The following program computes a least squares straight-line fit to a simple dataset, and outputs the best-fit line and its associated one standard-deviation error bars.
#include <stdio.h> #include <gsl/gsl_fit.h> int main (void) { int i, n = 4; double x[4] = { 1970, 1980, 1990, 2000 }; double y[4] = { 12, 11, 14, 13 }; double w[4] = { 0.1, 0.2, 0.3, 0.4 }; double c0, c1, cov00, cov01, cov11, chisq; gsl_fit_wlinear (x, 1, w, 1, y, 1, n, &c0, &c1, &cov00, &cov01, &cov11, &chisq); printf ("# best fit: Y = %g + %g X\n", c0, c1); printf ("# covariance matrix:\n"); printf ("# [ %g, %g\n# %g, %g]\n", cov00, cov01, cov01, cov11); printf ("# chisq = %g\n", chisq); for (i = 0; i < n; i++) printf ("data: %g %g %g\n", x[i], y[i], 1/sqrt(w[i])); printf ("\n"); for (i = -30; i < 130; i++) { double xf = x[0] + (i/100.0) * (x[n-1] - x[0]); double yf, yf_err; gsl_fit_linear_est (xf, c0, c1, cov00, cov01, cov11, &yf, &yf_err); printf ("fit: %g %g\n", xf, yf); printf ("hi : %g %g\n", xf, yf + yf_err); printf ("lo : %g %g\n", xf, yf - yf_err); } return 0; }
The following commands extract the data from the output of the program
and display it using the GNU plotutils graph
utility,
$ ./demo > tmp $ more tmp # best fit: Y = -106.6 + 0.06 X # covariance matrix: # [ 39602, -19.9 # -19.9, 0.01] # chisq = 0.8 $ for n in data fit hi lo ; do grep "^$n" tmp | cut -d: -f2 > $n ; done $ graph -T X -X x -Y y -y 0 20 -m 0 -S 2 -Ie data -S 0 -I a -m 1 fit -m 2 hi -m 2 lo