/* specfunc/legendre_H3d.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 3 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. */ /* Author: G. Jungman */ #include #include #include #include #include #include #include #include "error.h" #include "legendre.h" /* See [Abbott+Schaefer, Ap.J. 308, 546 (1986)] for * enough details to follow what is happening here. */ /* Logarithm of normalization factor, Log[N(ell,lambda)]. * N(ell,lambda) = Product[ lambda^2 + n^2, {n,0,ell} ] * = |Gamma(ell + 1 + I lambda)|^2 lambda sinh(Pi lambda) / Pi * Assumes ell >= 0. */ static int legendre_H3d_lnnorm(const int ell, const double lambda, double * result) { double abs_lam = fabs(lambda); if(abs_lam == 0.0) { *result = 0.0; GSL_ERROR ("error", GSL_EDOM); } else if(lambda > (ell + 1.0)/GSL_ROOT3_DBL_EPSILON) { /* There is a cancellation between the sinh(Pi lambda) * term and the log(gamma(ell + 1 + i lambda) in the * result below, so we show some care and save some digits. * Note that the above guarantees that lambda is large, * since ell >= 0. We use Stirling and a simple expansion * of sinh. */ double rat = (ell+1.0)/lambda; double ln_lam2ell2 = 2.0*log(lambda) + log(1.0 + rat*rat); double lg_corrected = -2.0*(ell+1.0) + M_LNPI + (ell+0.5)*ln_lam2ell2 + 1.0/(288.0*lambda*lambda); double angle_terms = lambda * 2.0 * rat * (1.0 - rat*rat/3.0); *result = log(abs_lam) + lg_corrected + angle_terms - M_LNPI; return GSL_SUCCESS; } else { gsl_sf_result lg_r; gsl_sf_result lg_theta; gsl_sf_result ln_sinh; gsl_sf_lngamma_complex_e(ell+1.0, lambda, &lg_r, &lg_theta); gsl_sf_lnsinh_e(M_PI * abs_lam, &ln_sinh); *result = log(abs_lam) + ln_sinh.val + 2.0*lg_r.val - M_LNPI; return GSL_SUCCESS; } } /* Calculate series for small eta*lambda. * Assumes eta > 0, lambda != 0. * * This is just the defining hypergeometric for the Legendre function. * * P^{mu}_{-1/2 + I lam}(z) = 1/Gamma(l+3/2) ((z+1)/(z-1)^(mu/2) * 2F1(1/2 - I lam, 1/2 + I lam; l+3/2; (1-z)/2) * We use * z = cosh(eta) * (z-1)/2 = sinh^2(eta/2) * * And recall * H3d = sqrt(Pi Norm /(2 lam^2 sinh(eta))) P^{-l-1/2}_{-1/2 + I lam}(cosh(eta)) */ static int legendre_H3d_series(const int ell, const double lambda, const double eta, gsl_sf_result * result) { const int nmax = 5000; const double shheta = sinh(0.5*eta); const double ln_zp1 = M_LN2 + log(1.0 + shheta*shheta); const double ln_zm1 = M_LN2 + 2.0*log(shheta); const double zeta = -shheta*shheta; gsl_sf_result lg_lp32; double term = 1.0; double sum = 1.0; double sum_err = 0.0; gsl_sf_result lnsheta; double lnN; double lnpre_val, lnpre_err, lnprepow; int stat_e; int n; gsl_sf_lngamma_e(ell + 3.0/2.0, &lg_lp32); gsl_sf_lnsinh_e(eta, &lnsheta); legendre_H3d_lnnorm(ell, lambda, &lnN); lnprepow = 0.5*(ell + 0.5) * (ln_zm1 - ln_zp1); lnpre_val = lnprepow + 0.5*(lnN + M_LNPI - M_LN2 - lnsheta.val) - lg_lp32.val - log(fabs(lambda)); lnpre_err = lnsheta.err + lg_lp32.err + GSL_DBL_EPSILON * fabs(lnpre_val); lnpre_err += 2.0*GSL_DBL_EPSILON * (fabs(lnN) + M_LNPI + M_LN2); lnpre_err += 2.0*GSL_DBL_EPSILON * (0.5*(ell + 0.5) * (fabs(ln_zm1) + fabs(ln_zp1))); for(n=1; n RECUR_BIG || fabs(Bn) > RECUR_BIG) { An /= RECUR_BIG; Bn /= RECUR_BIG; Anm1 /= RECUR_BIG; Bnm1 /= RECUR_BIG; Anm2 /= RECUR_BIG; Bnm2 /= RECUR_BIG; } old_fn = fn; fn = An/Bn; del = old_fn/fn; if(fabs(del - 1.0) < 4.0*GSL_DBL_EPSILON) break; } result->val = fn; result->err = 2.0 * GSL_DBL_EPSILON * (sqrt(n)+1.0) * fabs(fn); if(n >= maxiter) GSL_ERROR ("error", GSL_EMAXITER); else return GSL_SUCCESS; } #endif /* 0 */ /* Evaluate legendre_H3d(ell+1)/legendre_H3d(ell) * by continued fraction. Use the Gautschi (Euler) * equivalent series. */ /* FIXME: Maybe we have to worry about this. The a_k are * not positive and there can be a blow-up. It happened * for J_nu once or twice. Then we should probably use * the method above. */ static int legendre_H3d_CF1_ser(const int ell, const double lambda, const double coth_eta, gsl_sf_result * result) { const double pre = hypot(lambda, ell+1.0)/((2.0*ell+3)*coth_eta); const int maxk = 20000; double tk = 1.0; double sum = 1.0; double rhok = 0.0; double sum_err = 0.0; int k; for(k=1; kval = pre * sum; result->err = fabs(pre * tk); result->err += fabs(pre * sum_err); result->err += 4.0 * GSL_DBL_EPSILON * fabs(result->val); if(k >= maxk) GSL_ERROR ("error", GSL_EMAXITER); else return GSL_SUCCESS; } /*-*-*-*-*-*-*-*-*-*-*-* Functions with Error Codes *-*-*-*-*-*-*-*-*-*-*-*/ int gsl_sf_legendre_H3d_0_e(const double lambda, const double eta, gsl_sf_result * result) { /* CHECK_POINTER(result) */ if(eta < 0.0) { DOMAIN_ERROR(result); } else if(eta == 0.0 || lambda == 0.0) { result->val = 1.0; result->err = 0.0; return GSL_SUCCESS; } else { const double lam_eta = lambda * eta; gsl_sf_result s; gsl_sf_sin_err_e(lam_eta, 2.0*GSL_DBL_EPSILON * fabs(lam_eta), &s); if(eta > -0.5*GSL_LOG_DBL_EPSILON) { double f = 2.0 / lambda * exp(-eta); result->val = f * s.val; result->err = fabs(f * s.val) * (fabs(eta) + 1.0) * GSL_DBL_EPSILON; result->err += fabs(f) * s.err; result->err += 2.0 * GSL_DBL_EPSILON * fabs(result->val); } else { double f = 1.0/(lambda*sinh(eta)); result->val = f * s.val; result->err = fabs(f * s.val) * (fabs(eta) + 1.0) * GSL_DBL_EPSILON; result->err += fabs(f) * s.err; result->err += 2.0 * GSL_DBL_EPSILON * fabs(result->val); } return GSL_SUCCESS; } } int gsl_sf_legendre_H3d_1_e(const double lambda, const double eta, gsl_sf_result * result) { const double xi = fabs(eta*lambda); const double lsq = lambda*lambda; const double lsqp1 = lsq + 1.0; /* CHECK_POINTER(result) */ if(eta < 0.0) { DOMAIN_ERROR(result); } else if(eta == 0.0 || lambda == 0.0) { result->val = 0.0; result->err = 0.0; return GSL_SUCCESS; } else if(xi < GSL_ROOT5_DBL_EPSILON && eta < GSL_ROOT5_DBL_EPSILON) { double etasq = eta*eta; double xisq = xi*xi; double term1 = (etasq + xisq)/3.0; double term2 = -(2.0*etasq*etasq + 5.0*etasq*xisq + 3.0*xisq*xisq)/90.0; double sinh_term = 1.0 - eta*eta/6.0 * (1.0 - 7.0/60.0*eta*eta); double pre = sinh_term/sqrt(lsqp1) / eta; result->val = pre * (term1 + term2); result->err = pre * GSL_DBL_EPSILON * (fabs(term1) + fabs(term2)); result->err += 2.0 * GSL_DBL_EPSILON * fabs(result->val); return GSL_SUCCESS; } else { double sin_term; /* Sin(xi)/xi */ double cos_term; /* Cos(xi) */ double coth_term; /* eta/Tanh(eta) */ double sinh_term; /* eta/Sinh(eta) */ double sin_term_err; double cos_term_err; double t1; double pre_val; double pre_err; double term1; double term2; if(xi < GSL_ROOT5_DBL_EPSILON) { sin_term = 1.0 - xi*xi/6.0 * (1.0 - xi*xi/20.0); cos_term = 1.0 - 0.5*xi*xi * (1.0 - xi*xi/12.0); sin_term_err = GSL_DBL_EPSILON; cos_term_err = GSL_DBL_EPSILON; } else { gsl_sf_result sin_xi_result; gsl_sf_result cos_xi_result; gsl_sf_sin_e(xi, &sin_xi_result); gsl_sf_cos_e(xi, &cos_xi_result); sin_term = sin_xi_result.val/xi; cos_term = cos_xi_result.val; sin_term_err = sin_xi_result.err/fabs(xi); cos_term_err = cos_xi_result.err; } if(eta < GSL_ROOT5_DBL_EPSILON) { coth_term = 1.0 + eta*eta/3.0 * (1.0 - eta*eta/15.0); sinh_term = 1.0 - eta*eta/6.0 * (1.0 - 7.0/60.0*eta*eta); } else { coth_term = eta/tanh(eta); sinh_term = eta/sinh(eta); } t1 = sqrt(lsqp1) * eta; pre_val = sinh_term/t1; pre_err = 2.0 * GSL_DBL_EPSILON * fabs(pre_val); term1 = sin_term*coth_term; term2 = cos_term; result->val = pre_val * (term1 - term2); result->err = pre_err * fabs(term1 - term2); result->err += pre_val * (sin_term_err * coth_term + cos_term_err); result->err += pre_val * fabs(term1-term2) * (fabs(eta) + 1.0) * GSL_DBL_EPSILON; result->err += 2.0 * GSL_DBL_EPSILON * fabs(result->val); return GSL_SUCCESS; } } int gsl_sf_legendre_H3d_e(const int ell, const double lambda, const double eta, gsl_sf_result * result) { const double abs_lam = fabs(lambda); const double lsq = abs_lam*abs_lam; const double xi = abs_lam * eta; const double cosh_eta = cosh(eta); /* CHECK_POINTER(result) */ if(eta < 0.0) { DOMAIN_ERROR(result); } else if(eta > GSL_LOG_DBL_MAX) { /* cosh(eta) is too big. */ OVERFLOW_ERROR(result); } else if(ell == 0) { return gsl_sf_legendre_H3d_0_e(lambda, eta, result); } else if(ell == 1) { return gsl_sf_legendre_H3d_1_e(lambda, eta, result); } else if(eta == 0.0) { result->val = 0.0; result->err = 0.0; return GSL_SUCCESS; } else if(xi < 1.0) { return legendre_H3d_series(ell, lambda, eta, result); } else if((ell*ell+lsq)/sqrt(1.0+lsq)/(cosh_eta*cosh_eta) < 5.0*GSL_ROOT3_DBL_EPSILON) { /* Large argument. */ gsl_sf_result P; double lm; int stat_P = gsl_sf_conicalP_large_x_e(-ell-0.5, lambda, cosh_eta, &P, &lm); if(P.val == 0.0) { result->val = 0.0; result->err = 0.0; return stat_P; } else { double lnN; gsl_sf_result lnsh; double ln_abslam; double lnpre_val, lnpre_err; int stat_e; gsl_sf_lnsinh_e(eta, &lnsh); legendre_H3d_lnnorm(ell, lambda, &lnN); ln_abslam = log(abs_lam); lnpre_val = 0.5*(M_LNPI + lnN - M_LN2 - lnsh.val) - ln_abslam; lnpre_err = lnsh.err; lnpre_err += 2.0 * GSL_DBL_EPSILON * (0.5*(M_LNPI + M_LN2 + fabs(lnN)) + fabs(ln_abslam)); lnpre_err += 2.0 * GSL_DBL_EPSILON * fabs(lnpre_val); stat_e = gsl_sf_exp_mult_err_e(lnpre_val + lm, lnpre_err, P.val, P.err, result); return GSL_ERROR_SELECT_2(stat_e, stat_P); } } else if(abs_lam > 1000.0*ell*ell) { /* Large degree. */ gsl_sf_result P; double lm; int stat_P = gsl_sf_conicalP_xgt1_neg_mu_largetau_e(ell+0.5, lambda, cosh_eta, eta, &P, &lm); if(P.val == 0.0) { result->val = 0.0; result->err = 0.0; return stat_P; } else { double lnN; gsl_sf_result lnsh; double ln_abslam; double lnpre_val, lnpre_err; int stat_e; gsl_sf_lnsinh_e(eta, &lnsh); legendre_H3d_lnnorm(ell, lambda, &lnN); ln_abslam = log(abs_lam); lnpre_val = 0.5*(M_LNPI + lnN - M_LN2 - lnsh.val) - ln_abslam; lnpre_err = lnsh.err; lnpre_err += GSL_DBL_EPSILON * (0.5*(M_LNPI + M_LN2 + fabs(lnN)) + fabs(ln_abslam)); lnpre_err += 2.0 * GSL_DBL_EPSILON * fabs(lnpre_val); stat_e = gsl_sf_exp_mult_err_e(lnpre_val + lm, lnpre_err, P.val, P.err, result); return GSL_ERROR_SELECT_2(stat_e, stat_P); } } else { /* Backward recurrence. */ const double coth_eta = 1.0/tanh(eta); const double coth_err_mult = fabs(eta) + 1.0; gsl_sf_result rH; int stat_CF1 = legendre_H3d_CF1_ser(ell, lambda, coth_eta, &rH); double Hlm1; double Hl = GSL_SQRT_DBL_MIN; double Hlp1 = rH.val * Hl; int lp; for(lp=ell; lp>0; lp--) { double root_term_0 = hypot(lambda,lp); double root_term_1 = hypot(lambda,lp+1.0); Hlm1 = ((2.0*lp + 1.0)*coth_eta*Hl - root_term_1 * Hlp1)/root_term_0; Hlp1 = Hl; Hl = Hlm1; } if(fabs(Hl) > fabs(Hlp1)) { gsl_sf_result H0; int stat_H0 = gsl_sf_legendre_H3d_0_e(lambda, eta, &H0); result->val = GSL_SQRT_DBL_MIN/Hl * H0.val; result->err = GSL_SQRT_DBL_MIN/fabs(Hl) * H0.err; result->err += fabs(rH.err/rH.val) * (ell+1.0) * coth_err_mult * fabs(result->val); result->err += 2.0 * GSL_DBL_EPSILON * fabs(result->val); return GSL_ERROR_SELECT_2(stat_H0, stat_CF1); } else { gsl_sf_result H1; int stat_H1 = gsl_sf_legendre_H3d_1_e(lambda, eta, &H1); result->val = GSL_SQRT_DBL_MIN/Hlp1 * H1.val; result->err = GSL_SQRT_DBL_MIN/fabs(Hlp1) * H1.err; result->err += fabs(rH.err/rH.val) * (ell+1.0) * coth_err_mult * fabs(result->val); result->err += 2.0 * GSL_DBL_EPSILON * fabs(result->val); return GSL_ERROR_SELECT_2(stat_H1, stat_CF1); } } } int gsl_sf_legendre_H3d_array(const int lmax, const double lambda, const double eta, double * result_array) { /* CHECK_POINTER(result_array) */ if(eta < 0.0 || lmax < 0) { int ell; for(ell=0; ell<=lmax; ell++) result_array[ell] = 0.0; GSL_ERROR ("domain error", GSL_EDOM); } else if(eta > GSL_LOG_DBL_MAX) { /* cosh(eta) is too big. */ int ell; for(ell=0; ell<=lmax; ell++) result_array[ell] = 0.0; GSL_ERROR ("overflow", GSL_EOVRFLW); } else if(lmax == 0) { gsl_sf_result H0; int stat = gsl_sf_legendre_H3d_e(0, lambda, eta, &H0); result_array[0] = H0.val; return stat; } else { /* Not the most efficient method. But what the hell... it's simple. */ gsl_sf_result r_Hlp1; gsl_sf_result r_Hl; int stat_lmax = gsl_sf_legendre_H3d_e(lmax, lambda, eta, &r_Hlp1); int stat_lmaxm1 = gsl_sf_legendre_H3d_e(lmax-1, lambda, eta, &r_Hl); int stat_max = GSL_ERROR_SELECT_2(stat_lmax, stat_lmaxm1); const double coth_eta = 1.0/tanh(eta); int stat_recursion = GSL_SUCCESS; double Hlp1 = r_Hlp1.val; double Hl = r_Hl.val; double Hlm1; int ell; result_array[lmax] = Hlp1; result_array[lmax-1] = Hl; for(ell=lmax-1; ell>0; ell--) { double root_term_0 = hypot(lambda,ell); double root_term_1 = hypot(lambda,ell+1.0); Hlm1 = ((2.0*ell + 1.0)*coth_eta*Hl - root_term_1 * Hlp1)/root_term_0; result_array[ell-1] = Hlm1; if(!(Hlm1 < GSL_DBL_MAX)) stat_recursion = GSL_EOVRFLW; Hlp1 = Hl; Hl = Hlm1; } return GSL_ERROR_SELECT_2(stat_recursion, stat_max); } } /*-*-*-*-*-*-*-*-*-* Functions w/ Natural Prototypes *-*-*-*-*-*-*-*-*-*-*/ #include "eval.h" double gsl_sf_legendre_H3d_0(const double lambda, const double eta) { EVAL_RESULT(gsl_sf_legendre_H3d_0_e(lambda, eta, &result)); } double gsl_sf_legendre_H3d_1(const double lambda, const double eta) { EVAL_RESULT(gsl_sf_legendre_H3d_1_e(lambda, eta, &result)); } double gsl_sf_legendre_H3d(const int l, const double lambda, const double eta) { EVAL_RESULT(gsl_sf_legendre_H3d_e(l, lambda, eta, &result)); }