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📄 beta.c

📁 开放gsl矩阵运算
💻 C
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/* specfunc/beta.c *  * Copyright (C) 1996, 1997, 1998, 1999, 2000 Gerard Jungman *  * 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., 675 Mass Ave, Cambridge, MA 02139, USA. *//* Author:  G. Jungman */#include <config.h>#include <gsl/gsl_math.h>#include <gsl/gsl_errno.h>#include "gsl_sf_exp.h"#include "gsl_sf_log.h"#include "gsl_sf_psi.h"#include "gsl_sf_gamma.h"#include "error.h"intgsl_sf_lnbeta_e(const double x, const double y, gsl_sf_result * result){  /* CHECK_POINTER(result) */  if(x <= 0.0 || y <= 0.0) {    DOMAIN_ERROR(result);  }  else {    const double max = GSL_MAX(x,y);    const double min = GSL_MIN(x,y);    const double rat = min/max;    if(rat < 0.2) {      /* min << max, so be careful       * with the subtraction       */      double lnpre_val;      double lnpre_err;      double lnpow_val;      double lnpow_err;      double t1, t2, t3;      gsl_sf_result lnopr;      gsl_sf_result gsx, gsy, gsxy;      gsl_sf_gammastar_e(x, &gsx);      gsl_sf_gammastar_e(y, &gsy);      gsl_sf_gammastar_e(x+y, &gsxy);      gsl_sf_log_1plusx_e(rat, &lnopr);      lnpre_val = log(gsx.val*gsy.val/gsxy.val * M_SQRT2*M_SQRTPI);      lnpre_err = gsx.err/gsx.val + gsy.err/gsy.val + gsxy.err/gsxy.val;      t1 = min*log(rat);      t2 = 0.5*log(min);      t3 = (x+y-0.5)*lnopr.val;      lnpow_val  = t1 - t2 - t3;      lnpow_err  = GSL_DBL_EPSILON * (fabs(t1) + fabs(t2) + fabs(t3));      lnpow_err += fabs(x+y-0.5) * lnopr.err;      result->val  = lnpre_val + lnpow_val;      result->err  = lnpre_err + lnpow_err;      result->err += 2.0 * GSL_DBL_EPSILON * fabs(result->val);      return GSL_SUCCESS;    }    else {      gsl_sf_result lgx, lgy, lgxy;      int stat_gx  = gsl_sf_lngamma_e(x, &lgx);      int stat_gy  = gsl_sf_lngamma_e(y, &lgy);      int stat_gxy = gsl_sf_lngamma_e(x+y, &lgxy);      result->val  = lgx.val + lgy.val - lgxy.val;      result->err  = lgx.err + lgy.err + lgxy.err;      result->err += GSL_DBL_EPSILON * (fabs(lgx.val) + fabs(lgy.val) + fabs(lgxy.val));      result->err += 2.0 * GSL_DBL_EPSILON * fabs(result->val);      return GSL_ERROR_SELECT_3(stat_gx, stat_gy, stat_gxy);    }  }}intgsl_sf_beta_e(const double x, const double y, gsl_sf_result * result){  if(x < 50.0 && y < 50.0) {    gsl_sf_result gx, gy, gxy;    gsl_sf_gamma_e(x, &gx);    gsl_sf_gamma_e(y, &gy);    gsl_sf_gamma_e(x+y, &gxy);    result->val  = (gx.val*gy.val)/gxy.val;    result->err  = gx.err * gy.val/gxy.val;    result->err += gy.err * gx.val/gxy.val;    result->err += (gx.val*gy.val)/(gxy.val*gxy.val) * gxy.err;    result->err += 2.0 * GSL_DBL_EPSILON * fabs(result->val);    return GSL_SUCCESS;  }  else {    gsl_sf_result lb;    int stat_lb = gsl_sf_lnbeta_e(x, y, &lb);    if(stat_lb == GSL_SUCCESS) {      return gsl_sf_exp_err_e(lb.val, lb.err, result);    }    else {      result->val = 0.0;      result->err = 0.0;      return stat_lb;    }  }}/*-*-*-*-*-*-*-*-*-* Functions w/ Natural Prototypes *-*-*-*-*-*-*-*-*-*-*/#include "eval.h"double gsl_sf_lnbeta(const double x, const double y){  EVAL_RESULT(gsl_sf_lnbeta_e(x, y, &result));}double gsl_sf_beta(const double x, const double y){  EVAL_RESULT(gsl_sf_beta_e(x, y, &result));}

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