mpfr.hpp 30 KB

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  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. #ifndef BOOST_MATH_MPLFR_BINDINGS_HPP
  11. #define BOOST_MATH_MPLFR_BINDINGS_HPP
  12. #include <boost/config.hpp>
  13. #include <boost/lexical_cast.hpp>
  14. #ifdef BOOST_MSVC
  15. //
  16. // We get a lot of warnings from the gmp, mpfr and gmpfrxx headers,
  17. // disable them here, so we only see warnings from *our* code:
  18. //
  19. #pragma warning(push)
  20. #pragma warning(disable: 4127 4800 4512)
  21. #endif
  22. #include <gmpfrxx.h>
  23. #ifdef BOOST_MSVC
  24. #pragma warning(pop)
  25. #endif
  26. #include <boost/math/tools/precision.hpp>
  27. #include <boost/math/tools/real_cast.hpp>
  28. #include <boost/math/policies/policy.hpp>
  29. #include <boost/math/distributions/fwd.hpp>
  30. #include <boost/math/special_functions/math_fwd.hpp>
  31. #include <boost/math/bindings/detail/big_digamma.hpp>
  32. #include <boost/math/bindings/detail/big_lanczos.hpp>
  33. #include <boost/math/tools/big_constant.hpp>
  34. inline mpfr_class fabs(const mpfr_class& v)
  35. {
  36. return abs(v);
  37. }
  38. template <class T, class U>
  39. inline mpfr_class fabs(const __gmp_expr<T,U>& v)
  40. {
  41. return abs(static_cast<mpfr_class>(v));
  42. }
  43. inline mpfr_class pow(const mpfr_class& b, const mpfr_class& e)
  44. {
  45. mpfr_class result;
  46. mpfr_pow(result.__get_mp(), b.__get_mp(), e.__get_mp(), GMP_RNDN);
  47. return result;
  48. }
  49. /*
  50. template <class T, class U, class V, class W>
  51. inline mpfr_class pow(const __gmp_expr<T,U>& b, const __gmp_expr<V,W>& e)
  52. {
  53. return pow(static_cast<mpfr_class>(b), static_cast<mpfr_class>(e));
  54. }
  55. */
  56. inline mpfr_class ldexp(const mpfr_class& v, int e)
  57. {
  58. //int e = mpfr_get_exp(*v.__get_mp());
  59. mpfr_class result(v);
  60. mpfr_set_exp(result.__get_mp(), e);
  61. return result;
  62. }
  63. template <class T, class U>
  64. inline mpfr_class ldexp(const __gmp_expr<T,U>& v, int e)
  65. {
  66. return ldexp(static_cast<mpfr_class>(v), e);
  67. }
  68. inline mpfr_class frexp(const mpfr_class& v, int* expon)
  69. {
  70. int e = mpfr_get_exp(v.__get_mp());
  71. mpfr_class result(v);
  72. mpfr_set_exp(result.__get_mp(), 0);
  73. *expon = e;
  74. return result;
  75. }
  76. template <class T, class U>
  77. inline mpfr_class frexp(const __gmp_expr<T,U>& v, int* expon)
  78. {
  79. return frexp(static_cast<mpfr_class>(v), expon);
  80. }
  81. inline mpfr_class fmod(const mpfr_class& v1, const mpfr_class& v2)
  82. {
  83. mpfr_class n;
  84. if(v1 < 0)
  85. n = ceil(v1 / v2);
  86. else
  87. n = floor(v1 / v2);
  88. return v1 - n * v2;
  89. }
  90. template <class T, class U, class V, class W>
  91. inline mpfr_class fmod(const __gmp_expr<T,U>& v1, const __gmp_expr<V,W>& v2)
  92. {
  93. return fmod(static_cast<mpfr_class>(v1), static_cast<mpfr_class>(v2));
  94. }
  95. template <class Policy>
  96. inline mpfr_class modf(const mpfr_class& v, long long* ipart, const Policy& pol)
  97. {
  98. *ipart = lltrunc(v, pol);
  99. return v - boost::math::tools::real_cast<mpfr_class>(*ipart);
  100. }
  101. template <class T, class U, class Policy>
  102. inline mpfr_class modf(const __gmp_expr<T,U>& v, long long* ipart, const Policy& pol)
  103. {
  104. return modf(static_cast<mpfr_class>(v), ipart, pol);
  105. }
  106. template <class Policy>
  107. inline int iround(mpfr_class const& x, const Policy&)
  108. {
  109. 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()));
  110. }
  111. template <class T, class U, class Policy>
  112. inline int iround(__gmp_expr<T,U> const& x, const Policy& pol)
  113. {
  114. return iround(static_cast<mpfr_class>(x), pol);
  115. }
  116. template <class Policy>
  117. inline long lround(mpfr_class const& x, const Policy&)
  118. {
  119. 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()));
  120. }
  121. template <class T, class U, class Policy>
  122. inline long lround(__gmp_expr<T,U> const& x, const Policy& pol)
  123. {
  124. return lround(static_cast<mpfr_class>(x), pol);
  125. }
  126. template <class Policy>
  127. inline long long llround(mpfr_class const& x, const Policy&)
  128. {
  129. 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()));
  130. }
  131. template <class T, class U, class Policy>
  132. inline long long llround(__gmp_expr<T,U> const& x, const Policy& pol)
  133. {
  134. return llround(static_cast<mpfr_class>(x), pol);
  135. }
  136. template <class Policy>
  137. inline int itrunc(mpfr_class const& x, const Policy&)
  138. {
  139. 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()));
  140. }
  141. template <class T, class U, class Policy>
  142. inline int itrunc(__gmp_expr<T,U> const& x, const Policy& pol)
  143. {
  144. return itrunc(static_cast<mpfr_class>(x), pol);
  145. }
  146. template <class Policy>
  147. inline long ltrunc(mpfr_class const& x, const Policy&)
  148. {
  149. 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()));
  150. }
  151. template <class T, class U, class Policy>
  152. inline long ltrunc(__gmp_expr<T,U> const& x, const Policy& pol)
  153. {
  154. return ltrunc(static_cast<mpfr_class>(x), pol);
  155. }
  156. template <class Policy>
  157. inline long long lltrunc(mpfr_class const& x, const Policy&)
  158. {
  159. 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()));
  160. }
  161. template <class T, class U, class Policy>
  162. inline long long lltrunc(__gmp_expr<T,U> const& x, const Policy& pol)
  163. {
  164. return lltrunc(static_cast<mpfr_class>(x), pol);
  165. }
  166. namespace boost{
  167. #ifdef BOOST_MATH_USE_FLOAT128
  168. template<> struct is_convertible<BOOST_MATH_FLOAT128_TYPE, mpfr_class> : public boost::integral_constant<bool, false>{};
  169. #endif
  170. template<> struct is_convertible<long long, mpfr_class> : public boost::integral_constant<bool, false>{};
  171. namespace math{
  172. #if defined(__GNUC__) && (__GNUC__ < 4)
  173. using ::iround;
  174. using ::lround;
  175. using ::llround;
  176. using ::itrunc;
  177. using ::ltrunc;
  178. using ::lltrunc;
  179. using ::modf;
  180. #endif
  181. namespace lanczos{
  182. struct mpfr_lanczos
  183. {
  184. static mpfr_class lanczos_sum(const mpfr_class& z)
  185. {
  186. unsigned long p = z.get_dprec();
  187. if(p <= 72)
  188. return lanczos13UDT::lanczos_sum(z);
  189. else if(p <= 120)
  190. return lanczos22UDT::lanczos_sum(z);
  191. else if(p <= 170)
  192. return lanczos31UDT::lanczos_sum(z);
  193. else //if(p <= 370) approx 100 digit precision:
  194. return lanczos61UDT::lanczos_sum(z);
  195. }
  196. static mpfr_class lanczos_sum_expG_scaled(const mpfr_class& z)
  197. {
  198. unsigned long p = z.get_dprec();
  199. if(p <= 72)
  200. return lanczos13UDT::lanczos_sum_expG_scaled(z);
  201. else if(p <= 120)
  202. return lanczos22UDT::lanczos_sum_expG_scaled(z);
  203. else if(p <= 170)
  204. return lanczos31UDT::lanczos_sum_expG_scaled(z);
  205. else //if(p <= 370) approx 100 digit precision:
  206. return lanczos61UDT::lanczos_sum_expG_scaled(z);
  207. }
  208. static mpfr_class lanczos_sum_near_1(const mpfr_class& z)
  209. {
  210. unsigned long p = z.get_dprec();
  211. if(p <= 72)
  212. return lanczos13UDT::lanczos_sum_near_1(z);
  213. else if(p <= 120)
  214. return lanczos22UDT::lanczos_sum_near_1(z);
  215. else if(p <= 170)
  216. return lanczos31UDT::lanczos_sum_near_1(z);
  217. else //if(p <= 370) approx 100 digit precision:
  218. return lanczos61UDT::lanczos_sum_near_1(z);
  219. }
  220. static mpfr_class lanczos_sum_near_2(const mpfr_class& z)
  221. {
  222. unsigned long p = z.get_dprec();
  223. if(p <= 72)
  224. return lanczos13UDT::lanczos_sum_near_2(z);
  225. else if(p <= 120)
  226. return lanczos22UDT::lanczos_sum_near_2(z);
  227. else if(p <= 170)
  228. return lanczos31UDT::lanczos_sum_near_2(z);
  229. else //if(p <= 370) approx 100 digit precision:
  230. return lanczos61UDT::lanczos_sum_near_2(z);
  231. }
  232. static mpfr_class g()
  233. {
  234. unsigned long p = mpfr_class::get_dprec();
  235. if(p <= 72)
  236. return lanczos13UDT::g();
  237. else if(p <= 120)
  238. return lanczos22UDT::g();
  239. else if(p <= 170)
  240. return lanczos31UDT::g();
  241. else //if(p <= 370) approx 100 digit precision:
  242. return lanczos61UDT::g();
  243. }
  244. };
  245. template<class Policy>
  246. struct lanczos<mpfr_class, Policy>
  247. {
  248. typedef mpfr_lanczos type;
  249. };
  250. } // namespace lanczos
  251. namespace constants{
  252. template <class Real, class Policy>
  253. struct construction_traits;
  254. template <class Policy>
  255. struct construction_traits<mpfr_class, Policy>
  256. {
  257. typedef mpl::int_<0> type;
  258. };
  259. }
  260. namespace tools
  261. {
  262. template <class T, class U>
  263. struct promote_arg<__gmp_expr<T,U> >
  264. { // If T is integral type, then promote to double.
  265. typedef mpfr_class type;
  266. };
  267. template<>
  268. inline int digits<mpfr_class>(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr_class)) BOOST_NOEXCEPT
  269. {
  270. return mpfr_class::get_dprec();
  271. }
  272. namespace detail{
  273. template<class I>
  274. void convert_to_long_result(mpfr_class const& r, I& result)
  275. {
  276. result = 0;
  277. I last_result(0);
  278. mpfr_class t(r);
  279. double term;
  280. do
  281. {
  282. term = real_cast<double>(t);
  283. last_result = result;
  284. result += static_cast<I>(term);
  285. t -= term;
  286. }while(result != last_result);
  287. }
  288. }
  289. template <>
  290. inline mpfr_class real_cast<mpfr_class, long long>(long long t)
  291. {
  292. mpfr_class result;
  293. int expon = 0;
  294. int sign = 1;
  295. if(t < 0)
  296. {
  297. sign = -1;
  298. t = -t;
  299. }
  300. while(t)
  301. {
  302. result += ldexp((double)(t & 0xffffL), expon);
  303. expon += 32;
  304. t >>= 32;
  305. }
  306. return result * sign;
  307. }
  308. template <>
  309. inline unsigned real_cast<unsigned, mpfr_class>(mpfr_class t)
  310. {
  311. return t.get_ui();
  312. }
  313. template <>
  314. inline int real_cast<int, mpfr_class>(mpfr_class t)
  315. {
  316. return t.get_si();
  317. }
  318. template <>
  319. inline double real_cast<double, mpfr_class>(mpfr_class t)
  320. {
  321. return t.get_d();
  322. }
  323. template <>
  324. inline float real_cast<float, mpfr_class>(mpfr_class t)
  325. {
  326. return static_cast<float>(t.get_d());
  327. }
  328. template <>
  329. inline long real_cast<long, mpfr_class>(mpfr_class t)
  330. {
  331. long result;
  332. detail::convert_to_long_result(t, result);
  333. return result;
  334. }
  335. template <>
  336. inline long long real_cast<long long, mpfr_class>(mpfr_class t)
  337. {
  338. long long result;
  339. detail::convert_to_long_result(t, result);
  340. return result;
  341. }
  342. template <>
  343. inline mpfr_class max_value<mpfr_class>(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr_class))
  344. {
  345. static bool has_init = false;
  346. static mpfr_class val;
  347. if(!has_init)
  348. {
  349. val = 0.5;
  350. mpfr_set_exp(val.__get_mp(), mpfr_get_emax());
  351. has_init = true;
  352. }
  353. return val;
  354. }
  355. template <>
  356. inline mpfr_class min_value<mpfr_class>(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr_class))
  357. {
  358. static bool has_init = false;
  359. static mpfr_class val;
  360. if(!has_init)
  361. {
  362. val = 0.5;
  363. mpfr_set_exp(val.__get_mp(), mpfr_get_emin());
  364. has_init = true;
  365. }
  366. return val;
  367. }
  368. template <>
  369. inline mpfr_class log_max_value<mpfr_class>(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr_class))
  370. {
  371. static bool has_init = false;
  372. static mpfr_class val = max_value<mpfr_class>();
  373. if(!has_init)
  374. {
  375. val = log(val);
  376. has_init = true;
  377. }
  378. return val;
  379. }
  380. template <>
  381. inline mpfr_class log_min_value<mpfr_class>(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr_class))
  382. {
  383. static bool has_init = false;
  384. static mpfr_class val = max_value<mpfr_class>();
  385. if(!has_init)
  386. {
  387. val = log(val);
  388. has_init = true;
  389. }
  390. return val;
  391. }
  392. template <>
  393. inline mpfr_class epsilon<mpfr_class>(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(mpfr_class))
  394. {
  395. return ldexp(mpfr_class(1), 1-boost::math::policies::digits<mpfr_class, boost::math::policies::policy<> >());
  396. }
  397. } // namespace tools
  398. namespace policies{
  399. template <class T, class U, class Policy>
  400. struct evaluation<__gmp_expr<T, U>, Policy>
  401. {
  402. typedef mpfr_class type;
  403. };
  404. }
  405. template <class Policy>
  406. inline mpfr_class skewness(const extreme_value_distribution<mpfr_class, Policy>& /*dist*/)
  407. {
  408. //
  409. // This is 12 * sqrt(6) * zeta(3) / pi^3:
  410. // See http://mathworld.wolfram.com/ExtremeValueDistribution.html
  411. //
  412. return boost::lexical_cast<mpfr_class>("1.1395470994046486574927930193898461120875997958366");
  413. }
  414. template <class Policy>
  415. inline mpfr_class skewness(const rayleigh_distribution<mpfr_class, Policy>& /*dist*/)
  416. {
  417. // using namespace boost::math::constants;
  418. return boost::lexical_cast<mpfr_class>("0.63111065781893713819189935154422777984404221106391");
  419. // Computed using NTL at 150 bit, about 50 decimal digits.
  420. // return 2 * root_pi<RealType>() * pi_minus_three<RealType>() / pow23_four_minus_pi<RealType>();
  421. }
  422. template <class Policy>
  423. inline mpfr_class kurtosis(const rayleigh_distribution<mpfr_class, Policy>& /*dist*/)
  424. {
  425. // using namespace boost::math::constants;
  426. return boost::lexical_cast<mpfr_class>("3.2450893006876380628486604106197544154170667057995");
  427. // Computed using NTL at 150 bit, about 50 decimal digits.
  428. // return 3 - (6 * pi<RealType>() * pi<RealType>() - 24 * pi<RealType>() + 16) /
  429. // (four_minus_pi<RealType>() * four_minus_pi<RealType>());
  430. }
  431. template <class Policy>
  432. inline mpfr_class kurtosis_excess(const rayleigh_distribution<mpfr_class, Policy>& /*dist*/)
  433. {
  434. //using namespace boost::math::constants;
  435. // Computed using NTL at 150 bit, about 50 decimal digits.
  436. return boost::lexical_cast<mpfr_class>("0.2450893006876380628486604106197544154170667057995");
  437. // return -(6 * pi<RealType>() * pi<RealType>() - 24 * pi<RealType>() + 16) /
  438. // (four_minus_pi<RealType>() * four_minus_pi<RealType>());
  439. } // kurtosis
  440. namespace detail{
  441. //
  442. // Version of Digamma accurate to ~100 decimal digits.
  443. //
  444. template <class Policy>
  445. mpfr_class digamma_imp(mpfr_class x, const mpl::int_<0>* , const Policy& pol)
  446. {
  447. //
  448. // This handles reflection of negative arguments, and all our
  449. // empfr_classor handling, then forwards to the T-specific approximation.
  450. //
  451. BOOST_MATH_STD_USING // ADL of std functions.
  452. mpfr_class result = 0;
  453. //
  454. // Check for negative arguments and use reflection:
  455. //
  456. if(x < 0)
  457. {
  458. // Reflect:
  459. x = 1 - x;
  460. // Argument reduction for tan:
  461. mpfr_class remainder = x - floor(x);
  462. // Shift to negative if > 0.5:
  463. if(remainder > 0.5)
  464. {
  465. remainder -= 1;
  466. }
  467. //
  468. // check for evaluation at a negative pole:
  469. //
  470. if(remainder == 0)
  471. {
  472. return policies::raise_pole_error<mpfr_class>("boost::math::digamma<%1%>(%1%)", 0, (1-x), pol);
  473. }
  474. result = constants::pi<mpfr_class>() / tan(constants::pi<mpfr_class>() * remainder);
  475. }
  476. result += big_digamma(x);
  477. return result;
  478. }
  479. //
  480. // Specialisations of this function provides the initial
  481. // starting guess for Halley iteration:
  482. //
  483. template <class Policy>
  484. inline mpfr_class erf_inv_imp(const mpfr_class& p, const mpfr_class& q, const Policy&, const boost::mpl::int_<64>*)
  485. {
  486. BOOST_MATH_STD_USING // for ADL of std names.
  487. mpfr_class result = 0;
  488. if(p <= 0.5)
  489. {
  490. //
  491. // Evaluate inverse erf using the rational approximation:
  492. //
  493. // x = p(p+10)(Y+R(p))
  494. //
  495. // Where Y is a constant, and R(p) is optimised for a low
  496. // absolute empfr_classor compared to |Y|.
  497. //
  498. // double: Max empfr_classor found: 2.001849e-18
  499. // long double: Max empfr_classor found: 1.017064e-20
  500. // Maximum Deviation Found (actual empfr_classor term at infinite precision) 8.030e-21
  501. //
  502. static const float Y = 0.0891314744949340820313f;
  503. static const mpfr_class P[] = {
  504. -0.000508781949658280665617,
  505. -0.00836874819741736770379,
  506. 0.0334806625409744615033,
  507. -0.0126926147662974029034,
  508. -0.0365637971411762664006,
  509. 0.0219878681111168899165,
  510. 0.00822687874676915743155,
  511. -0.00538772965071242932965
  512. };
  513. static const mpfr_class Q[] = {
  514. 1,
  515. -0.970005043303290640362,
  516. -1.56574558234175846809,
  517. 1.56221558398423026363,
  518. 0.662328840472002992063,
  519. -0.71228902341542847553,
  520. -0.0527396382340099713954,
  521. 0.0795283687341571680018,
  522. -0.00233393759374190016776,
  523. 0.000886216390456424707504
  524. };
  525. mpfr_class g = p * (p + 10);
  526. mpfr_class r = tools::evaluate_polynomial(P, p) / tools::evaluate_polynomial(Q, p);
  527. result = g * Y + g * r;
  528. }
  529. else if(q >= 0.25)
  530. {
  531. //
  532. // Rational approximation for 0.5 > q >= 0.25
  533. //
  534. // x = sqrt(-2*log(q)) / (Y + R(q))
  535. //
  536. // Where Y is a constant, and R(q) is optimised for a low
  537. // absolute empfr_classor compared to Y.
  538. //
  539. // double : Max empfr_classor found: 7.403372e-17
  540. // long double : Max empfr_classor found: 6.084616e-20
  541. // Maximum Deviation Found (empfr_classor term) 4.811e-20
  542. //
  543. static const float Y = 2.249481201171875f;
  544. static const mpfr_class P[] = {
  545. -0.202433508355938759655,
  546. 0.105264680699391713268,
  547. 8.37050328343119927838,
  548. 17.6447298408374015486,
  549. -18.8510648058714251895,
  550. -44.6382324441786960818,
  551. 17.445385985570866523,
  552. 21.1294655448340526258,
  553. -3.67192254707729348546
  554. };
  555. static const mpfr_class Q[] = {
  556. 1,
  557. 6.24264124854247537712,
  558. 3.9713437953343869095,
  559. -28.6608180499800029974,
  560. -20.1432634680485188801,
  561. 48.5609213108739935468,
  562. 10.8268667355460159008,
  563. -22.6436933413139721736,
  564. 1.72114765761200282724
  565. };
  566. mpfr_class g = sqrt(-2 * log(q));
  567. mpfr_class xs = q - 0.25;
  568. mpfr_class r = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs);
  569. result = g / (Y + r);
  570. }
  571. else
  572. {
  573. //
  574. // For q < 0.25 we have a series of rational approximations all
  575. // of the general form:
  576. //
  577. // let: x = sqrt(-log(q))
  578. //
  579. // Then the result is given by:
  580. //
  581. // x(Y+R(x-B))
  582. //
  583. // where Y is a constant, B is the lowest value of x for which
  584. // the approximation is valid, and R(x-B) is optimised for a low
  585. // absolute empfr_classor compared to Y.
  586. //
  587. // Note that almost all code will really go through the first
  588. // or maybe second approximation. After than we're dealing with very
  589. // small input values indeed: 80 and 128 bit long double's go all the
  590. // way down to ~ 1e-5000 so the "tail" is rather long...
  591. //
  592. mpfr_class x = sqrt(-log(q));
  593. if(x < 3)
  594. {
  595. // Max empfr_classor found: 1.089051e-20
  596. static const float Y = 0.807220458984375f;
  597. static const mpfr_class P[] = {
  598. -0.131102781679951906451,
  599. -0.163794047193317060787,
  600. 0.117030156341995252019,
  601. 0.387079738972604337464,
  602. 0.337785538912035898924,
  603. 0.142869534408157156766,
  604. 0.0290157910005329060432,
  605. 0.00214558995388805277169,
  606. -0.679465575181126350155e-6,
  607. 0.285225331782217055858e-7,
  608. -0.681149956853776992068e-9
  609. };
  610. static const mpfr_class Q[] = {
  611. 1,
  612. 3.46625407242567245975,
  613. 5.38168345707006855425,
  614. 4.77846592945843778382,
  615. 2.59301921623620271374,
  616. 0.848854343457902036425,
  617. 0.152264338295331783612,
  618. 0.01105924229346489121
  619. };
  620. mpfr_class xs = x - 1.125;
  621. mpfr_class R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs);
  622. result = Y * x + R * x;
  623. }
  624. else if(x < 6)
  625. {
  626. // Max empfr_classor found: 8.389174e-21
  627. static const float Y = 0.93995571136474609375f;
  628. static const mpfr_class P[] = {
  629. -0.0350353787183177984712,
  630. -0.00222426529213447927281,
  631. 0.0185573306514231072324,
  632. 0.00950804701325919603619,
  633. 0.00187123492819559223345,
  634. 0.000157544617424960554631,
  635. 0.460469890584317994083e-5,
  636. -0.230404776911882601748e-9,
  637. 0.266339227425782031962e-11
  638. };
  639. static const mpfr_class Q[] = {
  640. 1,
  641. 1.3653349817554063097,
  642. 0.762059164553623404043,
  643. 0.220091105764131249824,
  644. 0.0341589143670947727934,
  645. 0.00263861676657015992959,
  646. 0.764675292302794483503e-4
  647. };
  648. mpfr_class xs = x - 3;
  649. mpfr_class R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs);
  650. result = Y * x + R * x;
  651. }
  652. else if(x < 18)
  653. {
  654. // Max empfr_classor found: 1.481312e-19
  655. static const float Y = 0.98362827301025390625f;
  656. static const mpfr_class P[] = {
  657. -0.0167431005076633737133,
  658. -0.00112951438745580278863,
  659. 0.00105628862152492910091,
  660. 0.000209386317487588078668,
  661. 0.149624783758342370182e-4,
  662. 0.449696789927706453732e-6,
  663. 0.462596163522878599135e-8,
  664. -0.281128735628831791805e-13,
  665. 0.99055709973310326855e-16
  666. };
  667. static const mpfr_class Q[] = {
  668. 1,
  669. 0.591429344886417493481,
  670. 0.138151865749083321638,
  671. 0.0160746087093676504695,
  672. 0.000964011807005165528527,
  673. 0.275335474764726041141e-4,
  674. 0.282243172016108031869e-6
  675. };
  676. mpfr_class xs = x - 6;
  677. mpfr_class R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs);
  678. result = Y * x + R * x;
  679. }
  680. else if(x < 44)
  681. {
  682. // Max empfr_classor found: 5.697761e-20
  683. static const float Y = 0.99714565277099609375f;
  684. static const mpfr_class P[] = {
  685. -0.0024978212791898131227,
  686. -0.779190719229053954292e-5,
  687. 0.254723037413027451751e-4,
  688. 0.162397777342510920873e-5,
  689. 0.396341011304801168516e-7,
  690. 0.411632831190944208473e-9,
  691. 0.145596286718675035587e-11,
  692. -0.116765012397184275695e-17
  693. };
  694. static const mpfr_class Q[] = {
  695. 1,
  696. 0.207123112214422517181,
  697. 0.0169410838120975906478,
  698. 0.000690538265622684595676,
  699. 0.145007359818232637924e-4,
  700. 0.144437756628144157666e-6,
  701. 0.509761276599778486139e-9
  702. };
  703. mpfr_class xs = x - 18;
  704. mpfr_class R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs);
  705. result = Y * x + R * x;
  706. }
  707. else
  708. {
  709. // Max empfr_classor found: 1.279746e-20
  710. static const float Y = 0.99941349029541015625f;
  711. static const mpfr_class P[] = {
  712. -0.000539042911019078575891,
  713. -0.28398759004727721098e-6,
  714. 0.899465114892291446442e-6,
  715. 0.229345859265920864296e-7,
  716. 0.225561444863500149219e-9,
  717. 0.947846627503022684216e-12,
  718. 0.135880130108924861008e-14,
  719. -0.348890393399948882918e-21
  720. };
  721. static const mpfr_class Q[] = {
  722. 1,
  723. 0.0845746234001899436914,
  724. 0.00282092984726264681981,
  725. 0.468292921940894236786e-4,
  726. 0.399968812193862100054e-6,
  727. 0.161809290887904476097e-8,
  728. 0.231558608310259605225e-11
  729. };
  730. mpfr_class xs = x - 44;
  731. mpfr_class R = tools::evaluate_polynomial(P, xs) / tools::evaluate_polynomial(Q, xs);
  732. result = Y * x + R * x;
  733. }
  734. }
  735. return result;
  736. }
  737. inline mpfr_class bessel_i0(mpfr_class x)
  738. {
  739. static const mpfr_class P1[] = {
  740. boost::lexical_cast<mpfr_class>("-2.2335582639474375249e+15"),
  741. boost::lexical_cast<mpfr_class>("-5.5050369673018427753e+14"),
  742. boost::lexical_cast<mpfr_class>("-3.2940087627407749166e+13"),
  743. boost::lexical_cast<mpfr_class>("-8.4925101247114157499e+11"),
  744. boost::lexical_cast<mpfr_class>("-1.1912746104985237192e+10"),
  745. boost::lexical_cast<mpfr_class>("-1.0313066708737980747e+08"),
  746. boost::lexical_cast<mpfr_class>("-5.9545626019847898221e+05"),
  747. boost::lexical_cast<mpfr_class>("-2.4125195876041896775e+03"),
  748. boost::lexical_cast<mpfr_class>("-7.0935347449210549190e+00"),
  749. boost::lexical_cast<mpfr_class>("-1.5453977791786851041e-02"),
  750. boost::lexical_cast<mpfr_class>("-2.5172644670688975051e-05"),
  751. boost::lexical_cast<mpfr_class>("-3.0517226450451067446e-08"),
  752. boost::lexical_cast<mpfr_class>("-2.6843448573468483278e-11"),
  753. boost::lexical_cast<mpfr_class>("-1.5982226675653184646e-14"),
  754. boost::lexical_cast<mpfr_class>("-5.2487866627945699800e-18"),
  755. };
  756. static const mpfr_class Q1[] = {
  757. boost::lexical_cast<mpfr_class>("-2.2335582639474375245e+15"),
  758. boost::lexical_cast<mpfr_class>("7.8858692566751002988e+12"),
  759. boost::lexical_cast<mpfr_class>("-1.2207067397808979846e+10"),
  760. boost::lexical_cast<mpfr_class>("1.0377081058062166144e+07"),
  761. boost::lexical_cast<mpfr_class>("-4.8527560179962773045e+03"),
  762. boost::lexical_cast<mpfr_class>("1.0"),
  763. };
  764. static const mpfr_class P2[] = {
  765. boost::lexical_cast<mpfr_class>("-2.2210262233306573296e-04"),
  766. boost::lexical_cast<mpfr_class>("1.3067392038106924055e-02"),
  767. boost::lexical_cast<mpfr_class>("-4.4700805721174453923e-01"),
  768. boost::lexical_cast<mpfr_class>("5.5674518371240761397e+00"),
  769. boost::lexical_cast<mpfr_class>("-2.3517945679239481621e+01"),
  770. boost::lexical_cast<mpfr_class>("3.1611322818701131207e+01"),
  771. boost::lexical_cast<mpfr_class>("-9.6090021968656180000e+00"),
  772. };
  773. static const mpfr_class Q2[] = {
  774. boost::lexical_cast<mpfr_class>("-5.5194330231005480228e-04"),
  775. boost::lexical_cast<mpfr_class>("3.2547697594819615062e-02"),
  776. boost::lexical_cast<mpfr_class>("-1.1151759188741312645e+00"),
  777. boost::lexical_cast<mpfr_class>("1.3982595353892851542e+01"),
  778. boost::lexical_cast<mpfr_class>("-6.0228002066743340583e+01"),
  779. boost::lexical_cast<mpfr_class>("8.5539563258012929600e+01"),
  780. boost::lexical_cast<mpfr_class>("-3.1446690275135491500e+01"),
  781. boost::lexical_cast<mpfr_class>("1.0"),
  782. };
  783. mpfr_class value, factor, r;
  784. BOOST_MATH_STD_USING
  785. using namespace boost::math::tools;
  786. if (x < 0)
  787. {
  788. x = -x; // even function
  789. }
  790. if (x == 0)
  791. {
  792. return static_cast<mpfr_class>(1);
  793. }
  794. if (x <= 15) // x in (0, 15]
  795. {
  796. mpfr_class y = x * x;
  797. value = evaluate_polynomial(P1, y) / evaluate_polynomial(Q1, y);
  798. }
  799. else // x in (15, \infty)
  800. {
  801. mpfr_class y = 1 / x - mpfr_class(1) / 15;
  802. r = evaluate_polynomial(P2, y) / evaluate_polynomial(Q2, y);
  803. factor = exp(x) / sqrt(x);
  804. value = factor * r;
  805. }
  806. return value;
  807. }
  808. inline mpfr_class bessel_i1(mpfr_class x)
  809. {
  810. static const mpfr_class P1[] = {
  811. static_cast<mpfr_class>("-1.4577180278143463643e+15"),
  812. static_cast<mpfr_class>("-1.7732037840791591320e+14"),
  813. static_cast<mpfr_class>("-6.9876779648010090070e+12"),
  814. static_cast<mpfr_class>("-1.3357437682275493024e+11"),
  815. static_cast<mpfr_class>("-1.4828267606612366099e+09"),
  816. static_cast<mpfr_class>("-1.0588550724769347106e+07"),
  817. static_cast<mpfr_class>("-5.1894091982308017540e+04"),
  818. static_cast<mpfr_class>("-1.8225946631657315931e+02"),
  819. static_cast<mpfr_class>("-4.7207090827310162436e-01"),
  820. static_cast<mpfr_class>("-9.1746443287817501309e-04"),
  821. static_cast<mpfr_class>("-1.3466829827635152875e-06"),
  822. static_cast<mpfr_class>("-1.4831904935994647675e-09"),
  823. static_cast<mpfr_class>("-1.1928788903603238754e-12"),
  824. static_cast<mpfr_class>("-6.5245515583151902910e-16"),
  825. static_cast<mpfr_class>("-1.9705291802535139930e-19"),
  826. };
  827. static const mpfr_class Q1[] = {
  828. static_cast<mpfr_class>("-2.9154360556286927285e+15"),
  829. static_cast<mpfr_class>("9.7887501377547640438e+12"),
  830. static_cast<mpfr_class>("-1.4386907088588283434e+10"),
  831. static_cast<mpfr_class>("1.1594225856856884006e+07"),
  832. static_cast<mpfr_class>("-5.1326864679904189920e+03"),
  833. static_cast<mpfr_class>("1.0"),
  834. };
  835. static const mpfr_class P2[] = {
  836. static_cast<mpfr_class>("1.4582087408985668208e-05"),
  837. static_cast<mpfr_class>("-8.9359825138577646443e-04"),
  838. static_cast<mpfr_class>("2.9204895411257790122e-02"),
  839. static_cast<mpfr_class>("-3.4198728018058047439e-01"),
  840. static_cast<mpfr_class>("1.3960118277609544334e+00"),
  841. static_cast<mpfr_class>("-1.9746376087200685843e+00"),
  842. static_cast<mpfr_class>("8.5591872901933459000e-01"),
  843. static_cast<mpfr_class>("-6.0437159056137599999e-02"),
  844. };
  845. static const mpfr_class Q2[] = {
  846. static_cast<mpfr_class>("3.7510433111922824643e-05"),
  847. static_cast<mpfr_class>("-2.2835624489492512649e-03"),
  848. static_cast<mpfr_class>("7.4212010813186530069e-02"),
  849. static_cast<mpfr_class>("-8.5017476463217924408e-01"),
  850. static_cast<mpfr_class>("3.2593714889036996297e+00"),
  851. static_cast<mpfr_class>("-3.8806586721556593450e+00"),
  852. static_cast<mpfr_class>("1.0"),
  853. };
  854. mpfr_class value, factor, r, w;
  855. BOOST_MATH_STD_USING
  856. using namespace boost::math::tools;
  857. w = abs(x);
  858. if (x == 0)
  859. {
  860. return static_cast<mpfr_class>(0);
  861. }
  862. if (w <= 15) // w in (0, 15]
  863. {
  864. mpfr_class y = x * x;
  865. r = evaluate_polynomial(P1, y) / evaluate_polynomial(Q1, y);
  866. factor = w;
  867. value = factor * r;
  868. }
  869. else // w in (15, \infty)
  870. {
  871. mpfr_class y = 1 / w - mpfr_class(1) / 15;
  872. r = evaluate_polynomial(P2, y) / evaluate_polynomial(Q2, y);
  873. factor = exp(w) / sqrt(w);
  874. value = factor * r;
  875. }
  876. if (x < 0)
  877. {
  878. value *= -value; // odd function
  879. }
  880. return value;
  881. }
  882. } // namespace detail
  883. }
  884. template<> struct is_convertible<long double, mpfr_class> : public mpl::false_{};
  885. }
  886. #endif // BOOST_MATH_MPLFR_BINDINGS_HPP