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glm/test/external/boost/math/bindings/mpfr.hpp

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// 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