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📄 bigauss.c

📁 This library is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY without ev
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/* randist/bigauss.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 <math.h>#include <gsl/gsl_math.h>#include <gsl/gsl_rng.h>#include <gsl/gsl_randist.h>/* The Bivariate Gaussian probability distribution is    p(x,y) dxdy = (1/(2 pi sigma_x sigma_y sqrt(c)))     exp(-((x/sigma_x)^2 + (y/sigma_y)^2 - 2 r (x/sigma_x)(y/sigma_y))/2c) dxdy    where c = 1-r^2*/voidgsl_ran_bivariate_gaussian (const gsl_rng * r,                             double sigma_x, double sigma_y, double rho,                            double *x, double *y){  double u, v, r2, scale;  do    {      /* choose x,y in uniform square (-1,-1) to (+1,+1) */      u = -1 + 2 * gsl_rng_uniform (r);      v = -1 + 2 * gsl_rng_uniform (r);      /* see if it is in the unit circle */      r2 = u * u + v * v;    }  while (r2 > 1.0 || r2 == 0);  scale = sqrt (-2.0 * log (r2) / r2);  *x = sigma_x * u * scale;  *y = sigma_y * (rho * u + sqrt(1 - rho*rho) * v) * scale;}doublegsl_ran_bivariate_gaussian_pdf (const double x, const double y,                                 const double sigma_x, const double sigma_y,                                const double rho){  double u = x / sigma_x ;  double v = y / sigma_y ;  double c = 1 - rho*rho ;  double p = (1 / (2 * M_PI * sigma_x * sigma_y * sqrt(c)))     * exp (-(u * u - 2 * rho * u * v + v * v) / (2 * c));  return p;}

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