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author | Anas Nashif <anas.nashif@intel.com> | 2012-10-30 12:57:26 -0700 |
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committer | Anas Nashif <anas.nashif@intel.com> | 2012-10-30 12:57:26 -0700 |
commit | 1a78a62555be32868418fe52f8e330c9d0f95d5a (patch) | |
tree | d3765a80e7d3b9640ec2e930743630cd6b9fce2b /boost/math/bindings/mpfr.hpp | |
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Imported Upstream version 1.49.0upstream/1.49.0
Diffstat (limited to 'boost/math/bindings/mpfr.hpp')
-rw-r--r-- | boost/math/bindings/mpfr.hpp | 866 |
1 files changed, 866 insertions, 0 deletions
diff --git a/boost/math/bindings/mpfr.hpp b/boost/math/bindings/mpfr.hpp new file mode 100644 index 0000000000..95be0ee2ba --- /dev/null +++ b/boost/math/bindings/mpfr.hpp @@ -0,0 +1,866 @@ +// 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_class defined in gmpfrxx.h +// See http://math.berkeley.edu/~wilken/code/gmpfrxx/ +// Also requires the gmp and mpfr libraries. +// + +#ifndef BOOST_MATH_MPLFR_BINDINGS_HPP +#define BOOST_MATH_MPLFR_BINDINGS_HPP + +#include <boost/config.hpp> + +#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 <gmpfrxx.h> + +#ifdef BOOST_MSVC +#pragma warning(pop) +#endif + +#include <boost/math/tools/precision.hpp> +#include <boost/math/tools/real_cast.hpp> +#include <boost/math/policies/policy.hpp> +#include <boost/math/distributions/fwd.hpp> +#include <boost/math/special_functions/math_fwd.hpp> +#include <boost/math/bindings/detail/big_digamma.hpp> +#include <boost/math/bindings/detail/big_lanczos.hpp> + +inline mpfr_class fabs(const mpfr_class& v) +{ + return abs(v); +} + +inline mpfr_class pow(const mpfr_class& b, const mpfr_class e) +{ + mpfr_class result; + mpfr_pow(result.__get_mp(), b.__get_mp(), e.__get_mp(), GMP_RNDN); + return result; +} + +inline mpfr_class ldexp(const mpfr_class& v, int e) +{ + //int e = mpfr_get_exp(*v.__get_mp()); + mpfr_class result(v); + mpfr_set_exp(result.__get_mp(), e); + return result; +} + +inline mpfr_class frexp(const mpfr_class& v, int* expon) +{ + int e = mpfr_get_exp(v.__get_mp()); + mpfr_class result(v); + mpfr_set_exp(result.__get_mp(), 0); + *expon = e; + return result; +} + +inline mpfr_class fmod(const mpfr_class& v1, const mpfr_class& v2) +{ + mpfr_class n; + if(v1 < 0) + n = ceil(v1 / v2); + else + n = floor(v1 / v2); + return v1 - n * v2; +} + +template <class Policy> +inline mpfr_class modf(const mpfr_class& v, long long* ipart, const Policy& pol) +{ + *ipart = lltrunc(v, pol); + return v - boost::math::tools::real_cast<mpfr_class>(*ipart); +} +template <class Policy> +inline int iround(mpfr_class const& x, const Policy& pol) +{ + return boost::math::tools::real_cast<int>(boost::math::round(x, pol)); +} + +template <class Policy> +inline long lround(mpfr_class const& x, const Policy& pol) +{ + return boost::math::tools::real_cast<long>(boost::math::round(x, pol)); +} + +template <class Policy> +inline long long llround(mpfr_class const& x, const Policy& pol) +{ + return boost::math::tools::real_cast<long long>(boost::math::round(x, pol)); +} + +template <class Policy> +inline int itrunc(mpfr_class const& x, const Policy& pol) +{ + return boost::math::tools::real_cast<int>(boost::math::trunc(x, pol)); +} + +template <class Policy> +inline long ltrunc(mpfr_class const& x, const Policy& pol) +{ + return boost::math::tools::real_cast<long>(boost::math::trunc(x, pol)); +} + +template <class Policy> +inline long long lltrunc(mpfr_class const& x, const Policy& pol) +{ + return boost::math::tools::real_cast<long long>(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 mpfr_lanczos +{ + static mpfr_class lanczos_sum(const mpfr_class& z) + { + unsigned long p = z.get_dprec(); + 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_class lanczos_sum_expG_scaled(const mpfr_class& z) + { + unsigned long p = z.get_dprec(); + 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_class lanczos_sum_near_1(const mpfr_class& z) + { + unsigned long p = z.get_dprec(); + 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_class lanczos_sum_near_2(const mpfr_class& z) + { + unsigned long p = z.get_dprec(); + 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_class g() + { + unsigned long p = mpfr_class::get_dprec(); + 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<class Policy> +struct lanczos<mpfr_class, Policy> +{ + typedef mpfr_lanczos type; +}; + +} // namespace lanczos + +namespace tools +{ + +template <class T, class U> +struct promote_arg<__gmp_expr<T,U> > +{ // If T is integral type, then promote to double. + typedef mpfr_class type; +}; + +template<> +inline int digits<mpfr_class>(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr_class)) +{ + return mpfr_class::get_dprec(); +} + +namespace detail{ + +template<class I> +void convert_to_long_result(mpfr_class const& r, I& result) +{ + result = 0; + I last_result(0); + mpfr_class t(r); + double term; + do + { + term = real_cast<double>(t); + last_result = result; + result += static_cast<I>(term); + t -= term; + }while(result != last_result); +} + +} + +template <> +inline mpfr_class real_cast<mpfr_class, long long>(long long t) +{ + mpfr_class 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<unsigned, mpfr_class>(mpfr_class t) +{ + return t.get_ui(); +} +template <> +inline int real_cast<int, mpfr_class>(mpfr_class t) +{ + return t.get_si(); +} +template <> +inline double real_cast<double, mpfr_class>(mpfr_class t) +{ + return t.get_d(); +} +template <> +inline float real_cast<float, mpfr_class>(mpfr_class t) +{ + return static_cast<float>(t.get_d()); +} +template <> +inline long real_cast<long, mpfr_class>(mpfr_class t) +{ + long result; + detail::convert_to_long_result(t, result); + return result; +} +template <> +inline long long real_cast<long long, mpfr_class>(mpfr_class t) +{ + long long result; + detail::convert_to_long_result(t, result); + return result; +} + +template <> +inline mpfr_class max_value<mpfr_class>(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr_class)) +{ + static bool has_init = false; + static mpfr_class val; + if(!has_init) + { + val = 0.5; + mpfr_set_exp(val.__get_mp(), mpfr_get_emax()); + has_init = true; + } + return val; +} + +template <> +inline mpfr_class min_value<mpfr_class>(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr_class)) +{ + static bool has_init = false; + static mpfr_class val; + if(!has_init) + { + val = 0.5; + mpfr_set_exp(val.__get_mp(), mpfr_get_emin()); + has_init = true; + } + return val; +} + +template <> +inline mpfr_class log_max_value<mpfr_class>(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr_class)) +{ + static bool has_init = false; + static mpfr_class val = max_value<mpfr_class>(); + if(!has_init) + { + val = log(val); + has_init = true; + } + return val; +} + +template <> +inline mpfr_class log_min_value<mpfr_class>(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr_class)) +{ + static bool has_init = false; + static mpfr_class val = max_value<mpfr_class>(); + if(!has_init) + { + val = log(val); + has_init = true; + } + return val; +} + +template <> +inline mpfr_class epsilon<mpfr_class>(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr_class)) +{ + return ldexp(mpfr_class(1), 1-boost::math::policies::digits<mpfr_class, boost::math::policies::policy<> >()); +} + +} // namespace tools + +namespace policies{ + +template <class T, class U, class Policy> +struct evaluation<__gmp_expr<T, U>, Policy> +{ + typedef mpfr_class type; +}; + +} + +template <class Policy> +inline mpfr_class skewness(const extreme_value_distribution<mpfr_class, Policy>& /*dist*/) +{ + // + // This is 12 * sqrt(6) * zeta(3) / pi^3: + // See http://mathworld.wolfram.com/ExtremeValueDistribution.html + // + return boost::lexical_cast<mpfr_class>("1.1395470994046486574927930193898461120875997958366"); +} + +template <class Policy> +inline mpfr_class skewness(const rayleigh_distribution<mpfr_class, Policy>& /*dist*/) +{ + // using namespace boost::math::constants; + return boost::lexical_cast<mpfr_class>("0.63111065781893713819189935154422777984404221106391"); + // Computed using NTL at 150 bit, about 50 decimal digits. + // return 2 * root_pi<RealType>() * pi_minus_three<RealType>() / pow23_four_minus_pi<RealType>(); +} + +template <class Policy> +inline mpfr_class kurtosis(const rayleigh_distribution<mpfr_class, Policy>& /*dist*/) +{ + // using namespace boost::math::constants; + return boost::lexical_cast<mpfr_class>("3.2450893006876380628486604106197544154170667057995"); + // Computed using NTL at 150 bit, about 50 decimal digits. + // return 3 - (6 * pi<RealType>() * pi<RealType>() - 24 * pi<RealType>() + 16) / + // (four_minus_pi<RealType>() * four_minus_pi<RealType>()); +} + +template <class Policy> +inline mpfr_class kurtosis_excess(const rayleigh_distribution<mpfr_class, Policy>& /*dist*/) +{ + //using namespace boost::math::constants; + // Computed using NTL at 150 bit, about 50 decimal digits. + return boost::lexical_cast<mpfr_class>("0.2450893006876380628486604106197544154170667057995"); + // return -(6 * pi<RealType>() * pi<RealType>() - 24 * pi<RealType>() + 16) / + // (four_minus_pi<RealType>() * four_minus_pi<RealType>()); +} // kurtosis + +namespace detail{ + +// +// Version of Digamma accurate to ~100 decimal digits. +// +template <class Policy> +mpfr_class digamma_imp(mpfr_class 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_class result = 0; + // + // Check for negative arguments and use reflection: + // + if(x < 0) + { + // Reflect: + x = 1 - x; + // Argument reduction for tan: + mpfr_class 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<mpfr_class>("boost::math::digamma<%1%>(%1%)", 0, (1-x), pol); + } + result = constants::pi<mpfr_class>() / tan(constants::pi<mpfr_class>() * remainder); + } + result += big_digamma(x); + return result; +} +// +// Specialisations of this function provides the initial +// starting guess for Halley iteration: +// +template <class Policy> +inline mpfr_class erf_inv_imp(const mpfr_class& p, const mpfr_class& q, const Policy&, const boost::mpl::int_<64>*) +{ + BOOST_MATH_STD_USING // for ADL of std names. + + mpfr_class 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_class P[] = { + -0.000508781949658280665617, + -0.00836874819741736770379, + 0.0334806625409744615033, + -0.0126926147662974029034, + -0.0365637971411762664006, + 0.0219878681111168899165, + 0.00822687874676915743155, + -0.00538772965071242932965 + }; + static const mpfr_class Q[] = { + 1, + -0.970005043303290640362, + -1.56574558234175846809, + 1.56221558398423026363, + 0.662328840472002992063, + -0.71228902341542847553, + -0.0527396382340099713954, + 0.0795283687341571680018, + -0.00233393759374190016776, + 0.000886216390456424707504 + }; + mpfr_class g = p * (p + 10); + mpfr_class 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_class P[] = { + -0.202433508355938759655, + 0.105264680699391713268, + 8.37050328343119927838, + 17.6447298408374015486, + -18.8510648058714251895, + -44.6382324441786960818, + 17.445385985570866523, + 21.1294655448340526258, + -3.67192254707729348546 + }; + static const mpfr_class Q[] = { + 1, + 6.24264124854247537712, + 3.9713437953343869095, + -28.6608180499800029974, + -20.1432634680485188801, + 48.5609213108739935468, + 10.8268667355460159008, + -22.6436933413139721736, + 1.72114765761200282724 + }; + mpfr_class g = sqrt(-2 * log(q)); + mpfr_class xs = q - 0.25; + mpfr_class 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_class x = sqrt(-log(q)); + if(x < 3) + { + // Max empfr_classor found: 1.089051e-20 + static const float Y = 0.807220458984375f; + static const mpfr_class 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_class Q[] = { + 1, + 3.46625407242567245975, + 5.38168345707006855425, + 4.77846592945843778382, + 2.59301921623620271374, + 0.848854343457902036425, + 0.152264338295331783612, + 0.01105924229346489121 + }; + mpfr_class xs = x - 1.125; + mpfr_class 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_class 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_class Q[] = { + 1, + 1.3653349817554063097, + 0.762059164553623404043, + 0.220091105764131249824, + 0.0341589143670947727934, + 0.00263861676657015992959, + 0.764675292302794483503e-4 + }; + mpfr_class xs = x - 3; + mpfr_class 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_class 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_class Q[] = { + 1, + 0.591429344886417493481, + 0.138151865749083321638, + 0.0160746087093676504695, + 0.000964011807005165528527, + 0.275335474764726041141e-4, + 0.282243172016108031869e-6 + }; + mpfr_class xs = x - 6; + mpfr_class 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_class 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_class Q[] = { + 1, + 0.207123112214422517181, + 0.0169410838120975906478, + 0.000690538265622684595676, + 0.145007359818232637924e-4, + 0.144437756628144157666e-6, + 0.509761276599778486139e-9 + }; + mpfr_class xs = x - 18; + mpfr_class 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_class 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_class Q[] = { + 1, + 0.0845746234001899436914, + 0.00282092984726264681981, + 0.468292921940894236786e-4, + 0.399968812193862100054e-6, + 0.161809290887904476097e-8, + 0.231558608310259605225e-11 + }; + mpfr_class xs = x - 44; + mpfr_class R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs); + result = Y * x + R * x; + } + } + return result; +} + +inline mpfr_class bessel_i0(mpfr_class x) +{ + static const mpfr_class P1[] = { + boost::lexical_cast<mpfr_class>("-2.2335582639474375249e+15"), + boost::lexical_cast<mpfr_class>("-5.5050369673018427753e+14"), + boost::lexical_cast<mpfr_class>("-3.2940087627407749166e+13"), + boost::lexical_cast<mpfr_class>("-8.4925101247114157499e+11"), + boost::lexical_cast<mpfr_class>("-1.1912746104985237192e+10"), + boost::lexical_cast<mpfr_class>("-1.0313066708737980747e+08"), + boost::lexical_cast<mpfr_class>("-5.9545626019847898221e+05"), + boost::lexical_cast<mpfr_class>("-2.4125195876041896775e+03"), + boost::lexical_cast<mpfr_class>("-7.0935347449210549190e+00"), + boost::lexical_cast<mpfr_class>("-1.5453977791786851041e-02"), + boost::lexical_cast<mpfr_class>("-2.5172644670688975051e-05"), + boost::lexical_cast<mpfr_class>("-3.0517226450451067446e-08"), + boost::lexical_cast<mpfr_class>("-2.6843448573468483278e-11"), + boost::lexical_cast<mpfr_class>("-1.5982226675653184646e-14"), + boost::lexical_cast<mpfr_class>("-5.2487866627945699800e-18"), + }; + static const mpfr_class Q1[] = { + boost::lexical_cast<mpfr_class>("-2.2335582639474375245e+15"), + boost::lexical_cast<mpfr_class>("7.8858692566751002988e+12"), + boost::lexical_cast<mpfr_class>("-1.2207067397808979846e+10"), + boost::lexical_cast<mpfr_class>("1.0377081058062166144e+07"), + boost::lexical_cast<mpfr_class>("-4.8527560179962773045e+03"), + boost::lexical_cast<mpfr_class>("1.0"), + }; + static const mpfr_class P2[] = { + boost::lexical_cast<mpfr_class>("-2.2210262233306573296e-04"), + boost::lexical_cast<mpfr_class>("1.3067392038106924055e-02"), + boost::lexical_cast<mpfr_class>("-4.4700805721174453923e-01"), + boost::lexical_cast<mpfr_class>("5.5674518371240761397e+00"), + boost::lexical_cast<mpfr_class>("-2.3517945679239481621e+01"), + boost::lexical_cast<mpfr_class>("3.1611322818701131207e+01"), + boost::lexical_cast<mpfr_class>("-9.6090021968656180000e+00"), + }; + static const mpfr_class Q2[] = { + boost::lexical_cast<mpfr_class>("-5.5194330231005480228e-04"), + boost::lexical_cast<mpfr_class>("3.2547697594819615062e-02"), + boost::lexical_cast<mpfr_class>("-1.1151759188741312645e+00"), + boost::lexical_cast<mpfr_class>("1.3982595353892851542e+01"), + boost::lexical_cast<mpfr_class>("-6.0228002066743340583e+01"), + boost::lexical_cast<mpfr_class>("8.5539563258012929600e+01"), + boost::lexical_cast<mpfr_class>("-3.1446690275135491500e+01"), + boost::lexical_cast<mpfr_class>("1.0"), + }; + mpfr_class 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<mpfr_class>(1); + } + if (x <= 15) // x in (0, 15] + { + mpfr_class y = x * x; + value = evaluate_polynomial(P1, y) / evaluate_polynomial(Q1, y); + } + else // x in (15, \infty) + { + mpfr_class y = 1 / x - 1 / 15; + r = evaluate_polynomial(P2, y) / evaluate_polynomial(Q2, y); + factor = exp(x) / sqrt(x); + value = factor * r; + } + + return value; +} + +inline mpfr_class bessel_i1(mpfr_class x) +{ + static const mpfr_class P1[] = { + static_cast<mpfr_class>("-1.4577180278143463643e+15"), + static_cast<mpfr_class>("-1.7732037840791591320e+14"), + static_cast<mpfr_class>("-6.9876779648010090070e+12"), + static_cast<mpfr_class>("-1.3357437682275493024e+11"), + static_cast<mpfr_class>("-1.4828267606612366099e+09"), + static_cast<mpfr_class>("-1.0588550724769347106e+07"), + static_cast<mpfr_class>("-5.1894091982308017540e+04"), + static_cast<mpfr_class>("-1.8225946631657315931e+02"), + static_cast<mpfr_class>("-4.7207090827310162436e-01"), + static_cast<mpfr_class>("-9.1746443287817501309e-04"), + static_cast<mpfr_class>("-1.3466829827635152875e-06"), + static_cast<mpfr_class>("-1.4831904935994647675e-09"), + static_cast<mpfr_class>("-1.1928788903603238754e-12"), + static_cast<mpfr_class>("-6.5245515583151902910e-16"), + static_cast<mpfr_class>("-1.9705291802535139930e-19"), + }; + static const mpfr_class Q1[] = { + static_cast<mpfr_class>("-2.9154360556286927285e+15"), + static_cast<mpfr_class>("9.7887501377547640438e+12"), + static_cast<mpfr_class>("-1.4386907088588283434e+10"), + static_cast<mpfr_class>("1.1594225856856884006e+07"), + static_cast<mpfr_class>("-5.1326864679904189920e+03"), + static_cast<mpfr_class>("1.0"), + }; + static const mpfr_class P2[] = { + static_cast<mpfr_class>("1.4582087408985668208e-05"), + static_cast<mpfr_class>("-8.9359825138577646443e-04"), + static_cast<mpfr_class>("2.9204895411257790122e-02"), + static_cast<mpfr_class>("-3.4198728018058047439e-01"), + static_cast<mpfr_class>("1.3960118277609544334e+00"), + static_cast<mpfr_class>("-1.9746376087200685843e+00"), + static_cast<mpfr_class>("8.5591872901933459000e-01"), + static_cast<mpfr_class>("-6.0437159056137599999e-02"), + }; + static const mpfr_class Q2[] = { + static_cast<mpfr_class>("3.7510433111922824643e-05"), + static_cast<mpfr_class>("-2.2835624489492512649e-03"), + static_cast<mpfr_class>("7.4212010813186530069e-02"), + static_cast<mpfr_class>("-8.5017476463217924408e-01"), + static_cast<mpfr_class>("3.2593714889036996297e+00"), + static_cast<mpfr_class>("-3.8806586721556593450e+00"), + static_cast<mpfr_class>("1.0"), + }; + mpfr_class value, factor, r, w; + + BOOST_MATH_STD_USING + using namespace boost::math::tools; + + w = abs(x); + if (x == 0) + { + return static_cast<mpfr_class>(0); + } + if (w <= 15) // w in (0, 15] + { + mpfr_class y = x * x; + r = evaluate_polynomial(P1, y) / evaluate_polynomial(Q1, y); + factor = w; + value = factor * r; + } + else // w in (15, \infty) + { + mpfr_class y = 1 / w - mpfr_class(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 + +}} + +#endif // BOOST_MATH_MPLFR_BINDINGS_HPP + |