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wrkdirs::usr:...man::lmcurve2(3)  lmfit manual	wrkdirs::usr:...man::lmcurve2(3)

NAME
     lmcurve2 - Levenberg-Marquardt least-squares fit of a curve (t,y,dy)

SYNOPSIS
     #include <lmcurve2.h>

     void lmcurve2(
		   const int n_par, double *par,
		   double *parerr, double *covar,
		   const int m_dat, const double *t,
		   const double *y, const double *dy,
		   double (*f)( const double ti, const double *par ),
		   const lm_control_struct *control,
		   lm_status_struct *status);

     extern const lm_control_struct lm_control_double;

     extern const lm_control_struct lm_control_float;

     extern const char *lm_infmsg[];

     extern const char *lm_shortmsg[];

DESCRIPTION
     lmcurve2() wraps the more generic minimization function lmmin2(), for use
     in curve fitting.

     lmcurve2() determines a vector par that minimizes the sum of squared ele-
     ments of a residue vector r[i] := (y[i] - f(t[i];par)) / dy[i]. Typically,
     lmcurve2() is used to approximate a data set t,y,dy, where dy represents
     the standard deviation of empirical data y, by a parametric function
     f(ti;par). On success, par represents a local minimum, not necessarily a
     global one; it may depend on its starting value. Users must ensure that all
     dy[i] are positive.

     Function arguments:

     n_par
	 Number of free variables.  Length of parameter vector par.

     par Parameter vector.  On input, it must contain a reasonable guess.  On
	 output, it contains the solution found to minimize ||r||.

     parerr
	 Parameter uncertainties vector.  Array of length n_par or NULL.  On
	 output, unless it or covar is NULL, it contains the weighted parameter
	 uncertainties for the found parameters.

     covar
	 Covariance matrix.  Array of length n_par * n_par or NULL.  On output,
	 unless it is NULL, it contains the covariance matrix.

     m_dat
	 Number of data points.  Length of vectors t, y, dy.  Must statisfy
	 n_par <= m_dat.

     t	 Array of length m_dat.  Contains the abcissae (time, or "x") for which
	 function f will be evaluated.

     y	 Array of length m_dat.  Contains the ordinate values that shall be fit-
	 ted.

     dy  Array of length m_dat.  Contains the standard deviations of the values
	 y.

     f	 A user-supplied parametric function f(ti;par).

     control
	 Parameter collection for tuning the fit procedure.  In most cases, the
	 default &lm_control_double is adequate.  If f is only computed with
	 single-precision accuracy, &lm_control_float should be used.  Parame-
	 ters are explained in lmmin2(3).

     status
	 A record used to return information about the minimization process: For
	 details, see lmmin2(3).

EXAMPLE
     Fit a data set y(x) with standard deviations dy(x) by a curve f(x;p):

	 #include "lmcurve2.h"
	 #include <stdio.h>

	 /* model function: a parabola */

	 double f( double t, const double *p )
	 {
	     return p[0] + p[1]*t + p[2]*t*t;
	 }

	 int main()
	 {
	     int n = 3; /* number of parameters in model function f */
	     double par[3] = { 100, 0, -10 }; /* really bad starting value */
	     double parerr[3];
	     double covar[3*3];

	     /* data points: a slightly distorted standard parabola */
	     int m = 9;
	     int i;
	     double t[9] = { -4., -3., -2., -1.,  0., 1.,  2.,	3.,  4. };
	     double y[9] = { 16.6, 9.9, 4.4, 1.1, 0., 1.1, 4.2, 9.3, 16.4 };
	     double dy[9] = { 4, 3, 2, 1, 2, 3, 4, 5, 6 };

	     lm_control_struct control = lm_control_double;
	     lm_status_struct status;
	     control.verbosity = 1;

	     printf( "Fitting ...\n" );
	     /* now the call to lmfit */
	     lmcurve2( n, par, parerr, covar, m, t, y, dy, f, &control, &status );

	     printf( "Results:\n" );
	     printf( "status after %d function evaluations:\n  %s\n",
		     status.nfev, lm_infmsg[status.outcome] );

	     printf("obtained parameters:\n");
	     for ( i = 0; i < n; ++i)
		 printf("  par[%i] = %12g  uncertainty = %12g\n", i, par[i], parerr[i]);
	     printf("obtained norm:\n  %12g\n", status.fnorm );

	     printf("fitting data as follows:\n");
	     for ( i = 0; i < m; ++i)
		 printf(
		 "  t[%1d]=%2g y=%5.1f+-%4.1f fit=%8.5f residue=%8.4f weighed=%8.4f\n",
		 i, t[i], y[i], dy[i], f(t[i],par), y[i] - f(t[i],par),
		 (y[i] - f(t[i],par))/dy[i] );

	     return 0;
	 }

COPYING
     Copyright (C) 2009-2015 Joachim Wuttke, Forschungszentrum Juelich GmbH

     Software: FreeBSD License

     Documentation: Creative Commons Attribution Share Alike

SEE ALSO
     lmmin2(3)

     Homepage: https://jugit.fz-juelich.de/mlz/lmfit

BUGS
     Please send bug reports and suggestions to the author <j.wut-
     tke@fz-juelich.de>.

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