_gradient::valueandgradientcomputer_ | ( | double * | v, |
double * | g, | ||
double * | x, | ||
void * | userdata | ||
) | [static, protected] |
Definition at line 81 of file vnl_conjugate_gradient.cxx.
double vnl_conjugate_gradient::valuecomputer_ | ( | double * | x, |
void * | userdata | ||
) | [static, protected] |
Definition at line 58 of file vnl_conjugate_gradient.cxx.
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_conjugate_gradient::f_ [protected] |
Definition at line 65 of file vnl_conjugate_gradient.h.
ReturnCodes vnl_nonlinear_minimizer::failure_code_ [protected, inherited] |
Definition at line 154 of file vnl_nonlinear_minimizer.h.
double vnl_conjugate_gradient::final_step_size_ [protected] |
Definition at line 66 of file vnl_conjugate_gradient.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.