1 //  Copyright John Maddock 2008.
2 //  Use, modification and distribution are subject to the
3 //  Boost Software License, Version 1.0. (See accompanying file
4 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
5 //
6 // Wrapper that works with mpfr_class defined in gmpfrxx.h
7 // See http://math.berkeley.edu/~wilken/code/gmpfrxx/
8 // Also requires the gmp and mpfr libraries.
9 //
10 
11 #ifndef BOOST_MATH_MPLFR_BINDINGS_HPP
12 #define BOOST_MATH_MPLFR_BINDINGS_HPP
13 
14 #include <boost/config.hpp>
15 #include <boost/lexical_cast.hpp>
16 
17 #ifdef BOOST_MSVC
18 //
19 // We get a lot of warnings from the gmp, mpfr and gmpfrxx headers,
20 // disable them here, so we only see warnings from *our* code:
21 //
22 #pragma warning(push)
23 #pragma warning(disable: 4127 4800 4512)
24 #endif
25 
26 #include <gmpfrxx.h>
27 
28 #ifdef BOOST_MSVC
29 #pragma warning(pop)
30 #endif
31 
32 #include <boost/math/tools/precision.hpp>
33 #include <boost/math/tools/real_cast.hpp>
34 #include <boost/math/policies/policy.hpp>
35 #include <boost/math/distributions/fwd.hpp>
36 #include <boost/math/special_functions/math_fwd.hpp>
37 #include <boost/math/bindings/detail/big_digamma.hpp>
38 #include <boost/math/bindings/detail/big_lanczos.hpp>
39 #include <boost/math/tools/big_constant.hpp>
40 
fabs(const mpfr_class & v)41 inline mpfr_class fabs(const mpfr_class& v)
42 {
43    return abs(v);
44 }
45 template <class T, class U>
fabs(const __gmp_expr<T,U> & v)46 inline mpfr_class fabs(const __gmp_expr<T,U>& v)
47 {
48    return abs(static_cast<mpfr_class>(v));
49 }
50 
pow(const mpfr_class & b,const mpfr_class & e)51 inline mpfr_class pow(const mpfr_class& b, const mpfr_class& e)
52 {
53    mpfr_class result;
54    mpfr_pow(result.__get_mp(), b.__get_mp(), e.__get_mp(), GMP_RNDN);
55    return result;
56 }
57 /*
58 template <class T, class U, class V, class W>
59 inline mpfr_class pow(const __gmp_expr<T,U>& b, const __gmp_expr<V,W>& e)
60 {
61    return pow(static_cast<mpfr_class>(b), static_cast<mpfr_class>(e));
62 }
63 */
ldexp(const mpfr_class & v,int e)64 inline mpfr_class ldexp(const mpfr_class& v, int e)
65 {
66    //int e = mpfr_get_exp(*v.__get_mp());
67    mpfr_class result(v);
68    mpfr_set_exp(result.__get_mp(), e);
69    return result;
70 }
71 template <class T, class U>
ldexp(const __gmp_expr<T,U> & v,int e)72 inline mpfr_class ldexp(const __gmp_expr<T,U>& v, int e)
73 {
74    return ldexp(static_cast<mpfr_class>(v), e);
75 }
76 
frexp(const mpfr_class & v,int * expon)77 inline mpfr_class frexp(const mpfr_class& v, int* expon)
78 {
79    int e = mpfr_get_exp(v.__get_mp());
80    mpfr_class result(v);
81    mpfr_set_exp(result.__get_mp(), 0);
82    *expon = e;
83    return result;
84 }
85 template <class T, class U>
frexp(const __gmp_expr<T,U> & v,int * expon)86 inline mpfr_class frexp(const __gmp_expr<T,U>& v, int* expon)
87 {
88    return frexp(static_cast<mpfr_class>(v), expon);
89 }
90 
fmod(const mpfr_class & v1,const mpfr_class & v2)91 inline mpfr_class fmod(const mpfr_class& v1, const mpfr_class& v2)
92 {
93    mpfr_class n;
94    if(v1 < 0)
95       n = ceil(v1 / v2);
96    else
97       n = floor(v1 / v2);
98    return v1 - n * v2;
99 }
100 template <class T, class U, class V, class W>
fmod(const __gmp_expr<T,U> & v1,const __gmp_expr<V,W> & v2)101 inline mpfr_class fmod(const __gmp_expr<T,U>& v1, const __gmp_expr<V,W>& v2)
102 {
103    return fmod(static_cast<mpfr_class>(v1), static_cast<mpfr_class>(v2));
104 }
105 
106 template <class Policy>
modf(const mpfr_class & v,long long * ipart,const Policy & pol)107 inline mpfr_class modf(const mpfr_class& v, long long* ipart, const Policy& pol)
108 {
109    *ipart = lltrunc(v, pol);
110    return v - boost::math::tools::real_cast<mpfr_class>(*ipart);
111 }
112 template <class T, class U, class Policy>
modf(const __gmp_expr<T,U> & v,long long * ipart,const Policy & pol)113 inline mpfr_class modf(const __gmp_expr<T,U>& v, long long* ipart, const Policy& pol)
114 {
115    return modf(static_cast<mpfr_class>(v), ipart, pol);
116 }
117 
118 template <class Policy>
iround(mpfr_class const & x,const Policy &)119 inline int iround(mpfr_class const& x, const Policy&)
120 {
121    return boost::math::tools::real_cast<int>(boost::math::round(x, typename boost::math::policies::normalise<Policy, boost::math::policies::rounding_error< boost::math::policies::throw_on_error> >::type()));
122 }
123 template <class T, class U, class Policy>
iround(__gmp_expr<T,U> const & x,const Policy & pol)124 inline int iround(__gmp_expr<T,U> const& x, const Policy& pol)
125 {
126    return iround(static_cast<mpfr_class>(x), pol);
127 }
128 
129 template <class Policy>
lround(mpfr_class const & x,const Policy &)130 inline long lround(mpfr_class const& x, const Policy&)
131 {
132    return boost::math::tools::real_cast<long>(boost::math::round(x, typename boost::math::policies::normalise<Policy, boost::math::policies::rounding_error< boost::math::policies::throw_on_error> >::type()));
133 }
134 template <class T, class U, class Policy>
lround(__gmp_expr<T,U> const & x,const Policy & pol)135 inline long lround(__gmp_expr<T,U> const& x, const Policy& pol)
136 {
137    return lround(static_cast<mpfr_class>(x), pol);
138 }
139 
140 template <class Policy>
llround(mpfr_class const & x,const Policy &)141 inline long long llround(mpfr_class const& x, const Policy&)
142 {
143    return boost::math::tools::real_cast<long long>(boost::math::round(x, typename boost::math::policies::normalise<Policy, boost::math::policies::rounding_error< boost::math::policies::throw_on_error> >::type()));
144 }
145 template <class T, class U, class Policy>
llround(__gmp_expr<T,U> const & x,const Policy & pol)146 inline long long llround(__gmp_expr<T,U> const& x, const Policy& pol)
147 {
148    return llround(static_cast<mpfr_class>(x), pol);
149 }
150 
151 template <class Policy>
itrunc(mpfr_class const & x,const Policy &)152 inline int itrunc(mpfr_class const& x, const Policy&)
153 {
154    return boost::math::tools::real_cast<int>(boost::math::trunc(x, typename boost::math::policies::normalise<Policy, boost::math::policies::rounding_error< boost::math::policies::throw_on_error> >::type()));
155 }
156 template <class T, class U, class Policy>
itrunc(__gmp_expr<T,U> const & x,const Policy & pol)157 inline int itrunc(__gmp_expr<T,U> const& x, const Policy& pol)
158 {
159    return itrunc(static_cast<mpfr_class>(x), pol);
160 }
161 
162 template <class Policy>
ltrunc(mpfr_class const & x,const Policy &)163 inline long ltrunc(mpfr_class const& x, const Policy&)
164 {
165    return boost::math::tools::real_cast<long>(boost::math::trunc(x, typename boost::math::policies::normalise<Policy, boost::math::policies::rounding_error< boost::math::policies::throw_on_error> >::type()));
166 }
167 template <class T, class U, class Policy>
ltrunc(__gmp_expr<T,U> const & x,const Policy & pol)168 inline long ltrunc(__gmp_expr<T,U> const& x, const Policy& pol)
169 {
170    return ltrunc(static_cast<mpfr_class>(x), pol);
171 }
172 
173 template <class Policy>
lltrunc(mpfr_class const & x,const Policy &)174 inline long long lltrunc(mpfr_class const& x, const Policy&)
175 {
176    return boost::math::tools::real_cast<long long>(boost::math::trunc(x, typename boost::math::policies::normalise<Policy, boost::math::policies::rounding_error< boost::math::policies::throw_on_error> >::type()));
177 }
178 template <class T, class U, class Policy>
lltrunc(__gmp_expr<T,U> const & x,const Policy & pol)179 inline long long lltrunc(__gmp_expr<T,U> const& x, const Policy& pol)
180 {
181    return lltrunc(static_cast<mpfr_class>(x), pol);
182 }
183 
184 namespace boost{
185 
186 #ifdef BOOST_MATH_USE_FLOAT128
187    template<> struct is_convertible<BOOST_MATH_FLOAT128_TYPE, mpfr_class> : public boost::integral_constant<bool, false>{};
188 #endif
189    template<> struct is_convertible<long long, mpfr_class> : public boost::integral_constant<bool, false>{};
190 
191 namespace math{
192 
193 #if defined(__GNUC__) && (__GNUC__ < 4)
194    using ::iround;
195    using ::lround;
196    using ::llround;
197    using ::itrunc;
198    using ::ltrunc;
199    using ::lltrunc;
200    using ::modf;
201 #endif
202 
203 namespace lanczos{
204 
205 struct mpfr_lanczos
206 {
lanczos_sumboost::math::lanczos::mpfr_lanczos207    static mpfr_class lanczos_sum(const mpfr_class& z)
208    {
209       unsigned long p = z.get_dprec();
210       if(p <= 72)
211          return lanczos13UDT::lanczos_sum(z);
212       else if(p <= 120)
213          return lanczos22UDT::lanczos_sum(z);
214       else if(p <= 170)
215          return lanczos31UDT::lanczos_sum(z);
216       else //if(p <= 370) approx 100 digit precision:
217          return lanczos61UDT::lanczos_sum(z);
218    }
lanczos_sum_expG_scaledboost::math::lanczos::mpfr_lanczos219    static mpfr_class lanczos_sum_expG_scaled(const mpfr_class& z)
220    {
221       unsigned long p = z.get_dprec();
222       if(p <= 72)
223          return lanczos13UDT::lanczos_sum_expG_scaled(z);
224       else if(p <= 120)
225          return lanczos22UDT::lanczos_sum_expG_scaled(z);
226       else if(p <= 170)
227          return lanczos31UDT::lanczos_sum_expG_scaled(z);
228       else //if(p <= 370) approx 100 digit precision:
229          return lanczos61UDT::lanczos_sum_expG_scaled(z);
230    }
lanczos_sum_near_1boost::math::lanczos::mpfr_lanczos231    static mpfr_class lanczos_sum_near_1(const mpfr_class& z)
232    {
233       unsigned long p = z.get_dprec();
234       if(p <= 72)
235          return lanczos13UDT::lanczos_sum_near_1(z);
236       else if(p <= 120)
237          return lanczos22UDT::lanczos_sum_near_1(z);
238       else if(p <= 170)
239          return lanczos31UDT::lanczos_sum_near_1(z);
240       else //if(p <= 370) approx 100 digit precision:
241          return lanczos61UDT::lanczos_sum_near_1(z);
242    }
lanczos_sum_near_2boost::math::lanczos::mpfr_lanczos243    static mpfr_class lanczos_sum_near_2(const mpfr_class& z)
244    {
245       unsigned long p = z.get_dprec();
246       if(p <= 72)
247          return lanczos13UDT::lanczos_sum_near_2(z);
248       else if(p <= 120)
249          return lanczos22UDT::lanczos_sum_near_2(z);
250       else if(p <= 170)
251          return lanczos31UDT::lanczos_sum_near_2(z);
252       else //if(p <= 370) approx 100 digit precision:
253          return lanczos61UDT::lanczos_sum_near_2(z);
254    }
gboost::math::lanczos::mpfr_lanczos255    static mpfr_class g()
256    {
257       unsigned long p = mpfr_class::get_dprec();
258       if(p <= 72)
259          return lanczos13UDT::g();
260       else if(p <= 120)
261          return lanczos22UDT::g();
262       else if(p <= 170)
263          return lanczos31UDT::g();
264       else //if(p <= 370) approx 100 digit precision:
265          return lanczos61UDT::g();
266    }
267 };
268 
269 template<class Policy>
270 struct lanczos<mpfr_class, Policy>
271 {
272    typedef mpfr_lanczos type;
273 };
274 
275 } // namespace lanczos
276 
277 namespace constants{
278 
279 template <class Real, class Policy>
280 struct construction_traits;
281 
282 template <class Policy>
283 struct construction_traits<mpfr_class, Policy>
284 {
285    typedef mpl::int_<0> type;
286 };
287 
288 }
289 
290 namespace tools
291 {
292 
293 template <class T, class U>
294 struct promote_arg<__gmp_expr<T,U> >
295 { // If T is integral type, then promote to double.
296   typedef mpfr_class type;
297 };
298 
299 template<>
digits(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC (mpfr_class))300 inline int digits<mpfr_class>(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr_class))
301 {
302    return mpfr_class::get_dprec();
303 }
304 
305 namespace detail{
306 
307 template<class I>
convert_to_long_result(mpfr_class const & r,I & result)308 void convert_to_long_result(mpfr_class const& r, I& result)
309 {
310    result = 0;
311    I last_result(0);
312    mpfr_class t(r);
313    double term;
314    do
315    {
316       term = real_cast<double>(t);
317       last_result = result;
318       result += static_cast<I>(term);
319       t -= term;
320    }while(result != last_result);
321 }
322 
323 }
324 
325 template <>
real_cast(long long t)326 inline mpfr_class real_cast<mpfr_class, long long>(long long t)
327 {
328    mpfr_class result;
329    int expon = 0;
330    int sign = 1;
331    if(t < 0)
332    {
333       sign = -1;
334       t = -t;
335    }
336    while(t)
337    {
338       result += ldexp((double)(t & 0xffffL), expon);
339       expon += 32;
340       t >>= 32;
341    }
342    return result * sign;
343 }
344 template <>
real_cast(mpfr_class t)345 inline unsigned real_cast<unsigned, mpfr_class>(mpfr_class t)
346 {
347    return t.get_ui();
348 }
349 template <>
real_cast(mpfr_class t)350 inline int real_cast<int, mpfr_class>(mpfr_class t)
351 {
352    return t.get_si();
353 }
354 template <>
real_cast(mpfr_class t)355 inline double real_cast<double, mpfr_class>(mpfr_class t)
356 {
357    return t.get_d();
358 }
359 template <>
real_cast(mpfr_class t)360 inline float real_cast<float, mpfr_class>(mpfr_class t)
361 {
362    return static_cast<float>(t.get_d());
363 }
364 template <>
real_cast(mpfr_class t)365 inline long real_cast<long, mpfr_class>(mpfr_class t)
366 {
367    long result;
368    detail::convert_to_long_result(t, result);
369    return result;
370 }
371 template <>
real_cast(mpfr_class t)372 inline long long real_cast<long long, mpfr_class>(mpfr_class t)
373 {
374    long long result;
375    detail::convert_to_long_result(t, result);
376    return result;
377 }
378 
379 template <>
max_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC (mpfr_class))380 inline mpfr_class max_value<mpfr_class>(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr_class))
381 {
382    static bool has_init = false;
383    static mpfr_class val;
384    if(!has_init)
385    {
386       val = 0.5;
387       mpfr_set_exp(val.__get_mp(), mpfr_get_emax());
388       has_init = true;
389    }
390    return val;
391 }
392 
393 template <>
min_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC (mpfr_class))394 inline mpfr_class min_value<mpfr_class>(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr_class))
395 {
396    static bool has_init = false;
397    static mpfr_class val;
398    if(!has_init)
399    {
400       val = 0.5;
401       mpfr_set_exp(val.__get_mp(), mpfr_get_emin());
402       has_init = true;
403    }
404    return val;
405 }
406 
407 template <>
log_max_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC (mpfr_class))408 inline mpfr_class log_max_value<mpfr_class>(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr_class))
409 {
410    static bool has_init = false;
411    static mpfr_class val = max_value<mpfr_class>();
412    if(!has_init)
413    {
414       val = log(val);
415       has_init = true;
416    }
417    return val;
418 }
419 
420 template <>
log_min_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC (mpfr_class))421 inline mpfr_class log_min_value<mpfr_class>(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr_class))
422 {
423    static bool has_init = false;
424    static mpfr_class val = max_value<mpfr_class>();
425    if(!has_init)
426    {
427       val = log(val);
428       has_init = true;
429    }
430    return val;
431 }
432 
433 template <>
epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC (mpfr_class))434 inline mpfr_class epsilon<mpfr_class>(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr_class))
435 {
436    return ldexp(mpfr_class(1), 1-boost::math::policies::digits<mpfr_class, boost::math::policies::policy<> >());
437 }
438 
439 } // namespace tools
440 
441 namespace policies{
442 
443 template <class T, class U, class Policy>
444 struct evaluation<__gmp_expr<T, U>, Policy>
445 {
446    typedef mpfr_class type;
447 };
448 
449 }
450 
451 template <class Policy>
skewness(const extreme_value_distribution<mpfr_class,Policy> &)452 inline mpfr_class skewness(const extreme_value_distribution<mpfr_class, Policy>& /*dist*/)
453 {
454    //
455    // This is 12 * sqrt(6) * zeta(3) / pi^3:
456    // See http://mathworld.wolfram.com/ExtremeValueDistribution.html
457    //
458    return boost::lexical_cast<mpfr_class>("1.1395470994046486574927930193898461120875997958366");
459 }
460 
461 template <class Policy>
skewness(const rayleigh_distribution<mpfr_class,Policy> &)462 inline mpfr_class skewness(const rayleigh_distribution<mpfr_class, Policy>& /*dist*/)
463 {
464   // using namespace boost::math::constants;
465   return boost::lexical_cast<mpfr_class>("0.63111065781893713819189935154422777984404221106391");
466   // Computed using NTL at 150 bit, about 50 decimal digits.
467   // return 2 * root_pi<RealType>() * pi_minus_three<RealType>() / pow23_four_minus_pi<RealType>();
468 }
469 
470 template <class Policy>
kurtosis(const rayleigh_distribution<mpfr_class,Policy> &)471 inline mpfr_class kurtosis(const rayleigh_distribution<mpfr_class, Policy>& /*dist*/)
472 {
473   // using namespace boost::math::constants;
474   return boost::lexical_cast<mpfr_class>("3.2450893006876380628486604106197544154170667057995");
475   // Computed using NTL at 150 bit, about 50 decimal digits.
476   // return 3 - (6 * pi<RealType>() * pi<RealType>() - 24 * pi<RealType>() + 16) /
477   // (four_minus_pi<RealType>() * four_minus_pi<RealType>());
478 }
479 
480 template <class Policy>
kurtosis_excess(const rayleigh_distribution<mpfr_class,Policy> &)481 inline mpfr_class kurtosis_excess(const rayleigh_distribution<mpfr_class, Policy>& /*dist*/)
482 {
483   //using namespace boost::math::constants;
484   // Computed using NTL at 150 bit, about 50 decimal digits.
485   return boost::lexical_cast<mpfr_class>("0.2450893006876380628486604106197544154170667057995");
486   // return -(6 * pi<RealType>() * pi<RealType>() - 24 * pi<RealType>() + 16) /
487   //   (four_minus_pi<RealType>() * four_minus_pi<RealType>());
488 } // kurtosis
489 
490 namespace detail{
491 
492 //
493 // Version of Digamma accurate to ~100 decimal digits.
494 //
495 template <class Policy>
digamma_imp(mpfr_class x,const mpl::int_<0> *,const Policy & pol)496 mpfr_class digamma_imp(mpfr_class x, const mpl::int_<0>* , const Policy& pol)
497 {
498    //
499    // This handles reflection of negative arguments, and all our
500    // empfr_classor handling, then forwards to the T-specific approximation.
501    //
502    BOOST_MATH_STD_USING // ADL of std functions.
503 
504    mpfr_class result = 0;
505    //
506    // Check for negative arguments and use reflection:
507    //
508    if(x < 0)
509    {
510       // Reflect:
511       x = 1 - x;
512       // Argument reduction for tan:
513       mpfr_class remainder = x - floor(x);
514       // Shift to negative if > 0.5:
515       if(remainder > 0.5)
516       {
517          remainder -= 1;
518       }
519       //
520       // check for evaluation at a negative pole:
521       //
522       if(remainder == 0)
523       {
524          return policies::raise_pole_error<mpfr_class>("boost::math::digamma<%1%>(%1%)", 0, (1-x), pol);
525       }
526       result = constants::pi<mpfr_class>() / tan(constants::pi<mpfr_class>() * remainder);
527    }
528    result += big_digamma(x);
529    return result;
530 }
531 //
532 // Specialisations of this function provides the initial
533 // starting guess for Halley iteration:
534 //
535 template <class Policy>
erf_inv_imp(const mpfr_class & p,const mpfr_class & q,const Policy &,const boost::mpl::int_<64> *)536 inline mpfr_class erf_inv_imp(const mpfr_class& p, const mpfr_class& q, const Policy&, const boost::mpl::int_<64>*)
537 {
538    BOOST_MATH_STD_USING // for ADL of std names.
539 
540    mpfr_class result = 0;
541 
542    if(p <= 0.5)
543    {
544       //
545       // Evaluate inverse erf using the rational approximation:
546       //
547       // x = p(p+10)(Y+R(p))
548       //
549       // Where Y is a constant, and R(p) is optimised for a low
550       // absolute empfr_classor compared to |Y|.
551       //
552       // double: Max empfr_classor found: 2.001849e-18
553       // long double: Max empfr_classor found: 1.017064e-20
554       // Maximum Deviation Found (actual empfr_classor term at infinite precision) 8.030e-21
555       //
556       static const float Y = 0.0891314744949340820313f;
557       static const mpfr_class P[] = {
558          -0.000508781949658280665617,
559          -0.00836874819741736770379,
560          0.0334806625409744615033,
561          -0.0126926147662974029034,
562          -0.0365637971411762664006,
563          0.0219878681111168899165,
564          0.00822687874676915743155,
565          -0.00538772965071242932965
566       };
567       static const mpfr_class Q[] = {
568          1,
569          -0.970005043303290640362,
570          -1.56574558234175846809,
571          1.56221558398423026363,
572          0.662328840472002992063,
573          -0.71228902341542847553,
574          -0.0527396382340099713954,
575          0.0795283687341571680018,
576          -0.00233393759374190016776,
577          0.000886216390456424707504
578       };
579       mpfr_class g = p * (p + 10);
580       mpfr_class r = tools::evaluate_polynomial(P, p) / tools::evaluate_polynomial(Q, p);
581       result = g * Y + g * r;
582    }
583    else if(q >= 0.25)
584    {
585       //
586       // Rational approximation for 0.5 > q >= 0.25
587       //
588       // x = sqrt(-2*log(q)) / (Y + R(q))
589       //
590       // Where Y is a constant, and R(q) is optimised for a low
591       // absolute empfr_classor compared to Y.
592       //
593       // double : Max empfr_classor found: 7.403372e-17
594       // long double : Max empfr_classor found: 6.084616e-20
595       // Maximum Deviation Found (empfr_classor term) 4.811e-20
596       //
597       static const float Y = 2.249481201171875f;
598       static const mpfr_class P[] = {
599          -0.202433508355938759655,
600          0.105264680699391713268,
601          8.37050328343119927838,
602          17.6447298408374015486,
603          -18.8510648058714251895,
604          -44.6382324441786960818,
605          17.445385985570866523,
606          21.1294655448340526258,
607          -3.67192254707729348546
608       };
609       static const mpfr_class Q[] = {
610          1,
611          6.24264124854247537712,
612          3.9713437953343869095,
613          -28.6608180499800029974,
614          -20.1432634680485188801,
615          48.5609213108739935468,
616          10.8268667355460159008,
617          -22.6436933413139721736,
618          1.72114765761200282724
619       };
620       mpfr_class g = sqrt(-2 * log(q));
621       mpfr_class xs = q - 0.25;
622       mpfr_class r = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs);
623       result = g / (Y + r);
624    }
625    else
626    {
627       //
628       // For q < 0.25 we have a series of rational approximations all
629       // of the general form:
630       //
631       // let: x = sqrt(-log(q))
632       //
633       // Then the result is given by:
634       //
635       // x(Y+R(x-B))
636       //
637       // where Y is a constant, B is the lowest value of x for which
638       // the approximation is valid, and R(x-B) is optimised for a low
639       // absolute empfr_classor compared to Y.
640       //
641       // Note that almost all code will really go through the first
642       // or maybe second approximation.  After than we're dealing with very
643       // small input values indeed: 80 and 128 bit long double's go all the
644       // way down to ~ 1e-5000 so the "tail" is rather long...
645       //
646       mpfr_class x = sqrt(-log(q));
647       if(x < 3)
648       {
649          // Max empfr_classor found: 1.089051e-20
650          static const float Y = 0.807220458984375f;
651          static const mpfr_class P[] = {
652             -0.131102781679951906451,
653             -0.163794047193317060787,
654             0.117030156341995252019,
655             0.387079738972604337464,
656             0.337785538912035898924,
657             0.142869534408157156766,
658             0.0290157910005329060432,
659             0.00214558995388805277169,
660             -0.679465575181126350155e-6,
661             0.285225331782217055858e-7,
662             -0.681149956853776992068e-9
663          };
664          static const mpfr_class Q[] = {
665             1,
666             3.46625407242567245975,
667             5.38168345707006855425,
668             4.77846592945843778382,
669             2.59301921623620271374,
670             0.848854343457902036425,
671             0.152264338295331783612,
672             0.01105924229346489121
673          };
674          mpfr_class xs = x - 1.125;
675          mpfr_class R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs);
676          result = Y * x + R * x;
677       }
678       else if(x < 6)
679       {
680          // Max empfr_classor found: 8.389174e-21
681          static const float Y = 0.93995571136474609375f;
682          static const mpfr_class P[] = {
683             -0.0350353787183177984712,
684             -0.00222426529213447927281,
685             0.0185573306514231072324,
686             0.00950804701325919603619,
687             0.00187123492819559223345,
688             0.000157544617424960554631,
689             0.460469890584317994083e-5,
690             -0.230404776911882601748e-9,
691             0.266339227425782031962e-11
692          };
693          static const mpfr_class Q[] = {
694             1,
695             1.3653349817554063097,
696             0.762059164553623404043,
697             0.220091105764131249824,
698             0.0341589143670947727934,
699             0.00263861676657015992959,
700             0.764675292302794483503e-4
701          };
702          mpfr_class xs = x - 3;
703          mpfr_class R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs);
704          result = Y * x + R * x;
705       }
706       else if(x < 18)
707       {
708          // Max empfr_classor found: 1.481312e-19
709          static const float Y = 0.98362827301025390625f;
710          static const mpfr_class P[] = {
711             -0.0167431005076633737133,
712             -0.00112951438745580278863,
713             0.00105628862152492910091,
714             0.000209386317487588078668,
715             0.149624783758342370182e-4,
716             0.449696789927706453732e-6,
717             0.462596163522878599135e-8,
718             -0.281128735628831791805e-13,
719             0.99055709973310326855e-16
720          };
721          static const mpfr_class Q[] = {
722             1,
723             0.591429344886417493481,
724             0.138151865749083321638,
725             0.0160746087093676504695,
726             0.000964011807005165528527,
727             0.275335474764726041141e-4,
728             0.282243172016108031869e-6
729          };
730          mpfr_class xs = x - 6;
731          mpfr_class R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs);
732          result = Y * x + R * x;
733       }
734       else if(x < 44)
735       {
736          // Max empfr_classor found: 5.697761e-20
737          static const float Y = 0.99714565277099609375f;
738          static const mpfr_class P[] = {
739             -0.0024978212791898131227,
740             -0.779190719229053954292e-5,
741             0.254723037413027451751e-4,
742             0.162397777342510920873e-5,
743             0.396341011304801168516e-7,
744             0.411632831190944208473e-9,
745             0.145596286718675035587e-11,
746             -0.116765012397184275695e-17
747          };
748          static const mpfr_class Q[] = {
749             1,
750             0.207123112214422517181,
751             0.0169410838120975906478,
752             0.000690538265622684595676,
753             0.145007359818232637924e-4,
754             0.144437756628144157666e-6,
755             0.509761276599778486139e-9
756          };
757          mpfr_class xs = x - 18;
758          mpfr_class R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs);
759          result = Y * x + R * x;
760       }
761       else
762       {
763          // Max empfr_classor found: 1.279746e-20
764          static const float Y = 0.99941349029541015625f;
765          static const mpfr_class P[] = {
766             -0.000539042911019078575891,
767             -0.28398759004727721098e-6,
768             0.899465114892291446442e-6,
769             0.229345859265920864296e-7,
770             0.225561444863500149219e-9,
771             0.947846627503022684216e-12,
772             0.135880130108924861008e-14,
773             -0.348890393399948882918e-21
774          };
775          static const mpfr_class Q[] = {
776             1,
777             0.0845746234001899436914,
778             0.00282092984726264681981,
779             0.468292921940894236786e-4,
780             0.399968812193862100054e-6,
781             0.161809290887904476097e-8,
782             0.231558608310259605225e-11
783          };
784          mpfr_class xs = x - 44;
785          mpfr_class R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs);
786          result = Y * x + R * x;
787       }
788    }
789    return result;
790 }
791 
bessel_i0(mpfr_class x)792 inline mpfr_class bessel_i0(mpfr_class x)
793 {
794     static const mpfr_class P1[] = {
795         boost::lexical_cast<mpfr_class>("-2.2335582639474375249e+15"),
796         boost::lexical_cast<mpfr_class>("-5.5050369673018427753e+14"),
797         boost::lexical_cast<mpfr_class>("-3.2940087627407749166e+13"),
798         boost::lexical_cast<mpfr_class>("-8.4925101247114157499e+11"),
799         boost::lexical_cast<mpfr_class>("-1.1912746104985237192e+10"),
800         boost::lexical_cast<mpfr_class>("-1.0313066708737980747e+08"),
801         boost::lexical_cast<mpfr_class>("-5.9545626019847898221e+05"),
802         boost::lexical_cast<mpfr_class>("-2.4125195876041896775e+03"),
803         boost::lexical_cast<mpfr_class>("-7.0935347449210549190e+00"),
804         boost::lexical_cast<mpfr_class>("-1.5453977791786851041e-02"),
805         boost::lexical_cast<mpfr_class>("-2.5172644670688975051e-05"),
806         boost::lexical_cast<mpfr_class>("-3.0517226450451067446e-08"),
807         boost::lexical_cast<mpfr_class>("-2.6843448573468483278e-11"),
808         boost::lexical_cast<mpfr_class>("-1.5982226675653184646e-14"),
809         boost::lexical_cast<mpfr_class>("-5.2487866627945699800e-18"),
810     };
811     static const mpfr_class Q1[] = {
812         boost::lexical_cast<mpfr_class>("-2.2335582639474375245e+15"),
813         boost::lexical_cast<mpfr_class>("7.8858692566751002988e+12"),
814         boost::lexical_cast<mpfr_class>("-1.2207067397808979846e+10"),
815         boost::lexical_cast<mpfr_class>("1.0377081058062166144e+07"),
816         boost::lexical_cast<mpfr_class>("-4.8527560179962773045e+03"),
817         boost::lexical_cast<mpfr_class>("1.0"),
818     };
819     static const mpfr_class P2[] = {
820         boost::lexical_cast<mpfr_class>("-2.2210262233306573296e-04"),
821         boost::lexical_cast<mpfr_class>("1.3067392038106924055e-02"),
822         boost::lexical_cast<mpfr_class>("-4.4700805721174453923e-01"),
823         boost::lexical_cast<mpfr_class>("5.5674518371240761397e+00"),
824         boost::lexical_cast<mpfr_class>("-2.3517945679239481621e+01"),
825         boost::lexical_cast<mpfr_class>("3.1611322818701131207e+01"),
826         boost::lexical_cast<mpfr_class>("-9.6090021968656180000e+00"),
827     };
828     static const mpfr_class Q2[] = {
829         boost::lexical_cast<mpfr_class>("-5.5194330231005480228e-04"),
830         boost::lexical_cast<mpfr_class>("3.2547697594819615062e-02"),
831         boost::lexical_cast<mpfr_class>("-1.1151759188741312645e+00"),
832         boost::lexical_cast<mpfr_class>("1.3982595353892851542e+01"),
833         boost::lexical_cast<mpfr_class>("-6.0228002066743340583e+01"),
834         boost::lexical_cast<mpfr_class>("8.5539563258012929600e+01"),
835         boost::lexical_cast<mpfr_class>("-3.1446690275135491500e+01"),
836         boost::lexical_cast<mpfr_class>("1.0"),
837     };
838     mpfr_class value, factor, r;
839 
840     BOOST_MATH_STD_USING
841     using namespace boost::math::tools;
842 
843     if (x < 0)
844     {
845         x = -x;                         // even function
846     }
847     if (x == 0)
848     {
849         return static_cast<mpfr_class>(1);
850     }
851     if (x <= 15)                        // x in (0, 15]
852     {
853         mpfr_class y = x * x;
854         value = evaluate_polynomial(P1, y) / evaluate_polynomial(Q1, y);
855     }
856     else                                // x in (15, \infty)
857     {
858         mpfr_class y = 1 / x - mpfr_class(1) / 15;
859         r = evaluate_polynomial(P2, y) / evaluate_polynomial(Q2, y);
860         factor = exp(x) / sqrt(x);
861         value = factor * r;
862     }
863 
864     return value;
865 }
866 
bessel_i1(mpfr_class x)867 inline mpfr_class bessel_i1(mpfr_class x)
868 {
869     static const mpfr_class P1[] = {
870         static_cast<mpfr_class>("-1.4577180278143463643e+15"),
871         static_cast<mpfr_class>("-1.7732037840791591320e+14"),
872         static_cast<mpfr_class>("-6.9876779648010090070e+12"),
873         static_cast<mpfr_class>("-1.3357437682275493024e+11"),
874         static_cast<mpfr_class>("-1.4828267606612366099e+09"),
875         static_cast<mpfr_class>("-1.0588550724769347106e+07"),
876         static_cast<mpfr_class>("-5.1894091982308017540e+04"),
877         static_cast<mpfr_class>("-1.8225946631657315931e+02"),
878         static_cast<mpfr_class>("-4.7207090827310162436e-01"),
879         static_cast<mpfr_class>("-9.1746443287817501309e-04"),
880         static_cast<mpfr_class>("-1.3466829827635152875e-06"),
881         static_cast<mpfr_class>("-1.4831904935994647675e-09"),
882         static_cast<mpfr_class>("-1.1928788903603238754e-12"),
883         static_cast<mpfr_class>("-6.5245515583151902910e-16"),
884         static_cast<mpfr_class>("-1.9705291802535139930e-19"),
885     };
886     static const mpfr_class Q1[] = {
887         static_cast<mpfr_class>("-2.9154360556286927285e+15"),
888         static_cast<mpfr_class>("9.7887501377547640438e+12"),
889         static_cast<mpfr_class>("-1.4386907088588283434e+10"),
890         static_cast<mpfr_class>("1.1594225856856884006e+07"),
891         static_cast<mpfr_class>("-5.1326864679904189920e+03"),
892         static_cast<mpfr_class>("1.0"),
893     };
894     static const mpfr_class P2[] = {
895         static_cast<mpfr_class>("1.4582087408985668208e-05"),
896         static_cast<mpfr_class>("-8.9359825138577646443e-04"),
897         static_cast<mpfr_class>("2.9204895411257790122e-02"),
898         static_cast<mpfr_class>("-3.4198728018058047439e-01"),
899         static_cast<mpfr_class>("1.3960118277609544334e+00"),
900         static_cast<mpfr_class>("-1.9746376087200685843e+00"),
901         static_cast<mpfr_class>("8.5591872901933459000e-01"),
902         static_cast<mpfr_class>("-6.0437159056137599999e-02"),
903     };
904     static const mpfr_class Q2[] = {
905         static_cast<mpfr_class>("3.7510433111922824643e-05"),
906         static_cast<mpfr_class>("-2.2835624489492512649e-03"),
907         static_cast<mpfr_class>("7.4212010813186530069e-02"),
908         static_cast<mpfr_class>("-8.5017476463217924408e-01"),
909         static_cast<mpfr_class>("3.2593714889036996297e+00"),
910         static_cast<mpfr_class>("-3.8806586721556593450e+00"),
911         static_cast<mpfr_class>("1.0"),
912     };
913     mpfr_class value, factor, r, w;
914 
915     BOOST_MATH_STD_USING
916     using namespace boost::math::tools;
917 
918     w = abs(x);
919     if (x == 0)
920     {
921         return static_cast<mpfr_class>(0);
922     }
923     if (w <= 15)                        // w in (0, 15]
924     {
925         mpfr_class y = x * x;
926         r = evaluate_polynomial(P1, y) / evaluate_polynomial(Q1, y);
927         factor = w;
928         value = factor * r;
929     }
930     else                                // w in (15, \infty)
931     {
932         mpfr_class y = 1 / w - mpfr_class(1) / 15;
933         r = evaluate_polynomial(P2, y) / evaluate_polynomial(Q2, y);
934         factor = exp(w) / sqrt(w);
935         value = factor * r;
936     }
937 
938     if (x < 0)
939     {
940         value *= -value;                 // odd function
941     }
942     return value;
943 }
944 
945 } // namespace detail
946 
947 }
948 
949 template<> struct is_convertible<long double, mpfr_class> : public mpl::false_{};
950 
951 }
952 
953 #endif // BOOST_MATH_MPLFR_BINDINGS_HPP
954 
955