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-rw-r--r--gsl-1.9/gsl-randist.c393
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+/* randist/gsl-randist.c
+ *
+ * Copyright (C) 1996, 1997, 1998, 1999, 2000 James Theiler, Brian Gough
+ *
+ * This program is free software; you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation; either version 2 of the License, or (at
+ * your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful, but
+ * WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+ * General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program; if not, write to the Free Software
+ * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
+ */
+
+#include <config.h>
+#include <stdio.h>
+#include <stdlib.h>
+#include <math.h>
+#include <string.h>
+
+#include <gsl/gsl_randist.h>
+#include <gsl/gsl_rng.h>
+#include <gsl/gsl_test.h>
+
+void error (const char * s);
+
+
+int
+main (int argc, char *argv[])
+{
+ size_t i,j;
+ size_t n = 0;
+ double mu = 0, nu = 0, nu1 = 0, nu2 = 0, sigma = 0, a = 0, b = 0, c = 0;
+ double zeta = 0, sigmax = 0, sigmay = 0, rho = 0;
+ double p = 0;
+ double x = 0, y =0, z=0 ;
+ unsigned int N = 0, t = 0, n1 = 0, n2 = 0 ;
+ unsigned long int seed = 0 ;
+ const char * name ;
+ gsl_rng * r ;
+
+ if (argc < 4)
+ {
+ printf (
+"Usage: gsl-randist seed n DIST param1 param2 ...\n"
+"Generates n samples from the distribution DIST with parameters param1,\n"
+"param2, etc. Valid distributions are,\n"
+"\n"
+" beta\n"
+" binomial\n"
+" bivariate-gaussian\n"
+" cauchy\n"
+" chisq\n"
+" dir-2d\n"
+" dir-3d\n"
+" dir-nd\n"
+" erlang\n"
+" exponential\n"
+" exppow\n"
+" fdist\n"
+" flat\n"
+" gamma\n"
+" gaussian-tail\n"
+" gaussian\n"
+" geometric\n"
+" gumbel1\n"
+" gumbel2\n"
+" hypergeometric\n"
+" laplace\n"
+" landau\n"
+" levy\n"
+" levy-skew\n"
+" logarithmic\n"
+" logistic\n"
+" lognormal\n"
+" negative-binomial\n"
+" pareto\n"
+" pascal\n"
+" poisson\n"
+" rayleigh-tail\n"
+" rayleigh\n"
+" tdist\n"
+" ugaussian-tail\n"
+" ugaussian\n"
+" weibull\n") ;
+ exit (0);
+ }
+
+ argv++ ; seed = atol (argv[0]); argc-- ;
+ argv++ ; n = atol (argv[0]); argc-- ;
+ argv++ ; name = argv[0] ; argc-- ; argc-- ;
+
+ gsl_rng_env_setup() ;
+
+ if (gsl_rng_default_seed != 0) {
+ fprintf(stderr,
+ "overriding GSL_RNG_SEED with command line value, seed = %ld\n",
+ seed) ;
+ }
+
+ gsl_rng_default_seed = seed ;
+
+ r = gsl_rng_alloc(gsl_rng_default) ;
+
+
+#define NAME(x) !strcmp(name,(x))
+#define OUTPUT(x) for (i = 0; i < n; i++) { printf("%g\n", (x)) ; }
+#define OUTPUT1(a,x) for(i = 0; i < n; i++) { a ; printf("%g\n", x) ; }
+#define OUTPUT2(a,x,y) for(i = 0; i < n; i++) { a ; printf("%g %g\n", x, y) ; }
+#define OUTPUT3(a,x,y,z) for(i = 0; i < n; i++) { a ; printf("%g %g %g\n", x, y, z) ; }
+#define INT_OUTPUT(x) for (i = 0; i < n; i++) { printf("%d\n", (x)) ; }
+#define ARGS(x,y) if (argc != x) error(y) ;
+#define DBL_ARG(x) if (argc) { x=atof((++argv)[0]);argc--;} else {error( #x);};
+#define INT_ARG(x) if (argc) { x=atoi((++argv)[0]);argc--;} else {error( #x);};
+
+ if (NAME("bernoulli"))
+ {
+ ARGS(1, "p = probability of success");
+ DBL_ARG(p)
+ INT_OUTPUT(gsl_ran_bernoulli (r, p));
+ }
+ else if (NAME("beta"))
+ {
+ ARGS(2, "a,b = shape parameters");
+ DBL_ARG(a)
+ DBL_ARG(b)
+ OUTPUT(gsl_ran_beta (r, a, b));
+ }
+ else if (NAME("binomial"))
+ {
+ ARGS(2, "p = probability, N = number of trials");
+ DBL_ARG(p)
+ INT_ARG(N)
+ INT_OUTPUT(gsl_ran_binomial (r, p, N));
+ }
+ else if (NAME("cauchy"))
+ {
+ ARGS(1, "a = scale parameter");
+ DBL_ARG(a)
+ OUTPUT(gsl_ran_cauchy (r, a));
+ }
+ else if (NAME("chisq"))
+ {
+ ARGS(1, "nu = degrees of freedom");
+ DBL_ARG(nu)
+ OUTPUT(gsl_ran_chisq (r, nu));
+ }
+ else if (NAME("erlang"))
+ {
+ ARGS(2, "a = scale parameter, b = order");
+ DBL_ARG(a)
+ DBL_ARG(b)
+ OUTPUT(gsl_ran_erlang (r, a, b));
+ }
+ else if (NAME("exponential"))
+ {
+ ARGS(1, "mu = mean value");
+ DBL_ARG(mu) ;
+ OUTPUT(gsl_ran_exponential (r, mu));
+ }
+ else if (NAME("exppow"))
+ {
+ ARGS(2, "a = scale parameter, b = power (1=exponential, 2=gaussian)");
+ DBL_ARG(a) ;
+ DBL_ARG(b) ;
+ OUTPUT(gsl_ran_exppow (r, a, b));
+ }
+ else if (NAME("fdist"))
+ {
+ ARGS(2, "nu1, nu2 = degrees of freedom parameters");
+ DBL_ARG(nu1) ;
+ DBL_ARG(nu2) ;
+ OUTPUT(gsl_ran_fdist (r, nu1, nu2));
+ }
+ else if (NAME("flat"))
+ {
+ ARGS(2, "a = lower limit, b = upper limit");
+ DBL_ARG(a) ;
+ DBL_ARG(b) ;
+ OUTPUT(gsl_ran_flat (r, a, b));
+ }
+ else if (NAME("gamma"))
+ {
+ ARGS(2, "a = order, b = scale");
+ DBL_ARG(a) ;
+ DBL_ARG(b) ;
+ OUTPUT(gsl_ran_gamma (r, a, b));
+ }
+ else if (NAME("gaussian"))
+ {
+ ARGS(1, "sigma = standard deviation");
+ DBL_ARG(sigma) ;
+ OUTPUT(gsl_ran_gaussian (r, sigma));
+ }
+ else if (NAME("gaussian-tail"))
+ {
+ ARGS(2, "a = lower limit, sigma = standard deviation");
+ DBL_ARG(a) ;
+ DBL_ARG(sigma) ;
+ OUTPUT(gsl_ran_gaussian_tail (r, a, sigma));
+ }
+ else if (NAME("ugaussian"))
+ {
+ ARGS(0, "unit gaussian, no parameters required");
+ OUTPUT(gsl_ran_ugaussian (r));
+ }
+ else if (NAME("ugaussian-tail"))
+ {
+ ARGS(1, "a = lower limit");
+ DBL_ARG(a) ;
+ OUTPUT(gsl_ran_ugaussian_tail (r, a));
+ }
+ else if (NAME("bivariate-gaussian"))
+ {
+ ARGS(3, "sigmax = x std.dev., sigmay = y std.dev., rho = correlation");
+ DBL_ARG(sigmax) ;
+ DBL_ARG(sigmay) ;
+ DBL_ARG(rho) ;
+ OUTPUT2(gsl_ran_bivariate_gaussian (r, sigmax, sigmay, rho, &x, &y),
+ x, y);
+ }
+ else if (NAME("dir-2d"))
+ {
+ OUTPUT2(gsl_ran_dir_2d (r, &x, &y), x, y);
+ }
+ else if (NAME("dir-3d"))
+ {
+ OUTPUT3(gsl_ran_dir_3d (r, &x, &y, &z), x, y, z);
+ }
+ else if (NAME("dir-nd"))
+ {
+ double *xarr;
+ ARGS(1, "n1 = number of dimensions of hypersphere");
+ INT_ARG(n1) ;
+ xarr = (double *)malloc(n1*sizeof(double));
+
+ for(i = 0; i < n; i++) {
+ gsl_ran_dir_nd (r, n1, xarr) ;
+ for (j = 0; j < n1; j++) {
+ if (j) putchar(' ');
+ printf("%g", xarr[j]) ;
+ }
+ putchar('\n');
+ } ;
+
+ free(xarr);
+ }
+ else if (NAME("geometric"))
+ {
+ ARGS(1, "p = bernoulli trial probability of success");
+ DBL_ARG(p) ;
+ INT_OUTPUT(gsl_ran_geometric (r, p));
+ }
+ else if (NAME("gumbel1"))
+ {
+ ARGS(2, "a = order, b = scale parameter");
+ DBL_ARG(a) ;
+ DBL_ARG(b) ;
+ OUTPUT(gsl_ran_gumbel1 (r, a, b));
+ }
+ else if (NAME("gumbel2"))
+ {
+ ARGS(2, "a = order, b = scale parameter");
+ DBL_ARG(a) ;
+ DBL_ARG(b) ;
+ OUTPUT(gsl_ran_gumbel2 (r, a, b));
+ }
+ else if (NAME("hypergeometric"))
+ {
+ ARGS(3, "n1 = tagged population, n2 = untagged population, t = number of trials");
+ INT_ARG(n1) ;
+ INT_ARG(n2) ;
+ INT_ARG(t) ;
+ INT_OUTPUT(gsl_ran_hypergeometric (r, n1, n2, t));
+ }
+ else if (NAME("laplace"))
+ {
+ ARGS(1, "a = scale parameter");
+ DBL_ARG(a) ;
+ OUTPUT(gsl_ran_laplace (r, a));
+ }
+ else if (NAME("landau"))
+ {
+ ARGS(0, "no arguments required");
+ OUTPUT(gsl_ran_landau (r));
+ }
+ else if (NAME("levy"))
+ {
+ ARGS(2, "c = scale, a = power (1=cauchy, 2=gaussian)");
+ DBL_ARG(c) ;
+ DBL_ARG(a) ;
+ OUTPUT(gsl_ran_levy (r, c, a));
+ }
+ else if (NAME("levy-skew"))
+ {
+ ARGS(3, "c = scale, a = power (1=cauchy, 2=gaussian), b = skew");
+ DBL_ARG(c) ;
+ DBL_ARG(a) ;
+ DBL_ARG(b) ;
+ OUTPUT(gsl_ran_levy_skew (r, c, a, b));
+ }
+ else if (NAME("logarithmic"))
+ {
+ ARGS(1, "p = probability");
+ DBL_ARG(p) ;
+ INT_OUTPUT(gsl_ran_logarithmic (r, p));
+ }
+ else if (NAME("logistic"))
+ {
+ ARGS(1, "a = scale parameter");
+ DBL_ARG(a) ;
+ OUTPUT(gsl_ran_logistic (r, a));
+ }
+ else if (NAME("lognormal"))
+ {
+ ARGS(2, "zeta = location parameter, sigma = scale parameter");
+ DBL_ARG(zeta) ;
+ DBL_ARG(sigma) ;
+ OUTPUT(gsl_ran_lognormal (r, zeta, sigma));
+ }
+ else if (NAME("negative-binomial"))
+ {
+ ARGS(2, "p = probability, a = order");
+ DBL_ARG(p) ;
+ DBL_ARG(a) ;
+ INT_OUTPUT(gsl_ran_negative_binomial (r, p, a));
+ }
+ else if (NAME("pareto"))
+ {
+ ARGS(2, "a = power, b = scale parameter");
+ DBL_ARG(a) ;
+ DBL_ARG(b) ;
+ OUTPUT(gsl_ran_pareto (r, a, b));
+ }
+ else if (NAME("pascal"))
+ {
+ ARGS(2, "p = probability, n = order (integer)");
+ DBL_ARG(p) ;
+ INT_ARG(N) ;
+ INT_OUTPUT(gsl_ran_pascal (r, p, N));
+ }
+ else if (NAME("poisson"))
+ {
+ ARGS(1, "mu = scale parameter");
+ DBL_ARG(mu) ;
+ INT_OUTPUT(gsl_ran_poisson (r, mu));
+ }
+ else if (NAME("rayleigh"))
+ {
+ ARGS(1, "sigma = scale parameter");
+ DBL_ARG(sigma) ;
+ OUTPUT(gsl_ran_rayleigh (r, sigma));
+ }
+ else if (NAME("rayleigh-tail"))
+ {
+ ARGS(2, "a = lower limit, sigma = scale parameter");
+ DBL_ARG(a) ;
+ DBL_ARG(sigma) ;
+ OUTPUT(gsl_ran_rayleigh_tail (r, a, sigma));
+ }
+ else if (NAME("tdist"))
+ {
+ ARGS(1, "nu = degrees of freedom");
+ DBL_ARG(nu) ;
+ OUTPUT(gsl_ran_tdist (r, nu));
+ }
+ else if (NAME("weibull"))
+ {
+ ARGS(2, "a = scale parameter, b = exponent");
+ DBL_ARG(a) ;
+ DBL_ARG(b) ;
+ OUTPUT(gsl_ran_weibull (r, a, b));
+ }
+ else
+ {
+ fprintf(stderr,"Error: unrecognized distribution: %s\n", name) ;
+ }
+
+ return 0 ;
+}
+
+
+void
+error (const char * s)
+{
+ fprintf(stderr, "Error: arguments should be %s\n",s) ;
+ exit (EXIT_FAILURE) ;
+}
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