1*5ddc57e5SXin Li /*
2*5ddc57e5SXin Li * Library: lmfit (Levenberg-Marquardt least squares fitting)
3*5ddc57e5SXin Li *
4*5ddc57e5SXin Li * File: demo/curve1.c
5*5ddc57e5SXin Li *
6*5ddc57e5SXin Li * Contents: Example for fitting data with error bars:
7*5ddc57e5SXin Li * fit a data set (x,y+-dy) by a curve f(x;p).
8*5ddc57e5SXin Li *
9*5ddc57e5SXin Li * Author: Joachim Wuttke <[email protected]> 2004-2013
10*5ddc57e5SXin Li *
11*5ddc57e5SXin Li * Licence: see ../COPYING (FreeBSD)
12*5ddc57e5SXin Li *
13*5ddc57e5SXin Li * Homepage: apps.jcns.fz-juelich.de/lmfit
14*5ddc57e5SXin Li */
15*5ddc57e5SXin Li
16*5ddc57e5SXin Li #include "lmcurve_tyd.h"
17*5ddc57e5SXin Li #include <stdio.h>
18*5ddc57e5SXin Li
19*5ddc57e5SXin Li /* model function: a parabola */
20*5ddc57e5SXin Li
f(double t,const double * p)21*5ddc57e5SXin Li double f( double t, const double *p )
22*5ddc57e5SXin Li {
23*5ddc57e5SXin Li return p[0] + p[1]*t + p[2]*t*t;
24*5ddc57e5SXin Li }
25*5ddc57e5SXin Li
main()26*5ddc57e5SXin Li int main()
27*5ddc57e5SXin Li {
28*5ddc57e5SXin Li int n = 3; /* number of parameters in model function f */
29*5ddc57e5SXin Li double par[3] = { 100, 0, -10 }; /* really bad starting value */
30*5ddc57e5SXin Li
31*5ddc57e5SXin Li /* data points: a slightly distorted standard parabola */
32*5ddc57e5SXin Li int m = 9;
33*5ddc57e5SXin Li int i;
34*5ddc57e5SXin Li double t[9] = { -4., -3., -2., -1., 0., 1., 2., 3., 4. };
35*5ddc57e5SXin Li double y[9] = { 16.6, 9.9, 4.4, 1.1, 0., 1.1, 4.2, 9.3, 16.4 };
36*5ddc57e5SXin Li double dy[9] = { 4, 3, 2, 1, 2, 3, 4, 5, 6 };
37*5ddc57e5SXin Li
38*5ddc57e5SXin Li lm_control_struct control = lm_control_double;
39*5ddc57e5SXin Li lm_status_struct status;
40*5ddc57e5SXin Li control.verbosity = 1;
41*5ddc57e5SXin Li
42*5ddc57e5SXin Li printf( "Fitting ...\n" );
43*5ddc57e5SXin Li /* now the call to lmfit */
44*5ddc57e5SXin Li lmcurve_tyd( n, par, m, t, y, dy, f, &control, &status );
45*5ddc57e5SXin Li
46*5ddc57e5SXin Li printf( "Results:\n" );
47*5ddc57e5SXin Li printf( "status after %d function evaluations:\n %s\n",
48*5ddc57e5SXin Li status.nfev, lm_infmsg[status.outcome] );
49*5ddc57e5SXin Li
50*5ddc57e5SXin Li printf("obtained parameters:\n");
51*5ddc57e5SXin Li for ( i = 0; i < n; ++i)
52*5ddc57e5SXin Li printf(" par[%i] = %12g\n", i, par[i]);
53*5ddc57e5SXin Li printf("obtained norm:\n %12g\n", status.fnorm );
54*5ddc57e5SXin Li
55*5ddc57e5SXin Li printf("fitting data as follows:\n");
56*5ddc57e5SXin Li for ( i = 0; i < m; ++i)
57*5ddc57e5SXin Li printf(
58*5ddc57e5SXin Li " t[%1d]=%2g y=%5.1f+-%4.1f fit=%8.5f residue=%8.4f weighed=%8.4f\n",
59*5ddc57e5SXin Li i, t[i], y[i], dy[i], f(t[i],par), y[i] - f(t[i],par),
60*5ddc57e5SXin Li (y[i] - f(t[i],par))/dy[i] );
61*5ddc57e5SXin Li
62*5ddc57e5SXin Li return 0;
63*5ddc57e5SXin Li }
64