=pod
=begin html
=end html
=head1 NAME
lmmin - Levenberg-Marquardt least-squares minimization
=head1 SYNOPSIS
B<#include >
B IB<, double *>IB<, const int> IB<,
constS< >void *>IB<,
void *>IB<(
constS< >double *>IB<, const int >IB<,
constS< >void *>IB<, double *>IB<, int *>IB<),
constS< >lm_control_struct *>IB<,
lm_status_struct *>IB< );>
B
B
B
B
=head1 DESCRIPTION
B determines a vector I that minimizes the sum of squared elements of a vector I that is computed by a user-supplied function I().
On success, I represents a local minimum, not necessarily a global one; it may depend on its starting value.
For applications in curve fitting, the wrapper function B offers a simplified API.
The Levenberg-Marquardt minimization starts with a steepest-descent exploration of the parameter space, and achieves rapid convergence by crossing over into the Newton-Gauss method.
Function arguments:
=over
=item I
Number of free variables.
Length of parameter vector I.
=item I
Parameter vector.
On input, it must contain a reasonable guess.
On output, it contains the solution found to minimize ||I||.
=item I
Length of vector I.
Must statisfy I <= I.
=item I
This pointer is ignored by the fit algorithm,
except for appearing as an argument in all calls to the user-supplied
routine I.
=item I
Pointer to a user-supplied function that computes I elements of vector I for a given parameter vector I.
If I return with *I set to a negative value, B will interrupt the fitting and terminate.
=item I
Parameter collection for tuning the fit procedure.
In most cases, the default &I is adequate.
If I is only computed with single-precision accuracy,
I<&lm_control_float> should be used.
See also below, NOTES on initializing parameter records.
I has the following members (for more details, see the source file I):
=over
=item B I
Relative error desired in the sum of squares.
Recommended setting: somewhat above machine precision; less if I is computed with reduced accuracy.
=item B I
Relative error between last two approximations.
Recommended setting: as I.
=item B I
A measure for degeneracy.
Recommended setting: as I.
=item B I
Step used to calculate the Jacobian.
Recommended setting: as I, but definitely less than the accuracy of I.
=item B I
Initial bound to steps in the outer loop, generally between 0.01 and 100; recommended value is 100.
=item B I
Used to set the maximum number of function evaluations to patience*n_par.
=item B I
Logical switch (0 or 1).
If 1, then scale parameters to their initial value.
This is the recommended setting.
=item B I
Progress messages will be written to this file.
Typically I or I.
The value I will be interpreted as I.
=item B I
If nonzero, some progress information from within the LM algorithm
is written to control.stream.
=item B I
-1, or maximum number of parameters to print.
=item B I
-1, or maximum number of residuals to print.
=back
=item I
A record used to return information about the minimization process:
=over
=item B I
Norm of the vector I;
=item B I
Actual number of iterations;
=item B I
Status of minimization;
for the corresponding text message, print IB<[>IB<]>;
for a short code, print IB<[>IB<]>.
=item B I
Set when termination has been forced by the user-supplied routine I.
=back
=back
=head1 NOTES
=head2 Initializing parameter records.
The parameter record I should always be initialized
from supplied default records:
lm_control_struct control = lm_control_double; /* or _float */
After this, parameters may be overwritten:
control.patience = 500; /* allow more iterations */
control.verbosity = 15; /* for verbose monitoring */
An application written this way is guaranteed to work even if new parameters
are added to I.
Conversely, addition of parameters is not considered an API change; it may happen without increment of the major version number.
=head1 EXAMPLES
=head2 Fitting a surface
Fit a data set y(t) by a function f(t;p) where t is a two-dimensional vector:
#include "lmmin.h"
#include
/* fit model: a plane p0 + p1*tx + p2*tz */
double f( double tx, double tz, const double *p )
{
return p[0] + p[1]*tx + p[2]*tz;
}
/* data structure to transmit data arays and fit model */
typedef struct {
double *tx, *tz;
double *y;
double (*f)( double tx, double tz, const double *p );
} data_struct;
/* function evaluation, determination of residues */
void evaluate_surface( const double *par, int m_dat,
const void *data, double *fvec, int *userbreak )
{
/* for readability, explicit type conversion */
data_struct *D;
D = (data_struct*)data;
int i;
for ( i = 0; i < m_dat; i++ )
fvec[i] = D->y[i] - D->f( D->tx[i], D->tz[i], par );
}
int main()
{
/* parameter vector */
int n_par = 3; /* number of parameters in model function f */
double par[3] = { -1, 0, 1 }; /* arbitrary starting value */
/* data points */
int m_dat = 4;
double tx[4] = { -1, -1, 1, 1 };
double tz[4] = { -1, 1, -1, 1 };
double y[4] = { 0, 1, 1, 2 };
data_struct data = { tx, tz, y, f };
/* auxiliary parameters */
lm_status_struct status;
lm_control_struct control = lm_control_double;
control.verbosity = 3;
/* perform the fit */
printf( "Fitting:\n" );
lmmin( n_par, par, m_dat, (const void*) &data, evaluate_surface,
&control, &status );
/* print results */
printf( "\nResults:\n" );
printf( "status after %d function evaluations:\n %s\n",
status.nfev, lm_infmsg[status.outcome] );
printf("obtained parameters:\n");
int i;
for ( i=0; ilmcurve(3)
=end html
=begin man
\fBlmcurve\fR(3)
.PP
=end man
Homepage: http://apps.jcns.fz-juelich.de/lmfit
=head1 BUGS
Please send bug reports and suggestions to the author .