/* specfunc/legendre_poly.c * * Copyright (C) 1996, 1997, 1998, 1999, 2000, 2001, 2002 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 #include #include "error.h" /* Calculate P_m^m(x) from the analytic result: * P_m^m(x) = (-1)^m (2m-1)!! (1-x^2)^(m/2) , m > 0 * = 1 , m = 0 */ static double legendre_Pmm(int m, double x) { if(m == 0) { return 1.0; } else { double p_mm = 1.0; double root_factor = sqrt(1.0-x)*sqrt(1.0+x); double fact_coeff = 1.0; int i; for(i=1; i<=m; i++) { p_mm *= -fact_coeff * root_factor; fact_coeff += 2.0; } return p_mm; } } /*-*-*-*-*-*-*-*-*-*-*-* Functions with Error Codes *-*-*-*-*-*-*-*-*-*-*-*/ int gsl_sf_legendre_P1_e(double x, gsl_sf_result * result) { /* CHECK_POINTER(result) */ { result->val = x; result->err = 0.0; return GSL_SUCCESS; } } int gsl_sf_legendre_P2_e(double x, gsl_sf_result * result) { /* CHECK_POINTER(result) */ { result->val = 0.5*(3.0*x*x - 1.0); result->err = GSL_DBL_EPSILON * (fabs(3.0*x*x) + 1.0); return GSL_SUCCESS; } } int gsl_sf_legendre_P3_e(double x, gsl_sf_result * result) { /* CHECK_POINTER(result) */ { result->val = 0.5*x*(5.0*x*x - 3.0); result->err = GSL_DBL_EPSILON * (fabs(result->val) + 0.5 * fabs(x) * (fabs(5.0*x*x) + 3.0)); return GSL_SUCCESS; } } int gsl_sf_legendre_Pl_e(const int l, const double x, gsl_sf_result * result) { /* CHECK_POINTER(result) */ if(l < 0 || x < -1.0 || x > 1.0) { DOMAIN_ERROR(result); } else if(l == 0) { result->val = 1.0; result->err = 0.0; return GSL_SUCCESS; } else if(l == 1) { result->val = x; result->err = 0.0; return GSL_SUCCESS; } else if(l == 2) { result->val = 0.5 * (3.0*x*x - 1.0); result->err = GSL_DBL_EPSILON * (fabs(3.0*x*x) + 1.0); /*result->err = 3.0 * GSL_DBL_EPSILON * fabs(result->val); removed this old bogus estimate [GJ] */ return GSL_SUCCESS; } else if(x == 1.0) { result->val = 1.0; result->err = 0.0; return GSL_SUCCESS; } else if(x == -1.0) { result->val = ( GSL_IS_ODD(l) ? -1.0 : 1.0 ); result->err = 0.0; return GSL_SUCCESS; } else if(l < 100000) { /* upward recurrence: l P_l = (2l-1) z P_{l-1} - (l-1) P_{l-2} */ double p_ellm2 = 1.0; /* P_0(x) */ double p_ellm1 = x; /* P_1(x) */ double p_ell = p_ellm1; double e_ellm2 = GSL_DBL_EPSILON; double e_ellm1 = fabs(x)*GSL_DBL_EPSILON; double e_ell = e_ellm1; int ell; for(ell=2; ell <= l; ell++){ p_ell = (x*(2*ell-1)*p_ellm1 - (ell-1)*p_ellm2) / ell; p_ellm2 = p_ellm1; p_ellm1 = p_ell; e_ell = 0.5*(fabs(x)*(2*ell-1.0) * e_ellm1 + (ell-1.0)*e_ellm2)/ell; e_ellm2 = e_ellm1; e_ellm1 = e_ell; } result->val = p_ell; result->err = e_ell + l*fabs(p_ell)*GSL_DBL_EPSILON; return GSL_SUCCESS; } else { /* Asymptotic expansion. * [Olver, p. 473] */ double u = l + 0.5; double th = acos(x); gsl_sf_result J0; gsl_sf_result Jm1; int stat_J0 = gsl_sf_bessel_J0_e(u*th, &J0); int stat_Jm1 = gsl_sf_bessel_Jn_e(-1, u*th, &Jm1); double pre; double B00; double c1; /* B00 = 1/8 (1 - th cot(th) / th^2 * pre = sqrt(th/sin(th)) */ if(th < GSL_ROOT4_DBL_EPSILON) { B00 = (1.0 + th*th/15.0)/24.0; pre = 1.0 + th*th/12.0; } else { double sin_th = sqrt(1.0 - x*x); double cot_th = x / sin_th; B00 = 1.0/8.0 * (1.0 - th * cot_th) / (th*th); pre = sqrt(th/sin_th); } c1 = th/u * B00; result->val = pre * (J0.val + c1 * Jm1.val); result->err = pre * (J0.err + fabs(c1) * Jm1.err); result->err += GSL_SQRT_DBL_EPSILON * fabs(result->val); return GSL_ERROR_SELECT_2(stat_J0, stat_Jm1); } } int gsl_sf_legendre_Pl_array(const int lmax, const double x, double * result_array) { /* CHECK_POINTER(result_array) */ if(lmax < 0 || x < -1.0 || x > 1.0) { GSL_ERROR ("domain error", GSL_EDOM); } else if(lmax == 0) { result_array[0] = 1.0; return GSL_SUCCESS; } else if(lmax == 1) { result_array[0] = 1.0; result_array[1] = x; return GSL_SUCCESS; } else { /* upward recurrence: l P_l = (2l-1) z P_{l-1} - (l-1) P_{l-2} */ double p_ellm2 = 1.0; /* P_0(x) */ double p_ellm1 = x; /* P_1(x) */ double p_ell = p_ellm1; int ell; result_array[0] = 1.0; result_array[1] = x; for(ell=2; ell <= lmax; ell++){ p_ell = (x*(2*ell-1)*p_ellm1 - (ell-1)*p_ellm2) / ell; p_ellm2 = p_ellm1; p_ellm1 = p_ell; result_array[ell] = p_ell; } return GSL_SUCCESS; } } int gsl_sf_legendre_Pl_deriv_array(const int lmax, const double x, double * result_array, double * result_deriv_array) { int stat_array = gsl_sf_legendre_Pl_array(lmax, x, result_array); if(lmax >= 0) result_deriv_array[0] = 0.0; if(lmax >= 1) result_deriv_array[1] = 1.0; if(stat_array == GSL_SUCCESS) { int ell; if(fabs(x - 1.0)*(lmax+1.0)*(lmax+1.0) < GSL_SQRT_DBL_EPSILON) { /* x is near 1 */ for(ell = 2; ell <= lmax; ell++) { const double pre = 0.5 * ell * (ell+1.0); result_deriv_array[ell] = pre * (1.0 - 0.25 * (1.0-x) * (ell+2.0)*(ell-1.0)); } } else if(fabs(x + 1.0)*(lmax+1.0)*(lmax+1.0) < GSL_SQRT_DBL_EPSILON) { /* x is near -1 */ for(ell = 2; ell <= lmax; ell++) { const double sgn = ( GSL_IS_ODD(ell) ? 1.0 : -1.0 ); /* derivative is odd in x for even ell */ const double pre = sgn * 0.5 * ell * (ell+1.0); result_deriv_array[ell] = pre * (1.0 - 0.25 * (1.0+x) * (ell+2.0)*(ell-1.0)); } } else { const double diff_a = 1.0 + x; const double diff_b = 1.0 - x; for(ell = 2; ell <= lmax; ell++) { result_deriv_array[ell] = - ell * (x * result_array[ell] - result_array[ell-1]) / (diff_a * diff_b); } } return GSL_SUCCESS; } else { return stat_array; } } int gsl_sf_legendre_Plm_e(const int l, const int m, const double x, gsl_sf_result * result) { /* If l is large and m is large, then we have to worry * about overflow. Calculate an approximate exponent which * measures the normalization of this thing. */ const double dif = l-m; const double sum = l+m; const double t_d = ( dif == 0.0 ? 0.0 : 0.5 * dif * (log(dif)-1.0) ); const double t_s = ( dif == 0.0 ? 0.0 : 0.5 * sum * (log(sum)-1.0) ); const double exp_check = 0.5 * log(2.0*l+1.0) + t_d - t_s; /* CHECK_POINTER(result) */ if(m < 0 || l < m || x < -1.0 || x > 1.0) { DOMAIN_ERROR(result); } else if(exp_check < GSL_LOG_DBL_MIN + 10.0){ /* Bail out. */ OVERFLOW_ERROR(result); } else { /* Account for the error due to the * representation of 1-x. */ const double err_amp = 1.0 / (GSL_DBL_EPSILON + fabs(1.0-fabs(x))); /* P_m^m(x) and P_{m+1}^m(x) */ double p_mm = legendre_Pmm(m, x); double p_mmp1 = x * (2*m + 1) * p_mm; if(l == m){ result->val = p_mm; result->err = err_amp * 2.0 * GSL_DBL_EPSILON * fabs(p_mm); return GSL_SUCCESS; } else if(l == m + 1) { result->val = p_mmp1; result->err = err_amp * 2.0 * GSL_DBL_EPSILON * fabs(p_mmp1); return GSL_SUCCESS; } else{ /* upward recurrence: (l-m) P(l,m) = (2l-1) z P(l-1,m) - (l+m-1) P(l-2,m) * start at P(m,m), P(m+1,m) */ double p_ellm2 = p_mm; double p_ellm1 = p_mmp1; double p_ell = 0.0; int ell; for(ell=m+2; ell <= l; ell++){ p_ell = (x*(2*ell-1)*p_ellm1 - (ell+m-1)*p_ellm2) / (ell-m); p_ellm2 = p_ellm1; p_ellm1 = p_ell; } result->val = p_ell; result->err = err_amp * (0.5*(l-m) + 1.0) * GSL_DBL_EPSILON * fabs(p_ell); return GSL_SUCCESS; } } } int gsl_sf_legendre_sphPlm_e(const int l, int m, const double x, gsl_sf_result * result) { /* CHECK_POINTER(result) */ if(m < 0 || l < m || x < -1.0 || x > 1.0) { DOMAIN_ERROR(result); } else if(m == 0) { gsl_sf_result P; int stat_P = gsl_sf_legendre_Pl_e(l, x, &P); double pre = sqrt((2.0*l + 1.0)/(4.0*M_PI)); result->val = pre * P.val; result->err = pre * P.err; result->err += 2.0 * GSL_DBL_EPSILON * fabs(result->val); return stat_P; } else if(x == 1.0 || x == -1.0) { /* m > 0 here */ result->val = 0.0; result->err = 0.0; return GSL_SUCCESS; } else { /* m > 0 and |x| < 1 here */ /* Starting value for recursion. * Y_m^m(x) = sqrt( (2m+1)/(4pi m) gamma(m+1/2)/gamma(m) ) (-1)^m (1-x^2)^(m/2) / pi^(1/4) */ gsl_sf_result lncirc; gsl_sf_result lnpoch; double lnpre_val; double lnpre_err; gsl_sf_result ex_pre; double sr; const double sgn = ( GSL_IS_ODD(m) ? -1.0 : 1.0); const double y_mmp1_factor = x * sqrt(2.0*m + 3.0); double y_mm, y_mm_err; double y_mmp1, y_mmp1_err; gsl_sf_log_1plusx_e(-x*x, &lncirc); gsl_sf_lnpoch_e(m, 0.5, &lnpoch); /* Gamma(m+1/2)/Gamma(m) */ lnpre_val = -0.25*M_LNPI + 0.5 * (lnpoch.val + m*lncirc.val); lnpre_err = 0.25*M_LNPI*GSL_DBL_EPSILON + 0.5 * (lnpoch.err + fabs(m)*lncirc.err); /* Compute exp(ln_pre) with error term, avoiding call to gsl_sf_exp_err BJG */ ex_pre.val = exp(lnpre_val); ex_pre.err = 2.0*(sinh(lnpre_err) + GSL_DBL_EPSILON)*ex_pre.val; sr = sqrt((2.0+1.0/m)/(4.0*M_PI)); y_mm = sgn * sr * ex_pre.val; y_mm_err = 2.0 * GSL_DBL_EPSILON * fabs(y_mm) + sr * ex_pre.err; y_mm_err *= 1.0 + 1.0/(GSL_DBL_EPSILON + fabs(1.0-x)); y_mmp1 = y_mmp1_factor * y_mm; y_mmp1_err=fabs(y_mmp1_factor) * y_mm_err; if(l == m){ result->val = y_mm; result->err = y_mm_err; result->err += 2.0 * GSL_DBL_EPSILON * fabs(y_mm); return GSL_SUCCESS; } else if(l == m + 1) { result->val = y_mmp1; result->err = y_mmp1_err; result->err += 2.0 * GSL_DBL_EPSILON * fabs(y_mmp1); return GSL_SUCCESS; } else{ double y_ell = 0.0; double y_ell_err = 0.0; int ell; /* Compute Y_l^m, l > m+1, upward recursion on l. */ for(ell=m+2; ell <= l; ell++){ const double rat1 = (double)(ell-m)/(double)(ell+m); const double rat2 = (ell-m-1.0)/(ell+m-1.0); const double factor1 = sqrt(rat1*(2.0*ell+1.0)*(2.0*ell-1.0)); const double factor2 = sqrt(rat1*rat2*(2.0*ell+1.0)/(2.0*ell-3.0)); y_ell = (x*y_mmp1*factor1 - (ell+m-1.0)*y_mm*factor2) / (ell-m); y_mm = y_mmp1; y_mmp1 = y_ell; y_ell_err = 0.5*(fabs(x*factor1)*y_mmp1_err + fabs((ell+m-1.0)*factor2)*y_mm_err) / fabs(ell-m); y_mm_err = y_mmp1_err; y_mmp1_err = y_ell_err; } result->val = y_ell; result->err = y_ell_err + (0.5*(l-m) + 1.0) * GSL_DBL_EPSILON * fabs(y_ell); return GSL_SUCCESS; } } } #ifndef GSL_DISABLE_DEPRECATED int gsl_sf_legendre_Plm_array(const int lmax, const int m, const double x, double * result_array) { /* If l is large and m is large, then we have to worry * about overflow. Calculate an approximate exponent which * measures the normalization of this thing. */ const double dif = lmax-m; const double sum = lmax+m; const double t_d = ( dif == 0.0 ? 0.0 : 0.5 * dif * (log(dif)-1.0) ); const double t_s = ( dif == 0.0 ? 0.0 : 0.5 * sum * (log(sum)-1.0) ); const double exp_check = 0.5 * log(2.0*lmax+1.0) + t_d - t_s; /* CHECK_POINTER(result_array) */ if(m < 0 || lmax < m || x < -1.0 || x > 1.0) { GSL_ERROR ("domain error", GSL_EDOM); } else if(m > 0 && (x == 1.0 || x == -1.0)) { int ell; for(ell=m; ell<=lmax; ell++) result_array[ell-m] = 0.0; return GSL_SUCCESS; } else if(exp_check < GSL_LOG_DBL_MIN + 10.0){ /* Bail out. */ GSL_ERROR ("overflow", GSL_EOVRFLW); } else { double p_mm = legendre_Pmm(m, x); double p_mmp1 = x * (2.0*m + 1.0) * p_mm; if(lmax == m){ result_array[0] = p_mm; return GSL_SUCCESS; } else if(lmax == m + 1) { result_array[0] = p_mm; result_array[1] = p_mmp1; return GSL_SUCCESS; } else { double p_ellm2 = p_mm; double p_ellm1 = p_mmp1; double p_ell = 0.0; int ell; result_array[0] = p_mm; result_array[1] = p_mmp1; for(ell=m+2; ell <= lmax; ell++){ p_ell = (x*(2.0*ell-1.0)*p_ellm1 - (ell+m-1)*p_ellm2) / (ell-m); p_ellm2 = p_ellm1; p_ellm1 = p_ell; result_array[ell-m] = p_ell; } return GSL_SUCCESS; } } } int gsl_sf_legendre_Plm_deriv_array( const int lmax, const int m, const double x, double * result_array, double * result_deriv_array) { if(m < 0 || m > lmax) { GSL_ERROR("m < 0 or m > lmax", GSL_EDOM); } else if(m == 0) { /* It is better to do m=0 this way, so we can more easily * trap the divergent case which can occur when m == 1. */ return gsl_sf_legendre_Pl_deriv_array(lmax, x, result_array, result_deriv_array); } else { int stat_array = gsl_sf_legendre_Plm_array(lmax, m, x, result_array); if(stat_array == GSL_SUCCESS) { int ell; if(m == 1 && (1.0 - fabs(x) < GSL_DBL_EPSILON)) { /* This divergence is real and comes from the cusp-like * behaviour for m = 1. For example, P[1,1] = - Sqrt[1-x^2]. */ GSL_ERROR("divergence near |x| = 1.0 since m = 1", GSL_EOVRFLW); } else if(m == 2 && (1.0 - fabs(x) < GSL_DBL_EPSILON)) { /* m = 2 gives a finite nonzero result for |x| near 1 */ if(fabs(x - 1.0) < GSL_DBL_EPSILON) { for(ell = m; ell <= lmax; ell++) result_deriv_array[ell-m] = -0.25 * x * (ell - 1.0)*ell*(ell+1.0)*(ell+2.0); } else if(fabs(x + 1.0) < GSL_DBL_EPSILON) { for(ell = m; ell <= lmax; ell++) { const double sgn = ( GSL_IS_ODD(ell) ? 1.0 : -1.0 ); result_deriv_array[ell-m] = -0.25 * sgn * x * (ell - 1.0)*ell*(ell+1.0)*(ell+2.0); } } return GSL_SUCCESS; } else { /* m > 2 is easier to deal with since the endpoints always vanish */ if(1.0 - fabs(x) < GSL_DBL_EPSILON) { for(ell = m; ell <= lmax; ell++) result_deriv_array[ell-m] = 0.0; return GSL_SUCCESS; } else { const double diff_a = 1.0 + x; const double diff_b = 1.0 - x; result_deriv_array[0] = - m * x / (diff_a * diff_b) * result_array[0]; if(lmax-m >= 1) result_deriv_array[1] = (2.0 * m + 1.0) * (x * result_deriv_array[0] + result_array[0]); for(ell = m+2; ell <= lmax; ell++) { result_deriv_array[ell-m] = - (ell * x * result_array[ell-m] - (ell+m) * result_array[ell-1-m]) / (diff_a * diff_b); } return GSL_SUCCESS; } } } else { return stat_array; } } } int gsl_sf_legendre_sphPlm_array(const int lmax, int m, const double x, double * result_array) { /* CHECK_POINTER(result_array) */ if(m < 0 || lmax < m || x < -1.0 || x > 1.0) { GSL_ERROR ("error", GSL_EDOM); } else if(m > 0 && (x == 1.0 || x == -1.0)) { int ell; for(ell=m; ell<=lmax; ell++) result_array[ell-m] = 0.0; return GSL_SUCCESS; } else { double y_mm; double y_mmp1; if(m == 0) { y_mm = 0.5/M_SQRTPI; /* Y00 = 1/sqrt(4pi) */ y_mmp1 = x * M_SQRT3 * y_mm; } else { /* |x| < 1 here */ gsl_sf_result lncirc; gsl_sf_result lnpoch; double lnpre; const double sgn = ( GSL_IS_ODD(m) ? -1.0 : 1.0); gsl_sf_log_1plusx_e(-x*x, &lncirc); gsl_sf_lnpoch_e(m, 0.5, &lnpoch); /* Gamma(m+1/2)/Gamma(m) */ lnpre = -0.25*M_LNPI + 0.5 * (lnpoch.val + m*lncirc.val); y_mm = sqrt((2.0+1.0/m)/(4.0*M_PI)) * sgn * exp(lnpre); y_mmp1 = x * sqrt(2.0*m + 3.0) * y_mm; } if(lmax == m){ result_array[0] = y_mm; return GSL_SUCCESS; } else if(lmax == m + 1) { result_array[0] = y_mm; result_array[1] = y_mmp1; return GSL_SUCCESS; } else{ double y_ell; int ell; result_array[0] = y_mm; result_array[1] = y_mmp1; /* Compute Y_l^m, l > m+1, upward recursion on l. */ for(ell=m+2; ell <= lmax; ell++){ const double rat1 = (double)(ell-m)/(double)(ell+m); const double rat2 = (ell-m-1.0)/(ell+m-1.0); const double factor1 = sqrt(rat1*(2*ell+1)*(2*ell-1)); const double factor2 = sqrt(rat1*rat2*(2*ell+1)/(2*ell-3)); y_ell = (x*y_mmp1*factor1 - (ell+m-1)*y_mm*factor2) / (ell-m); y_mm = y_mmp1; y_mmp1 = y_ell; result_array[ell-m] = y_ell; } } return GSL_SUCCESS; } } int gsl_sf_legendre_sphPlm_deriv_array( const int lmax, const int m, const double x, double * result_array, double * result_deriv_array) { if(m < 0 || lmax < m || x < -1.0 || x > 1.0) { GSL_ERROR ("domain", GSL_EDOM); } else if(m == 0) { /* m = 0 is easy to trap */ const int stat_array = gsl_sf_legendre_Pl_deriv_array(lmax, x, result_array, result_deriv_array); int ell; for(ell = 0; ell <= lmax; ell++) { const double prefactor = sqrt((2.0 * ell + 1.0)/(4.0*M_PI)); result_array[ell] *= prefactor; result_deriv_array[ell] *= prefactor; } return stat_array; } else if(m == 1) { /* Trapping m = 1 is necessary because of the possible divergence. * Recall that this divergence is handled properly in ..._Plm_deriv_array(), * and the scaling factor is not large for small m, so we just scale. */ const int stat_array = gsl_sf_legendre_Plm_deriv_array(lmax, m, x, result_array, result_deriv_array); int ell; for(ell = 1; ell <= lmax; ell++) { const double prefactor = sqrt((2.0 * ell + 1.0)/(ell + 1.0) / (4.0*M_PI*ell)); result_array[ell-1] *= prefactor; result_deriv_array[ell-1] *= prefactor; } return stat_array; } else { /* as for the derivative of P_lm, everything is regular for m >= 2 */ int stat_array = gsl_sf_legendre_sphPlm_array(lmax, m, x, result_array); if(stat_array == GSL_SUCCESS) { int ell; if(1.0 - fabs(x) < GSL_DBL_EPSILON) { for(ell = m; ell <= lmax; ell++) result_deriv_array[ell-m] = 0.0; return GSL_SUCCESS; } else { const double diff_a = 1.0 + x; const double diff_b = 1.0 - x; result_deriv_array[0] = - m * x / (diff_a * diff_b) * result_array[0]; if(lmax-m >= 1) result_deriv_array[1] = sqrt(2.0 * m + 3.0) * (x * result_deriv_array[0] + result_array[0]); for(ell = m+2; ell <= lmax; ell++) { const double c1 = sqrt(((2.0*ell+1.0)/(2.0*ell-1.0)) * ((double)(ell-m)/(double)(ell+m))); result_deriv_array[ell-m] = - (ell * x * result_array[ell-m] - c1 * (ell+m) * result_array[ell-1-m]) / (diff_a * diff_b); } return GSL_SUCCESS; } } else { return stat_array; } } } int gsl_sf_legendre_array_size(const int lmax, const int m) { return lmax-m+1; } #endif /* !GSL_DISABLE_DEPRECATED */ /*-*-*-*-*-*-*-*-*-* Functions w/ Natural Prototypes *-*-*-*-*-*-*-*-*-*-*/ #include "eval.h" double gsl_sf_legendre_P1(const double x) { EVAL_RESULT(gsl_sf_legendre_P1_e(x, &result)); } double gsl_sf_legendre_P2(const double x) { EVAL_RESULT(gsl_sf_legendre_P2_e(x, &result)); } double gsl_sf_legendre_P3(const double x) { EVAL_RESULT(gsl_sf_legendre_P3_e(x, &result)); } double gsl_sf_legendre_Pl(const int l, const double x) { EVAL_RESULT(gsl_sf_legendre_Pl_e(l, x, &result)); } double gsl_sf_legendre_Plm(const int l, const int m, const double x) { EVAL_RESULT(gsl_sf_legendre_Plm_e(l, m, x, &result)); } double gsl_sf_legendre_sphPlm(const int l, const int m, const double x) { EVAL_RESULT(gsl_sf_legendre_sphPlm_e(l, m, x, &result)); }