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 GNU Scientific Library Reference Manual - Third Edition (v1.12) by M. Galassi, J. Davies, J. Theiler, B. Gough, G. Jungman, P. Alken, M. Booth, F. RossiPaperback (6"x9"), 592 pages, 60 figuresISBN 0954612078RRP £24.95 ($39.95) ## 38.6 Examples The following program computes a linear least squares fit to data using cubic B-spline basis functions with uniform breakpoints. The data is generated from the curve y(x) = \cos{(x) \exp{(-x/10)}} on the interval [0, 15] with gaussian noise added. #include <stdio.h> #include <stdlib.h> #include <math.h> #include <gsl/gsl_bspline.h> #include <gsl/gsl_multifit.h> #include <gsl/gsl_rng.h> #include <gsl/gsl_randist.h> #include <gsl/gsl_statistics.h> /* number of data points to fit */ #define N 200 /* number of fit coefficients */ #define NCOEFFS 12 /* nbreak = ncoeffs + 2 - k = ncoeffs - 2 since k = 4 */ #define NBREAK (NCOEFFS - 2) int main (void) { const size_t n = N; const size_t ncoeffs = NCOEFFS; const size_t nbreak = NBREAK; size_t i, j; gsl_bspline_workspace *bw; gsl_vector *B; double dy; gsl_rng *r; gsl_vector *c, *w; gsl_vector *x, *y; gsl_matrix *X, *cov; gsl_multifit_linear_workspace *mw; double chisq, Rsq, dof, tss; gsl_rng_env_setup(); r = gsl_rng_alloc(gsl_rng_default); /* allocate a cubic bspline workspace (k = 4) */ bw = gsl_bspline_alloc(4, nbreak); B = gsl_vector_alloc(ncoeffs); x = gsl_vector_alloc(n); y = gsl_vector_alloc(n); X = gsl_matrix_alloc(n, ncoeffs); c = gsl_vector_alloc(ncoeffs); w = gsl_vector_alloc(n); cov = gsl_matrix_alloc(ncoeffs, ncoeffs); mw = gsl_multifit_linear_alloc(n, ncoeffs); printf("#m=0,S=0\n"); /* this is the data to be fitted */ for (i = 0; i < n; ++i) { double sigma; double xi = (15.0 / (N - 1)) * i; double yi = cos(xi) * exp(-0.1 * xi); sigma = 0.1 * yi; dy = gsl_ran_gaussian(r, sigma); yi += dy; gsl_vector_set(x, i, xi); gsl_vector_set(y, i, yi); gsl_vector_set(w, i, 1.0 / (sigma * sigma)); printf("%f %f\n", xi, yi); } /* use uniform breakpoints on [0, 15] */ gsl_bspline_knots_uniform(0.0, 15.0, bw); /* construct the fit matrix X */ for (i = 0; i < n; ++i) { double xi = gsl_vector_get(x, i); /* compute B_j(xi) for all j */ gsl_bspline_eval(xi, B, bw); /* fill in row i of X */ for (j = 0; j < ncoeffs; ++j) { double Bj = gsl_vector_get(B, j); gsl_matrix_set(X, i, j, Bj); } } /* do the fit */ gsl_multifit_wlinear(X, w, y, c, cov, &chisq, mw); dof = n - ncoeffs; tss = gsl_stats_wtss(w->data, 1, y->data, 1, y->size); Rsq = 1.0 - chisq / tss; fprintf(stderr, "chisq/dof = %e, Rsq = %f\n", chisq / dof, Rsq); /* output the smoothed curve */ { double xi, yi, yerr; printf("#m=1,S=0\n"); for (xi = 0.0; xi < 15.0; xi += 0.1) { gsl_bspline_eval(xi, B, bw); gsl_multifit_linear_est(B, c, cov, &yi, &yerr); printf("%f %f\n", xi, yi); } } gsl_rng_free(r); gsl_bspline_free(bw); gsl_vector_free(B); gsl_vector_free(x); gsl_vector_free(y); gsl_matrix_free(X); gsl_vector_free(c); gsl_vector_free(w); gsl_matrix_free(cov); gsl_multifit_linear_free(mw); return 0; } /* main() */  The output can be plotted with gnu graph. $ ./a.out > bspline.dat
chisq/dof = 1.118217e+00, Rsq = 0.989771
\$ graph -T ps -X x -Y y -x 0 15 -y -1 1.3 < bspline.dat
> bspline.ps

 ISBN 0954612078 GNU Scientific Library Reference Manual - Third Edition (v1.12) See the print edition