#include #include #include #include #include /* Of the two methods provided below, I think the Polar method is more * efficient, but only when you are actually producing two random * deviates. We don't produce two, because then we'd have to save one * in a static variable for the next call, and that would screws up * re-entrant or threaded code, so we only produce one. This makes * the Ratio method suddenly more appealing. There are further tests * one can make if the log() is slow. See Knuth for details */ /* Both methods pass the statistical tests; but the polar method * seems to be a touch faster on my home Pentium, EVEN though we * are only using half of the available random deviates! */ /* Polar (Box-Mueller) method; See Knuth v2, 3rd ed, p122 */ double gsl_ran_gaussian (const gsl_rng * r, const double sigma) { double x, y, r2; do { /* choose x,y in uniform square (-1,-1) to (+1,+1) */ x = -1 + 2 * gsl_rng_uniform (r); y = -1 + 2 * gsl_rng_uniform (r); /* see if it is in the unit circle */ r2 = x * x + y * y; } while (r2 > 1.0 || r2 == 0); /* Box-Muller transform */ return sigma * y * sqrt (-2.0 * log (r2) / r2); } /* Ratio method (Kinderman-Monahan); see Knuth v2, 3rd ed, p130 */ /* K+M, ACM Trans Math Software 3 (1977) 257-260. */ double gsl_ran_gaussian_ratio_method (const gsl_rng * r, const double sigma) { double u, v, x; do { v = gsl_rng_uniform (r); do { u = gsl_rng_uniform (r); } while (u == 0); /* Const 1.715... = sqrt(8/e) */ x = 1.71552776992141359295 * (v - 0.5) / u; } while (x * x > -4.0 * log (u)); return sigma * x; } double gsl_ran_gaussian_pdf (const double x, const double sigma) { double u = x / fabs (sigma); double p = (1 / (sqrt (2 * M_PI) * fabs (sigma))) * exp (-u * u / 2); return p; } double gsl_ran_ugaussian (const gsl_rng * r) { return gsl_ran_gaussian (r, 1.0); } double gsl_ran_ugaussian_ratio_method (const gsl_rng * r) { return gsl_ran_gaussian_ratio_method (r, 1.0); } double gsl_ran_ugaussian_pdf (const double x) { return gsl_ran_gaussian_pdf (x, 1.0); }