/* * Library: lmfit (Levenberg-Marquardt least squares fitting) * * File: demo/curve1.c * * Contents: Example for fitting data with error bars: * fit a data set (x,y+-dy) by a curve f(x;p). * * Author: Joachim Wuttke 2004-2013 * * Licence: see ../COPYING (FreeBSD) * * Homepage: apps.jcns.fz-juelich.de/lmfit */ #include "lmcurve_tyd.h" #include /* 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 */ /* 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 */ lmcurve_tyd( n, par, 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\n", i, par[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; }