// Copyright John Maddock 2008. // Use, modification and distribution are subject to the // Boost Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) // // Wrapper that works with mpfr::mpreal defined in gmpfrxx.h // See http://math.berkeley.edu/~wilken/code/gmpfrxx/ // Also requires the gmp and mpfr libraries. // #ifndef BOOST_MATH_MPREAL_BINDINGS_HPP #define BOOST_MATH_MPREAL_BINDINGS_HPP #include #include #ifdef BOOST_MSVC // // We get a lot of warnings from the gmp, mpfr and gmpfrxx headers, // disable them here, so we only see warnings from *our* code: // #pragma warning(push) #pragma warning(disable: 4127 4800 4512) #endif #include #ifdef BOOST_MSVC #pragma warning(pop) #endif #include #include #include #include #include #include #include namespace mpfr{ template inline mpreal operator + (const mpreal& r, const T& t){ return r + mpreal(t); } template inline mpreal operator - (const mpreal& r, const T& t){ return r - mpreal(t); } template inline mpreal operator * (const mpreal& r, const T& t){ return r * mpreal(t); } template inline mpreal operator / (const mpreal& r, const T& t){ return r / mpreal(t); } template inline mpreal operator + (const T& t, const mpreal& r){ return mpreal(t) + r; } template inline mpreal operator - (const T& t, const mpreal& r){ return mpreal(t) - r; } template inline mpreal operator * (const T& t, const mpreal& r){ return mpreal(t) * r; } template inline mpreal operator / (const T& t, const mpreal& r){ return mpreal(t) / r; } template inline bool operator == (const mpreal& r, const T& t){ return r == mpreal(t); } template inline bool operator != (const mpreal& r, const T& t){ return r != mpreal(t); } template inline bool operator <= (const mpreal& r, const T& t){ return r <= mpreal(t); } template inline bool operator >= (const mpreal& r, const T& t){ return r >= mpreal(t); } template inline bool operator < (const mpreal& r, const T& t){ return r < mpreal(t); } template inline bool operator > (const mpreal& r, const T& t){ return r > mpreal(t); } template inline bool operator == (const T& t, const mpreal& r){ return mpreal(t) == r; } template inline bool operator != (const T& t, const mpreal& r){ return mpreal(t) != r; } template inline bool operator <= (const T& t, const mpreal& r){ return mpreal(t) <= r; } template inline bool operator >= (const T& t, const mpreal& r){ return mpreal(t) >= r; } template inline bool operator < (const T& t, const mpreal& r){ return mpreal(t) < r; } template inline bool operator > (const T& t, const mpreal& r){ return mpreal(t) > r; } /* inline mpfr::mpreal fabs(const mpfr::mpreal& v) { return abs(v); } inline mpfr::mpreal pow(const mpfr::mpreal& b, const mpfr::mpreal e) { mpfr::mpreal result; mpfr_pow(result.__get_mp(), b.__get_mp(), e.__get_mp(), GMP_RNDN); return result; } */ inline mpfr::mpreal ldexp(const mpfr::mpreal& v, int e) { return mpfr::ldexp(v, static_cast(e)); } inline mpfr::mpreal frexp(const mpfr::mpreal& v, int* expon) { mp_exp_t e; mpfr::mpreal r = mpfr::frexp(v, &e); *expon = e; return r; } #if (MPFR_VERSION < MPFR_VERSION_NUM(2,4,0)) mpfr::mpreal fmod(const mpfr::mpreal& v1, const mpfr::mpreal& v2) { mpfr::mpreal n; if(v1 < 0) n = ceil(v1 / v2); else n = floor(v1 / v2); return v1 - n * v2; } #endif template inline mpfr::mpreal modf(const mpfr::mpreal& v, long long* ipart, const Policy& pol) { *ipart = lltrunc(v, pol); return v - boost::math::tools::real_cast(*ipart); } template inline int iround(mpfr::mpreal const& x, const Policy& pol) { return boost::math::tools::real_cast(boost::math::round(x, pol)); } template inline long lround(mpfr::mpreal const& x, const Policy& pol) { return boost::math::tools::real_cast(boost::math::round(x, pol)); } template inline long long llround(mpfr::mpreal const& x, const Policy& pol) { return boost::math::tools::real_cast(boost::math::round(x, pol)); } template inline int itrunc(mpfr::mpreal const& x, const Policy& pol) { return boost::math::tools::real_cast(boost::math::trunc(x, pol)); } template inline long ltrunc(mpfr::mpreal const& x, const Policy& pol) { return boost::math::tools::real_cast(boost::math::trunc(x, pol)); } template inline long long lltrunc(mpfr::mpreal const& x, const Policy& pol) { return boost::math::tools::real_cast(boost::math::trunc(x, pol)); } } namespace boost{ namespace math{ #if defined(__GNUC__) && (__GNUC__ < 4) using ::iround; using ::lround; using ::llround; using ::itrunc; using ::ltrunc; using ::lltrunc; using ::modf; #endif namespace lanczos{ struct mpreal_lanczos { static mpfr::mpreal lanczos_sum(const mpfr::mpreal& z) { unsigned long p = z.get_default_prec(); if(p <= 72) return lanczos13UDT::lanczos_sum(z); else if(p <= 120) return lanczos22UDT::lanczos_sum(z); else if(p <= 170) return lanczos31UDT::lanczos_sum(z); else //if(p <= 370) approx 100 digit precision: return lanczos61UDT::lanczos_sum(z); } static mpfr::mpreal lanczos_sum_expG_scaled(const mpfr::mpreal& z) { unsigned long p = z.get_default_prec(); if(p <= 72) return lanczos13UDT::lanczos_sum_expG_scaled(z); else if(p <= 120) return lanczos22UDT::lanczos_sum_expG_scaled(z); else if(p <= 170) return lanczos31UDT::lanczos_sum_expG_scaled(z); else //if(p <= 370) approx 100 digit precision: return lanczos61UDT::lanczos_sum_expG_scaled(z); } static mpfr::mpreal lanczos_sum_near_1(const mpfr::mpreal& z) { unsigned long p = z.get_default_prec(); if(p <= 72) return lanczos13UDT::lanczos_sum_near_1(z); else if(p <= 120) return lanczos22UDT::lanczos_sum_near_1(z); else if(p <= 170) return lanczos31UDT::lanczos_sum_near_1(z); else //if(p <= 370) approx 100 digit precision: return lanczos61UDT::lanczos_sum_near_1(z); } static mpfr::mpreal lanczos_sum_near_2(const mpfr::mpreal& z) { unsigned long p = z.get_default_prec(); if(p <= 72) return lanczos13UDT::lanczos_sum_near_2(z); else if(p <= 120) return lanczos22UDT::lanczos_sum_near_2(z); else if(p <= 170) return lanczos31UDT::lanczos_sum_near_2(z); else //if(p <= 370) approx 100 digit precision: return lanczos61UDT::lanczos_sum_near_2(z); } static mpfr::mpreal g() { unsigned long p = mpfr::mpreal::get_default_prec(); if(p <= 72) return lanczos13UDT::g(); else if(p <= 120) return lanczos22UDT::g(); else if(p <= 170) return lanczos31UDT::g(); else //if(p <= 370) approx 100 digit precision: return lanczos61UDT::g(); } }; template struct lanczos { typedef mpreal_lanczos type; }; } // namespace lanczos namespace tools { template<> inline int digits(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr::mpreal)) { return mpfr::mpreal::get_default_prec(); } namespace detail{ template void convert_to_long_result(mpfr::mpreal const& r, I& result) { result = 0; I last_result(0); mpfr::mpreal t(r); double term; do { term = real_cast(t); last_result = result; result += static_cast(term); t -= term; }while(result != last_result); } } template <> inline mpfr::mpreal real_cast(long long t) { mpfr::mpreal result; int expon = 0; int sign = 1; if(t < 0) { sign = -1; t = -t; } while(t) { result += ldexp((double)(t & 0xffffL), expon); expon += 32; t >>= 32; } return result * sign; } /* template <> inline unsigned real_cast(mpfr::mpreal t) { return t.get_ui(); } template <> inline int real_cast(mpfr::mpreal t) { return t.get_si(); } template <> inline double real_cast(mpfr::mpreal t) { return t.get_d(); } template <> inline float real_cast(mpfr::mpreal t) { return static_cast(t.get_d()); } template <> inline long real_cast(mpfr::mpreal t) { long result; detail::convert_to_long_result(t, result); return result; } */ template <> inline long long real_cast(mpfr::mpreal t) { long long result; detail::convert_to_long_result(t, result); return result; } template <> inline mpfr::mpreal max_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr::mpreal)) { static bool has_init = false; static mpfr::mpreal val(0.5); if(!has_init) { val = ldexp(val, mpfr_get_emax()); has_init = true; } return val; } template <> inline mpfr::mpreal min_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr::mpreal)) { static bool has_init = false; static mpfr::mpreal val(0.5); if(!has_init) { val = ldexp(val, mpfr_get_emin()); has_init = true; } return val; } template <> inline mpfr::mpreal log_max_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr::mpreal)) { static bool has_init = false; static mpfr::mpreal val = max_value(); if(!has_init) { val = log(val); has_init = true; } return val; } template <> inline mpfr::mpreal log_min_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr::mpreal)) { static bool has_init = false; static mpfr::mpreal val = max_value(); if(!has_init) { val = log(val); has_init = true; } return val; } template <> inline mpfr::mpreal epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr::mpreal)) { return ldexp(mpfr::mpreal(1), 1-boost::math::policies::digits >()); } } // namespace tools template inline mpfr::mpreal skewness(const extreme_value_distribution& /*dist*/) { // // This is 12 * sqrt(6) * zeta(3) / pi^3: // See http://mathworld.wolfram.com/ExtremeValueDistribution.html // return boost::lexical_cast("1.1395470994046486574927930193898461120875997958366"); } template inline mpfr::mpreal skewness(const rayleigh_distribution& /*dist*/) { // using namespace boost::math::constants; return boost::lexical_cast("0.63111065781893713819189935154422777984404221106391"); // Computed using NTL at 150 bit, about 50 decimal digits. // return 2 * root_pi() * pi_minus_three() / pow23_four_minus_pi(); } template inline mpfr::mpreal kurtosis(const rayleigh_distribution& /*dist*/) { // using namespace boost::math::constants; return boost::lexical_cast("3.2450893006876380628486604106197544154170667057995"); // Computed using NTL at 150 bit, about 50 decimal digits. // return 3 - (6 * pi() * pi() - 24 * pi() + 16) / // (four_minus_pi() * four_minus_pi()); } template inline mpfr::mpreal kurtosis_excess(const rayleigh_distribution& /*dist*/) { //using namespace boost::math::constants; // Computed using NTL at 150 bit, about 50 decimal digits. return boost::lexical_cast("0.2450893006876380628486604106197544154170667057995"); // return -(6 * pi() * pi() - 24 * pi() + 16) / // (four_minus_pi() * four_minus_pi()); } // kurtosis namespace detail{ // // Version of Digamma accurate to ~100 decimal digits. // template mpfr::mpreal digamma_imp(mpfr::mpreal x, const mpl::int_<0>* , const Policy& pol) { // // This handles reflection of negative arguments, and all our // empfr_classor handling, then forwards to the T-specific approximation. // BOOST_MATH_STD_USING // ADL of std functions. mpfr::mpreal result = 0; // // Check for negative arguments and use reflection: // if(x < 0) { // Reflect: x = 1 - x; // Argument reduction for tan: mpfr::mpreal remainder = x - floor(x); // Shift to negative if > 0.5: if(remainder > 0.5) { remainder -= 1; } // // check for evaluation at a negative pole: // if(remainder == 0) { return policies::raise_pole_error("boost::math::digamma<%1%>(%1%)", 0, (1-x), pol); } result = constants::pi() / tan(constants::pi() * remainder); } result += big_digamma(x); return result; } // // Specialisations of this function provides the initial // starting guess for Halley iteration: // template mpfr::mpreal erf_inv_imp(const mpfr::mpreal& p, const mpfr::mpreal& q, const Policy&, const boost::mpl::int_<64>*) { BOOST_MATH_STD_USING // for ADL of std names. mpfr::mpreal result = 0; if(p <= 0.5) { // // Evaluate inverse erf using the rational approximation: // // x = p(p+10)(Y+R(p)) // // Where Y is a constant, and R(p) is optimised for a low // absolute empfr_classor compared to |Y|. // // double: Max empfr_classor found: 2.001849e-18 // long double: Max empfr_classor found: 1.017064e-20 // Maximum Deviation Found (actual empfr_classor term at infinite precision) 8.030e-21 // static const float Y = 0.0891314744949340820313f; static const mpfr::mpreal P[] = { -0.000508781949658280665617, -0.00836874819741736770379, 0.0334806625409744615033, -0.0126926147662974029034, -0.0365637971411762664006, 0.0219878681111168899165, 0.00822687874676915743155, -0.00538772965071242932965 }; static const mpfr::mpreal Q[] = { 1, -0.970005043303290640362, -1.56574558234175846809, 1.56221558398423026363, 0.662328840472002992063, -0.71228902341542847553, -0.0527396382340099713954, 0.0795283687341571680018, -0.00233393759374190016776, 0.000886216390456424707504 }; mpfr::mpreal g = p * (p + 10); mpfr::mpreal r = tools::evaluate_polynomial(P, p) / tools::evaluate_polynomial(Q, p); result = g * Y + g * r; } else if(q >= 0.25) { // // Rational approximation for 0.5 > q >= 0.25 // // x = sqrt(-2*log(q)) / (Y + R(q)) // // Where Y is a constant, and R(q) is optimised for a low // absolute empfr_classor compared to Y. // // double : Max empfr_classor found: 7.403372e-17 // long double : Max empfr_classor found: 6.084616e-20 // Maximum Deviation Found (empfr_classor term) 4.811e-20 // static const float Y = 2.249481201171875f; static const mpfr::mpreal P[] = { -0.202433508355938759655, 0.105264680699391713268, 8.37050328343119927838, 17.6447298408374015486, -18.8510648058714251895, -44.6382324441786960818, 17.445385985570866523, 21.1294655448340526258, -3.67192254707729348546 }; static const mpfr::mpreal Q[] = { 1, 6.24264124854247537712, 3.9713437953343869095, -28.6608180499800029974, -20.1432634680485188801, 48.5609213108739935468, 10.8268667355460159008, -22.6436933413139721736, 1.72114765761200282724 }; mpfr::mpreal g = sqrt(-2 * log(q)); mpfr::mpreal xs = q - 0.25; mpfr::mpreal r = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs); result = g / (Y + r); } else { // // For q < 0.25 we have a series of rational approximations all // of the general form: // // let: x = sqrt(-log(q)) // // Then the result is given by: // // x(Y+R(x-B)) // // where Y is a constant, B is the lowest value of x for which // the approximation is valid, and R(x-B) is optimised for a low // absolute empfr_classor compared to Y. // // Note that almost all code will really go through the first // or maybe second approximation. After than we're dealing with very // small input values indeed: 80 and 128 bit long double's go all the // way down to ~ 1e-5000 so the "tail" is rather long... // mpfr::mpreal x = sqrt(-log(q)); if(x < 3) { // Max empfr_classor found: 1.089051e-20 static const float Y = 0.807220458984375f; static const mpfr::mpreal P[] = { -0.131102781679951906451, -0.163794047193317060787, 0.117030156341995252019, 0.387079738972604337464, 0.337785538912035898924, 0.142869534408157156766, 0.0290157910005329060432, 0.00214558995388805277169, -0.679465575181126350155e-6, 0.285225331782217055858e-7, -0.681149956853776992068e-9 }; static const mpfr::mpreal Q[] = { 1, 3.46625407242567245975, 5.38168345707006855425, 4.77846592945843778382, 2.59301921623620271374, 0.848854343457902036425, 0.152264338295331783612, 0.01105924229346489121 }; mpfr::mpreal xs = x - 1.125; mpfr::mpreal R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs); result = Y * x + R * x; } else if(x < 6) { // Max empfr_classor found: 8.389174e-21 static const float Y = 0.93995571136474609375f; static const mpfr::mpreal P[] = { -0.0350353787183177984712, -0.00222426529213447927281, 0.0185573306514231072324, 0.00950804701325919603619, 0.00187123492819559223345, 0.000157544617424960554631, 0.460469890584317994083e-5, -0.230404776911882601748e-9, 0.266339227425782031962e-11 }; static const mpfr::mpreal Q[] = { 1, 1.3653349817554063097, 0.762059164553623404043, 0.220091105764131249824, 0.0341589143670947727934, 0.00263861676657015992959, 0.764675292302794483503e-4 }; mpfr::mpreal xs = x - 3; mpfr::mpreal R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs); result = Y * x + R * x; } else if(x < 18) { // Max empfr_classor found: 1.481312e-19 static const float Y = 0.98362827301025390625f; static const mpfr::mpreal P[] = { -0.0167431005076633737133, -0.00112951438745580278863, 0.00105628862152492910091, 0.000209386317487588078668, 0.149624783758342370182e-4, 0.449696789927706453732e-6, 0.462596163522878599135e-8, -0.281128735628831791805e-13, 0.99055709973310326855e-16 }; static const mpfr::mpreal Q[] = { 1, 0.591429344886417493481, 0.138151865749083321638, 0.0160746087093676504695, 0.000964011807005165528527, 0.275335474764726041141e-4, 0.282243172016108031869e-6 }; mpfr::mpreal xs = x - 6; mpfr::mpreal R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs); result = Y * x + R * x; } else if(x < 44) { // Max empfr_classor found: 5.697761e-20 static const float Y = 0.99714565277099609375f; static const mpfr::mpreal P[] = { -0.0024978212791898131227, -0.779190719229053954292e-5, 0.254723037413027451751e-4, 0.162397777342510920873e-5, 0.396341011304801168516e-7, 0.411632831190944208473e-9, 0.145596286718675035587e-11, -0.116765012397184275695e-17 }; static const mpfr::mpreal Q[] = { 1, 0.207123112214422517181, 0.0169410838120975906478, 0.000690538265622684595676, 0.145007359818232637924e-4, 0.144437756628144157666e-6, 0.509761276599778486139e-9 }; mpfr::mpreal xs = x - 18; mpfr::mpreal R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs); result = Y * x + R * x; } else { // Max empfr_classor found: 1.279746e-20 static const float Y = 0.99941349029541015625f; static const mpfr::mpreal P[] = { -0.000539042911019078575891, -0.28398759004727721098e-6, 0.899465114892291446442e-6, 0.229345859265920864296e-7, 0.225561444863500149219e-9, 0.947846627503022684216e-12, 0.135880130108924861008e-14, -0.348890393399948882918e-21 }; static const mpfr::mpreal Q[] = { 1, 0.0845746234001899436914, 0.00282092984726264681981, 0.468292921940894236786e-4, 0.399968812193862100054e-6, 0.161809290887904476097e-8, 0.231558608310259605225e-11 }; mpfr::mpreal xs = x - 44; mpfr::mpreal R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs); result = Y * x + R * x; } } return result; } mpfr::mpreal bessel_i0(mpfr::mpreal x) { static const mpfr::mpreal P1[] = { boost::lexical_cast("-2.2335582639474375249e+15"), boost::lexical_cast("-5.5050369673018427753e+14"), boost::lexical_cast("-3.2940087627407749166e+13"), boost::lexical_cast("-8.4925101247114157499e+11"), boost::lexical_cast("-1.1912746104985237192e+10"), boost::lexical_cast("-1.0313066708737980747e+08"), boost::lexical_cast("-5.9545626019847898221e+05"), boost::lexical_cast("-2.4125195876041896775e+03"), boost::lexical_cast("-7.0935347449210549190e+00"), boost::lexical_cast("-1.5453977791786851041e-02"), boost::lexical_cast("-2.5172644670688975051e-05"), boost::lexical_cast("-3.0517226450451067446e-08"), boost::lexical_cast("-2.6843448573468483278e-11"), boost::lexical_cast("-1.5982226675653184646e-14"), boost::lexical_cast("-5.2487866627945699800e-18"), }; static const mpfr::mpreal Q1[] = { boost::lexical_cast("-2.2335582639474375245e+15"), boost::lexical_cast("7.8858692566751002988e+12"), boost::lexical_cast("-1.2207067397808979846e+10"), boost::lexical_cast("1.0377081058062166144e+07"), boost::lexical_cast("-4.8527560179962773045e+03"), boost::lexical_cast("1.0"), }; static const mpfr::mpreal P2[] = { boost::lexical_cast("-2.2210262233306573296e-04"), boost::lexical_cast("1.3067392038106924055e-02"), boost::lexical_cast("-4.4700805721174453923e-01"), boost::lexical_cast("5.5674518371240761397e+00"), boost::lexical_cast("-2.3517945679239481621e+01"), boost::lexical_cast("3.1611322818701131207e+01"), boost::lexical_cast("-9.6090021968656180000e+00"), }; static const mpfr::mpreal Q2[] = { boost::lexical_cast("-5.5194330231005480228e-04"), boost::lexical_cast("3.2547697594819615062e-02"), boost::lexical_cast("-1.1151759188741312645e+00"), boost::lexical_cast("1.3982595353892851542e+01"), boost::lexical_cast("-6.0228002066743340583e+01"), boost::lexical_cast("8.5539563258012929600e+01"), boost::lexical_cast("-3.1446690275135491500e+01"), boost::lexical_cast("1.0"), }; mpfr::mpreal value, factor, r; BOOST_MATH_STD_USING using namespace boost::math::tools; if (x < 0) { x = -x; // even function } if (x == 0) { return static_cast(1); } if (x <= 15) // x in (0, 15] { mpfr::mpreal y = x * x; value = evaluate_polynomial(P1, y) / evaluate_polynomial(Q1, y); } else // x in (15, \infty) { mpfr::mpreal y = 1 / x - 1 / 15; r = evaluate_polynomial(P2, y) / evaluate_polynomial(Q2, y); factor = exp(x) / sqrt(x); value = factor * r; } return value; } mpfr::mpreal bessel_i1(mpfr::mpreal x) { static const mpfr::mpreal P1[] = { static_cast("-1.4577180278143463643e+15"), static_cast("-1.7732037840791591320e+14"), static_cast("-6.9876779648010090070e+12"), static_cast("-1.3357437682275493024e+11"), static_cast("-1.4828267606612366099e+09"), static_cast("-1.0588550724769347106e+07"), static_cast("-5.1894091982308017540e+04"), static_cast("-1.8225946631657315931e+02"), static_cast("-4.7207090827310162436e-01"), static_cast("-9.1746443287817501309e-04"), static_cast("-1.3466829827635152875e-06"), static_cast("-1.4831904935994647675e-09"), static_cast("-1.1928788903603238754e-12"), static_cast("-6.5245515583151902910e-16"), static_cast("-1.9705291802535139930e-19"), }; static const mpfr::mpreal Q1[] = { static_cast("-2.9154360556286927285e+15"), static_cast("9.7887501377547640438e+12"), static_cast("-1.4386907088588283434e+10"), static_cast("1.1594225856856884006e+07"), static_cast("-5.1326864679904189920e+03"), static_cast("1.0"), }; static const mpfr::mpreal P2[] = { static_cast("1.4582087408985668208e-05"), static_cast("-8.9359825138577646443e-04"), static_cast("2.9204895411257790122e-02"), static_cast("-3.4198728018058047439e-01"), static_cast("1.3960118277609544334e+00"), static_cast("-1.9746376087200685843e+00"), static_cast("8.5591872901933459000e-01"), static_cast("-6.0437159056137599999e-02"), }; static const mpfr::mpreal Q2[] = { static_cast("3.7510433111922824643e-05"), static_cast("-2.2835624489492512649e-03"), static_cast("7.4212010813186530069e-02"), static_cast("-8.5017476463217924408e-01"), static_cast("3.2593714889036996297e+00"), static_cast("-3.8806586721556593450e+00"), static_cast("1.0"), }; mpfr::mpreal value, factor, r, w; BOOST_MATH_STD_USING using namespace boost::math::tools; w = abs(x); if (x == 0) { return static_cast(0); } if (w <= 15) // w in (0, 15] { mpfr::mpreal y = x * x; r = evaluate_polynomial(P1, y) / evaluate_polynomial(Q1, y); factor = w; value = factor * r; } else // w in (15, \infty) { mpfr::mpreal y = 1 / w - mpfr::mpreal(1) / 15; r = evaluate_polynomial(P2, y) / evaluate_polynomial(Q2, y); factor = exp(w) / sqrt(w); value = factor * r; } if (x < 0) { value *= -value; // odd function } return value; } } // namespace detail } // namespace math } #endif // BOOST_MATH_MPLFR_BINDINGS_HPP