gsl_specfunc__psi.c 24 KB

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  1. /* specfunc/psi.c
  2. *
  3. * Copyright (C) 2007 Brian Gough
  4. * Copyright (C) 1996, 1997, 1998, 1999, 2000, 2004, 2005, 2006 Gerard Jungman
  5. *
  6. * This program is free software; you can redistribute it and/or modify
  7. * it under the terms of the GNU General Public License as published by
  8. * the Free Software Foundation; either version 3 of the License, or (at
  9. * your option) any later version.
  10. *
  11. * This program is distributed in the hope that it will be useful, but
  12. * WITHOUT ANY WARRANTY; without even the implied warranty of
  13. * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
  14. * General Public License for more details.
  15. *
  16. * You should have received a copy of the GNU General Public License
  17. * along with this program; if not, write to the Free Software
  18. * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
  19. */
  20. /* Author: G. Jungman */
  21. #include "gsl__config.h"
  22. #include "gsl_math.h"
  23. #include "gsl_errno.h"
  24. #include "gsl_sf_exp.h"
  25. #include "gsl_sf_gamma.h"
  26. #include "gsl_sf_zeta.h"
  27. #include "gsl_sf_psi.h"
  28. #include "gsl_complex_math.h"
  29. #include <stdio.h>
  30. #include "gsl_specfunc__error.h"
  31. #include "gsl_specfunc__chebyshev.h"
  32. #include "gsl_specfunc__cheb_eval.c"
  33. /*-*-*-*-*-*-*-*-*-*-*-* Private Section *-*-*-*-*-*-*-*-*-*-*-*/
  34. /* Chebyshev fit for f(y) = Re(Psi(1+Iy)) + M_EULER - y^2/(1+y^2) - y^2/(2(4+y^2))
  35. * 1 < y < 10
  36. * ==>
  37. * y(x) = (9x + 11)/2, -1 < x < 1
  38. * x(y) = (2y - 11)/9
  39. *
  40. * g(x) := f(y(x))
  41. */
  42. static double r1py_data[] = {
  43. 1.59888328244976954803168395603,
  44. 0.67905625353213463845115658455,
  45. -0.068485802980122530009506482524,
  46. -0.005788184183095866792008831182,
  47. 0.008511258167108615980419855648,
  48. -0.004042656134699693434334556409,
  49. 0.001352328406159402601778462956,
  50. -0.000311646563930660566674525382,
  51. 0.000018507563785249135437219139,
  52. 0.000028348705427529850296492146,
  53. -0.000019487536014574535567541960,
  54. 8.0709788710834469408621587335e-06,
  55. -2.2983564321340518037060346561e-06,
  56. 3.0506629599604749843855962658e-07,
  57. 1.3042238632418364610774284846e-07,
  58. -1.2308657181048950589464690208e-07,
  59. 5.7710855710682427240667414345e-08,
  60. -1.8275559342450963966092636354e-08,
  61. 3.1020471300626589420759518930e-09,
  62. 6.8989327480593812470039430640e-10,
  63. -8.7182290258923059852334818997e-10,
  64. 4.4069147710243611798213548777e-10,
  65. -1.4727311099198535963467200277e-10,
  66. 2.7589682523262644748825844248e-11,
  67. 4.1871826756975856411554363568e-12,
  68. -6.5673460487260087541400767340e-12,
  69. 3.4487900886723214020103638000e-12,
  70. -1.1807251417448690607973794078e-12,
  71. 2.3798314343969589258709315574e-13,
  72. 2.1663630410818831824259465821e-15
  73. };
  74. static cheb_series r1py_cs = {
  75. r1py_data,
  76. 29,
  77. -1,1,
  78. 18
  79. };
  80. /* Chebyshev fits from SLATEC code for psi(x)
  81. Series for PSI on the interval 0. to 1.00000D+00
  82. with weighted error 2.03E-17
  83. log weighted error 16.69
  84. significant figures required 16.39
  85. decimal places required 17.37
  86. Series for APSI on the interval 0. to 2.50000D-01
  87. with weighted error 5.54E-17
  88. log weighted error 16.26
  89. significant figures required 14.42
  90. decimal places required 16.86
  91. */
  92. static double psics_data[23] = {
  93. -.038057080835217922,
  94. .491415393029387130,
  95. -.056815747821244730,
  96. .008357821225914313,
  97. -.001333232857994342,
  98. .000220313287069308,
  99. -.000037040238178456,
  100. .000006283793654854,
  101. -.000001071263908506,
  102. .000000183128394654,
  103. -.000000031353509361,
  104. .000000005372808776,
  105. -.000000000921168141,
  106. .000000000157981265,
  107. -.000000000027098646,
  108. .000000000004648722,
  109. -.000000000000797527,
  110. .000000000000136827,
  111. -.000000000000023475,
  112. .000000000000004027,
  113. -.000000000000000691,
  114. .000000000000000118,
  115. -.000000000000000020
  116. };
  117. static cheb_series psi_cs = {
  118. psics_data,
  119. 22,
  120. -1, 1,
  121. 17
  122. };
  123. static double apsics_data[16] = {
  124. -.0204749044678185,
  125. -.0101801271534859,
  126. .0000559718725387,
  127. -.0000012917176570,
  128. .0000000572858606,
  129. -.0000000038213539,
  130. .0000000003397434,
  131. -.0000000000374838,
  132. .0000000000048990,
  133. -.0000000000007344,
  134. .0000000000001233,
  135. -.0000000000000228,
  136. .0000000000000045,
  137. -.0000000000000009,
  138. .0000000000000002,
  139. -.0000000000000000
  140. };
  141. static cheb_series apsi_cs = {
  142. apsics_data,
  143. 15,
  144. -1, 1,
  145. 9
  146. };
  147. #define PSI_TABLE_NMAX 100
  148. static double psi_table[PSI_TABLE_NMAX+1] = {
  149. 0.0, /* Infinity */ /* psi(0) */
  150. -M_EULER, /* psi(1) */
  151. 0.42278433509846713939348790992, /* ... */
  152. 0.92278433509846713939348790992,
  153. 1.25611766843180047272682124325,
  154. 1.50611766843180047272682124325,
  155. 1.70611766843180047272682124325,
  156. 1.87278433509846713939348790992,
  157. 2.01564147795560999653634505277,
  158. 2.14064147795560999653634505277,
  159. 2.25175258906672110764745616389,
  160. 2.35175258906672110764745616389,
  161. 2.44266167997581201673836525479,
  162. 2.52599501330914535007169858813,
  163. 2.60291809023222227314862166505,
  164. 2.67434666166079370172005023648,
  165. 2.74101332832746036838671690315,
  166. 2.80351332832746036838671690315,
  167. 2.86233685773922507426906984432,
  168. 2.91789241329478062982462539988,
  169. 2.97052399224214905087725697883,
  170. 3.02052399224214905087725697883,
  171. 3.06814303986119666992487602645,
  172. 3.11359758531574212447033057190,
  173. 3.15707584618530734186163491973,
  174. 3.1987425128519740085283015864,
  175. 3.2387425128519740085283015864,
  176. 3.2772040513135124700667631249,
  177. 3.3142410883505495071038001619,
  178. 3.3499553740648352213895144476,
  179. 3.3844381326855248765619282407,
  180. 3.4177714660188582098952615740,
  181. 3.4500295305349872421533260902,
  182. 3.4812795305349872421533260902,
  183. 3.5115825608380175451836291205,
  184. 3.5409943255438998981248055911,
  185. 3.5695657541153284695533770196,
  186. 3.5973435318931062473311547974,
  187. 3.6243705589201332743581818244,
  188. 3.6506863483938174848844976139,
  189. 3.6763273740348431259101386396,
  190. 3.7013273740348431259101386396,
  191. 3.7257176179372821503003825420,
  192. 3.7495271417468059598241920658,
  193. 3.7727829557002943319172153216,
  194. 3.7955102284275670591899425943,
  195. 3.8177324506497892814121648166,
  196. 3.8394715810845718901078169905,
  197. 3.8607481768292527411716467777,
  198. 3.8815815101625860745049801110,
  199. 3.9019896734278921969539597029,
  200. 3.9219896734278921969539597029,
  201. 3.9415975165651470989147440166,
  202. 3.9608282857959163296839747858,
  203. 3.9796962103242182164764276160,
  204. 3.9982147288427367349949461345,
  205. 4.0163965470245549168131279527,
  206. 4.0342536898816977739559850956,
  207. 4.0517975495308205809735289552,
  208. 4.0690389288411654085597358518,
  209. 4.0859880813835382899156680552,
  210. 4.1026547480502049565823347218,
  211. 4.1190481906731557762544658694,
  212. 4.1351772229312202923834981274,
  213. 4.1510502388042361653993711433,
  214. 4.1666752388042361653993711433,
  215. 4.1820598541888515500147557587,
  216. 4.1972113693403667015299072739,
  217. 4.2121367424746950597388624977,
  218. 4.2268426248276362362094507330,
  219. 4.2413353784508246420065521823,
  220. 4.2556210927365389277208378966,
  221. 4.2697055997787924488475984600,
  222. 4.2835944886676813377364873489,
  223. 4.2972931188046676391063503626,
  224. 4.3108066323181811526198638761,
  225. 4.3241399656515144859531972094,
  226. 4.3372978603883565912163551041,
  227. 4.3502848733753695782293421171,
  228. 4.3631053861958823987421626300,
  229. 4.3757636140439836645649474401,
  230. 4.3882636140439836645649474401,
  231. 4.4006092930563293435772931191,
  232. 4.4128044150075488557724150703,
  233. 4.4248526077786331931218126607,
  234. 4.4367573696833950978837174226,
  235. 4.4485220755657480390601880108,
  236. 4.4601499825424922251066996387,
  237. 4.4716442354160554434975042364,
  238. 4.4830078717796918071338678728,
  239. 4.4942438268358715824147667492,
  240. 4.5053549379469826935258778603,
  241. 4.5163439489359936825368668713,
  242. 4.5272135141533849868846929582,
  243. 4.5379662023254279976373811303,
  244. 4.5486045001977684231692960239,
  245. 4.5591308159872421073798223397,
  246. 4.5695474826539087740464890064,
  247. 4.5798567610044242379640147796,
  248. 4.5900608426370772991885045755,
  249. 4.6001618527380874001986055856
  250. };
  251. #define PSI_1_TABLE_NMAX 100
  252. static double psi_1_table[PSI_1_TABLE_NMAX+1] = {
  253. 0.0, /* Infinity */ /* psi(1,0) */
  254. M_PI*M_PI/6.0, /* psi(1,1) */
  255. 0.644934066848226436472415, /* ... */
  256. 0.394934066848226436472415,
  257. 0.2838229557371153253613041,
  258. 0.2213229557371153253613041,
  259. 0.1813229557371153253613041,
  260. 0.1535451779593375475835263,
  261. 0.1331370146940314251345467,
  262. 0.1175120146940314251345467,
  263. 0.1051663356816857461222010,
  264. 0.0951663356816857461222010,
  265. 0.0869018728717683907503002,
  266. 0.0799574284273239463058557,
  267. 0.0740402686640103368384001,
  268. 0.0689382278476838062261552,
  269. 0.0644937834032393617817108,
  270. 0.0605875334032393617817108,
  271. 0.0571273257907826143768665,
  272. 0.0540409060376961946237801,
  273. 0.0512708229352031198315363,
  274. 0.0487708229352031198315363,
  275. 0.0465032492390579951149830,
  276. 0.0444371335365786562720078,
  277. 0.0425467743683366902984728,
  278. 0.0408106632572255791873617,
  279. 0.0392106632572255791873617,
  280. 0.0377313733163971768204978,
  281. 0.0363596312039143235969038,
  282. 0.0350841209998326909438426,
  283. 0.0338950603577399442137594,
  284. 0.0327839492466288331026483,
  285. 0.0317433665203020901265817,
  286. 0.03076680402030209012658168,
  287. 0.02984853037475571730748159,
  288. 0.02898347847164153045627052,
  289. 0.02816715194102928555831133,
  290. 0.02739554700275768062003973,
  291. 0.02666508681283803124093089,
  292. 0.02597256603721476254286995,
  293. 0.02531510384129102815759710,
  294. 0.02469010384129102815759710,
  295. 0.02409521984367056414807896,
  296. 0.02352832641963428296894063,
  297. 0.02298749353699501850166102,
  298. 0.02247096461137518379091722,
  299. 0.02197713745088135663042339,
  300. 0.02150454765882086513703965,
  301. 0.02105185413233829383780923,
  302. 0.02061782635456051606003145,
  303. 0.02020133322669712580597065,
  304. 0.01980133322669712580597065,
  305. 0.01941686571420193164987683,
  306. 0.01904704322899483105816086,
  307. 0.01869104465298913508094477,
  308. 0.01834810912486842177504628,
  309. 0.01801753061247172756017024,
  310. 0.01769865306145131939690494,
  311. 0.01739086605006319997554452,
  312. 0.01709360088954001329302371,
  313. 0.01680632711763538818529605,
  314. 0.01652854933985761040751827,
  315. 0.01625980437882562975715546,
  316. 0.01599965869724394401313881,
  317. 0.01574770606433893015574400,
  318. 0.01550356543933893015574400,
  319. 0.01526687904880638577704578,
  320. 0.01503731063741979257227076,
  321. 0.01481454387422086185273411,
  322. 0.01459828089844231513993134,
  323. 0.01438824099085987447620523,
  324. 0.01418415935820681325171544,
  325. 0.01398578601958352422176106,
  326. 0.01379288478501562298719316,
  327. 0.01360523231738567365335942,
  328. 0.01342261726990576130858221,
  329. 0.01324483949212798353080444,
  330. 0.01307170929822216635628920,
  331. 0.01290304679189732236910755,
  332. 0.01273868124291638877278934,
  333. 0.01257845051066194236996928,
  334. 0.01242220051066194236996928,
  335. 0.01226978472038606978956995,
  336. 0.01212106372098095378719041,
  337. 0.01197590477193174490346273,
  338. 0.01183418141592267460867815,
  339. 0.01169577311142440471248438,
  340. 0.01156056489076458859566448,
  341. 0.01142844704164317229232189,
  342. 0.01129931481023821361463594,
  343. 0.01117306812421372175754719,
  344. 0.01104961133409026496742374,
  345. 0.01092885297157366069257770,
  346. 0.01081070552355853781923177,
  347. 0.01069508522063334415522437,
  348. 0.01058191183901270133041676,
  349. 0.01047110851491297833872701,
  350. 0.01036260157046853389428257,
  351. 0.01025632035036012704977199, /* ... */
  352. 0.01015219706839427948625679, /* psi(1,99) */
  353. 0.01005016666333357139524567 /* psi(1,100) */
  354. };
  355. /* digamma for x both positive and negative; we do both
  356. * cases here because of the way we use even/odd parts
  357. * of the function
  358. */
  359. static int
  360. psi_x(const double x, gsl_sf_result * result)
  361. {
  362. const double y = fabs(x);
  363. if(x == 0.0 || x == -1.0 || x == -2.0) {
  364. DOMAIN_ERROR(result);
  365. }
  366. else if(y >= 2.0) {
  367. const double t = 8.0/(y*y)-1.0;
  368. gsl_sf_result result_c;
  369. cheb_eval_e(&apsi_cs, t, &result_c);
  370. if(x < 0.0) {
  371. const double s = sin(M_PI*x);
  372. const double c = cos(M_PI*x);
  373. if(fabs(s) < 2.0*GSL_SQRT_DBL_MIN) {
  374. DOMAIN_ERROR(result);
  375. }
  376. else {
  377. result->val = log(y) - 0.5/x + result_c.val - M_PI * c/s;
  378. result->err = M_PI*fabs(x)*GSL_DBL_EPSILON/(s*s);
  379. result->err += result_c.err;
  380. result->err += GSL_DBL_EPSILON * fabs(result->val);
  381. return GSL_SUCCESS;
  382. }
  383. }
  384. else {
  385. result->val = log(y) - 0.5/x + result_c.val;
  386. result->err = result_c.err;
  387. result->err += GSL_DBL_EPSILON * fabs(result->val);
  388. return GSL_SUCCESS;
  389. }
  390. }
  391. else { /* -2 < x < 2 */
  392. gsl_sf_result result_c;
  393. if(x < -1.0) { /* x = -2 + v */
  394. const double v = x + 2.0;
  395. const double t1 = 1.0/x;
  396. const double t2 = 1.0/(x+1.0);
  397. const double t3 = 1.0/v;
  398. cheb_eval_e(&psi_cs, 2.0*v-1.0, &result_c);
  399. result->val = -(t1 + t2 + t3) + result_c.val;
  400. result->err = GSL_DBL_EPSILON * (fabs(t1) + fabs(x/(t2*t2)) + fabs(x/(t3*t3)));
  401. result->err += result_c.err;
  402. result->err += GSL_DBL_EPSILON * fabs(result->val);
  403. return GSL_SUCCESS;
  404. }
  405. else if(x < 0.0) { /* x = -1 + v */
  406. const double v = x + 1.0;
  407. const double t1 = 1.0/x;
  408. const double t2 = 1.0/v;
  409. cheb_eval_e(&psi_cs, 2.0*v-1.0, &result_c);
  410. result->val = -(t1 + t2) + result_c.val;
  411. result->err = GSL_DBL_EPSILON * (fabs(t1) + fabs(x/(t2*t2)));
  412. result->err += result_c.err;
  413. result->err += GSL_DBL_EPSILON * fabs(result->val);
  414. return GSL_SUCCESS;
  415. }
  416. else if(x < 1.0) { /* x = v */
  417. const double t1 = 1.0/x;
  418. cheb_eval_e(&psi_cs, 2.0*x-1.0, &result_c);
  419. result->val = -t1 + result_c.val;
  420. result->err = GSL_DBL_EPSILON * t1;
  421. result->err += result_c.err;
  422. result->err += GSL_DBL_EPSILON * fabs(result->val);
  423. return GSL_SUCCESS;
  424. }
  425. else { /* x = 1 + v */
  426. const double v = x - 1.0;
  427. return cheb_eval_e(&psi_cs, 2.0*v-1.0, result);
  428. }
  429. }
  430. }
  431. /* psi(z) for large |z| in the right half-plane; [Abramowitz + Stegun, 6.3.18] */
  432. static
  433. gsl_complex
  434. psi_complex_asymp(gsl_complex z)
  435. {
  436. /* coefficients in the asymptotic expansion for large z;
  437. * let w = z^(-2) and write the expression in the form
  438. *
  439. * ln(z) - 1/(2z) - 1/12 w (1 + c1 w + c2 w + c3 w + ... )
  440. */
  441. static const double c1 = -0.1;
  442. static const double c2 = 1.0/21.0;
  443. static const double c3 = -0.05;
  444. gsl_complex zi = gsl_complex_inverse(z);
  445. gsl_complex w = gsl_complex_mul(zi, zi);
  446. gsl_complex cs;
  447. /* Horner method evaluation of term in parentheses */
  448. gsl_complex sum;
  449. sum = gsl_complex_mul_real(w, c3/c2);
  450. sum = gsl_complex_add_real(sum, 1.0);
  451. sum = gsl_complex_mul_real(sum, c2/c1);
  452. sum = gsl_complex_mul(sum, w);
  453. sum = gsl_complex_add_real(sum, 1.0);
  454. sum = gsl_complex_mul_real(sum, c1);
  455. sum = gsl_complex_mul(sum, w);
  456. sum = gsl_complex_add_real(sum, 1.0);
  457. /* correction added to log(z) */
  458. cs = gsl_complex_mul(sum, w);
  459. cs = gsl_complex_mul_real(cs, -1.0/12.0);
  460. cs = gsl_complex_add(cs, gsl_complex_mul_real(zi, -0.5));
  461. return gsl_complex_add(gsl_complex_log(z), cs);
  462. }
  463. /* psi(z) for complex z in the right half-plane */
  464. static int
  465. psi_complex_rhp(
  466. gsl_complex z,
  467. gsl_sf_result * result_re,
  468. gsl_sf_result * result_im
  469. )
  470. {
  471. int n_recurse = 0;
  472. int i;
  473. gsl_complex a;
  474. if(GSL_REAL(z) == 0.0 && GSL_IMAG(z) == 0.0)
  475. {
  476. result_re->val = 0.0;
  477. result_im->val = 0.0;
  478. result_re->err = 0.0;
  479. result_im->err = 0.0;
  480. return GSL_EDOM;
  481. }
  482. /* compute the number of recurrences to apply */
  483. if(GSL_REAL(z) < 20.0 && fabs(GSL_IMAG(z)) < 20.0)
  484. {
  485. const double sp = sqrt(20.0 + GSL_IMAG(z));
  486. const double sn = sqrt(20.0 - GSL_IMAG(z));
  487. const double rhs = sp*sn - GSL_REAL(z);
  488. if(rhs > 0.0) n_recurse = ceil(rhs);
  489. }
  490. /* compute asymptotic at the large value z + n_recurse */
  491. a = psi_complex_asymp(gsl_complex_add_real(z, n_recurse));
  492. result_re->err = 2.0 * GSL_DBL_EPSILON * fabs(GSL_REAL(a));
  493. result_im->err = 2.0 * GSL_DBL_EPSILON * fabs(GSL_IMAG(a));
  494. /* descend recursively, if necessary */
  495. for(i = n_recurse; i >= 1; --i)
  496. {
  497. gsl_complex zn = gsl_complex_add_real(z, i - 1.0);
  498. gsl_complex zn_inverse = gsl_complex_inverse(zn);
  499. a = gsl_complex_sub(a, zn_inverse);
  500. /* accumulate the error, to catch cancellations */
  501. result_re->err += 2.0 * GSL_DBL_EPSILON * fabs(GSL_REAL(zn_inverse));
  502. result_im->err += 2.0 * GSL_DBL_EPSILON * fabs(GSL_IMAG(zn_inverse));
  503. }
  504. result_re->val = GSL_REAL(a);
  505. result_im->val = GSL_IMAG(a);
  506. result_re->err += 2.0 * GSL_DBL_EPSILON * fabs(result_re->val);
  507. result_im->err += 2.0 * GSL_DBL_EPSILON * fabs(result_im->val);
  508. return GSL_SUCCESS;
  509. }
  510. /* generic polygamma; assumes n >= 0 and x > 0
  511. */
  512. static int
  513. psi_n_xg0(const int n, const double x, gsl_sf_result * result)
  514. {
  515. if(n == 0) {
  516. return gsl_sf_psi_e(x, result);
  517. }
  518. else {
  519. /* Abramowitz + Stegun 6.4.10 */
  520. gsl_sf_result ln_nf;
  521. gsl_sf_result hzeta;
  522. int stat_hz = gsl_sf_hzeta_e(n+1.0, x, &hzeta);
  523. int stat_nf = gsl_sf_lnfact_e((unsigned int) n, &ln_nf);
  524. int stat_e = gsl_sf_exp_mult_err_e(ln_nf.val, ln_nf.err,
  525. hzeta.val, hzeta.err,
  526. result);
  527. if(GSL_IS_EVEN(n)) result->val = -result->val;
  528. return GSL_ERROR_SELECT_3(stat_e, stat_nf, stat_hz);
  529. }
  530. }
  531. /*-*-*-*-*-*-*-*-*-*-*-* Functions with Error Codes *-*-*-*-*-*-*-*-*-*-*-*/
  532. int gsl_sf_psi_int_e(const int n, gsl_sf_result * result)
  533. {
  534. /* CHECK_POINTER(result) */
  535. if(n <= 0) {
  536. DOMAIN_ERROR(result);
  537. }
  538. else if(n <= PSI_TABLE_NMAX) {
  539. result->val = psi_table[n];
  540. result->err = GSL_DBL_EPSILON * fabs(result->val);
  541. return GSL_SUCCESS;
  542. }
  543. else {
  544. /* Abramowitz+Stegun 6.3.18 */
  545. const double c2 = -1.0/12.0;
  546. const double c3 = 1.0/120.0;
  547. const double c4 = -1.0/252.0;
  548. const double c5 = 1.0/240.0;
  549. const double ni2 = (1.0/n)*(1.0/n);
  550. const double ser = ni2 * (c2 + ni2 * (c3 + ni2 * (c4 + ni2*c5)));
  551. result->val = log(n) - 0.5/n + ser;
  552. result->err = GSL_DBL_EPSILON * (fabs(log(n)) + fabs(0.5/n) + fabs(ser));
  553. result->err += GSL_DBL_EPSILON * fabs(result->val);
  554. return GSL_SUCCESS;
  555. }
  556. }
  557. int gsl_sf_psi_e(const double x, gsl_sf_result * result)
  558. {
  559. /* CHECK_POINTER(result) */
  560. return psi_x(x, result);
  561. }
  562. int
  563. gsl_sf_psi_1piy_e(const double y, gsl_sf_result * result)
  564. {
  565. const double ay = fabs(y);
  566. /* CHECK_POINTER(result) */
  567. if(ay > 1000.0) {
  568. /* [Abramowitz+Stegun, 6.3.19] */
  569. const double yi2 = 1.0/(ay*ay);
  570. const double lny = log(ay);
  571. const double sum = yi2 * (1.0/12.0 + 1.0/120.0 * yi2 + 1.0/252.0 * yi2*yi2);
  572. result->val = lny + sum;
  573. result->err = 2.0 * GSL_DBL_EPSILON * (fabs(lny) + fabs(sum));
  574. return GSL_SUCCESS;
  575. }
  576. else if(ay > 10.0) {
  577. /* [Abramowitz+Stegun, 6.3.19] */
  578. const double yi2 = 1.0/(ay*ay);
  579. const double lny = log(ay);
  580. const double sum = yi2 * (1.0/12.0 +
  581. yi2 * (1.0/120.0 +
  582. yi2 * (1.0/252.0 +
  583. yi2 * (1.0/240.0 +
  584. yi2 * (1.0/132.0 + 691.0/32760.0 * yi2)))));
  585. result->val = lny + sum;
  586. result->err = 2.0 * GSL_DBL_EPSILON * (fabs(lny) + fabs(sum));
  587. return GSL_SUCCESS;
  588. }
  589. else if(ay > 1.0){
  590. const double y2 = ay*ay;
  591. const double x = (2.0*ay - 11.0)/9.0;
  592. const double v = y2*(1.0/(1.0+y2) + 0.5/(4.0+y2));
  593. gsl_sf_result result_c;
  594. cheb_eval_e(&r1py_cs, x, &result_c);
  595. result->val = result_c.val - M_EULER + v;
  596. result->err = result_c.err;
  597. result->err += 2.0 * GSL_DBL_EPSILON * (fabs(v) + M_EULER + fabs(result_c.val));
  598. result->err += 2.0 * GSL_DBL_EPSILON * fabs(result->val);
  599. result->err *= 5.0; /* FIXME: losing a digit somewhere... maybe at x=... ? */
  600. return GSL_SUCCESS;
  601. }
  602. else {
  603. /* [Abramowitz+Stegun, 6.3.17]
  604. *
  605. * -M_EULER + y^2 Sum[1/n 1/(n^2 + y^2), {n,1,M}]
  606. * + Sum[1/n^3, {n,M+1,Infinity}]
  607. * - y^2 Sum[1/n^5, {n,M+1,Infinity}]
  608. * + y^4 Sum[1/n^7, {n,M+1,Infinity}]
  609. * - y^6 Sum[1/n^9, {n,M+1,Infinity}]
  610. * + O(y^8)
  611. *
  612. * We take M=50 for at least 15 digit precision.
  613. */
  614. const int M = 50;
  615. const double y2 = y*y;
  616. const double c0 = 0.00019603999466879846570;
  617. const double c2 = 3.8426659205114376860e-08;
  618. const double c4 = 1.0041592839497643554e-11;
  619. const double c6 = 2.9516743763500191289e-15;
  620. const double p = c0 + y2 *(-c2 + y2*(c4 - y2*c6));
  621. double sum = 0.0;
  622. double v;
  623. int n;
  624. for(n=1; n<=M; n++) {
  625. sum += 1.0/(n * (n*n + y*y));
  626. }
  627. v = y2 * (sum + p);
  628. result->val = -M_EULER + v;
  629. result->err = GSL_DBL_EPSILON * (M_EULER + fabs(v));
  630. result->err += 2.0 * GSL_DBL_EPSILON * fabs(result->val);
  631. return GSL_SUCCESS;
  632. }
  633. }
  634. int gsl_sf_psi_1_int_e(const int n, gsl_sf_result * result)
  635. {
  636. /* CHECK_POINTER(result) */
  637. if(n <= 0) {
  638. DOMAIN_ERROR(result);
  639. }
  640. else if(n <= PSI_1_TABLE_NMAX) {
  641. result->val = psi_1_table[n];
  642. result->err = GSL_DBL_EPSILON * result->val;
  643. return GSL_SUCCESS;
  644. }
  645. else {
  646. /* Abramowitz+Stegun 6.4.12
  647. * double-precision for n > 100
  648. */
  649. const double c0 = -1.0/30.0;
  650. const double c1 = 1.0/42.0;
  651. const double c2 = -1.0/30.0;
  652. const double ni2 = (1.0/n)*(1.0/n);
  653. const double ser = ni2*ni2 * (c0 + ni2*(c1 + c2*ni2));
  654. result->val = (1.0 + 0.5/n + 1.0/(6.0*n*n) + ser) / n;
  655. result->err = GSL_DBL_EPSILON * result->val;
  656. return GSL_SUCCESS;
  657. }
  658. }
  659. int gsl_sf_psi_1_e(const double x, gsl_sf_result * result)
  660. {
  661. /* CHECK_POINTER(result) */
  662. if(x == 0.0 || x == -1.0 || x == -2.0) {
  663. DOMAIN_ERROR(result);
  664. }
  665. else if(x > 0.0)
  666. {
  667. return psi_n_xg0(1, x, result);
  668. }
  669. else if(x > -5.0)
  670. {
  671. /* Abramowitz + Stegun 6.4.6 */
  672. int M = -floor(x);
  673. double fx = x + M;
  674. double sum = 0.0;
  675. int m;
  676. if(fx == 0.0)
  677. DOMAIN_ERROR(result);
  678. for(m = 0; m < M; ++m)
  679. sum += 1.0/((x+m)*(x+m));
  680. {
  681. int stat_psi = psi_n_xg0(1, fx, result);
  682. result->val += sum;
  683. result->err += M * GSL_DBL_EPSILON * sum;
  684. return stat_psi;
  685. }
  686. }
  687. else
  688. {
  689. /* Abramowitz + Stegun 6.4.7 */
  690. const double sin_px = sin(M_PI * x);
  691. const double d = M_PI*M_PI/(sin_px*sin_px);
  692. gsl_sf_result r;
  693. int stat_psi = psi_n_xg0(1, 1.0-x, &r);
  694. result->val = d - r.val;
  695. result->err = r.err + 2.0*GSL_DBL_EPSILON*d;
  696. return stat_psi;
  697. }
  698. }
  699. int gsl_sf_psi_n_e(const int n, const double x, gsl_sf_result * result)
  700. {
  701. /* CHECK_POINTER(result) */
  702. if(n == 0)
  703. {
  704. return gsl_sf_psi_e(x, result);
  705. }
  706. else if(n == 1)
  707. {
  708. return gsl_sf_psi_1_e(x, result);
  709. }
  710. else if(n < 0 || x <= 0.0) {
  711. DOMAIN_ERROR(result);
  712. }
  713. else {
  714. gsl_sf_result ln_nf;
  715. gsl_sf_result hzeta;
  716. int stat_hz = gsl_sf_hzeta_e(n+1.0, x, &hzeta);
  717. int stat_nf = gsl_sf_lnfact_e((unsigned int) n, &ln_nf);
  718. int stat_e = gsl_sf_exp_mult_err_e(ln_nf.val, ln_nf.err,
  719. hzeta.val, hzeta.err,
  720. result);
  721. if(GSL_IS_EVEN(n)) result->val = -result->val;
  722. return GSL_ERROR_SELECT_3(stat_e, stat_nf, stat_hz);
  723. }
  724. }
  725. int
  726. gsl_sf_complex_psi_e(
  727. const double x,
  728. const double y,
  729. gsl_sf_result * result_re,
  730. gsl_sf_result * result_im
  731. )
  732. {
  733. if(x >= 0.0)
  734. {
  735. gsl_complex z = gsl_complex_rect(x, y);
  736. return psi_complex_rhp(z, result_re, result_im);
  737. }
  738. else
  739. {
  740. /* reflection formula [Abramowitz+Stegun, 6.3.7] */
  741. gsl_complex z = gsl_complex_rect(x, y);
  742. gsl_complex omz = gsl_complex_rect(1.0 - x, -y);
  743. gsl_complex zpi = gsl_complex_mul_real(z, M_PI);
  744. gsl_complex cotzpi = gsl_complex_cot(zpi);
  745. int ret_val = psi_complex_rhp(omz, result_re, result_im);
  746. if(GSL_IS_REAL(GSL_REAL(cotzpi)) && GSL_IS_REAL(GSL_IMAG(cotzpi)))
  747. {
  748. result_re->val -= M_PI * GSL_REAL(cotzpi);
  749. result_im->val -= M_PI * GSL_IMAG(cotzpi);
  750. return ret_val;
  751. }
  752. else
  753. {
  754. GSL_ERROR("singularity", GSL_EDOM);
  755. }
  756. }
  757. }
  758. /*-*-*-*-*-*-*-*-*-* Functions w/ Natural Prototypes *-*-*-*-*-*-*-*-*-*-*/
  759. #include "gsl_specfunc__eval.h"
  760. double gsl_sf_psi_int(const int n)
  761. {
  762. EVAL_RESULT(gsl_sf_psi_int_e(n, &result));
  763. }
  764. double gsl_sf_psi(const double x)
  765. {
  766. EVAL_RESULT(gsl_sf_psi_e(x, &result));
  767. }
  768. double gsl_sf_psi_1piy(const double x)
  769. {
  770. EVAL_RESULT(gsl_sf_psi_1piy_e(x, &result));
  771. }
  772. double gsl_sf_psi_1_int(const int n)
  773. {
  774. EVAL_RESULT(gsl_sf_psi_1_int_e(n, &result));
  775. }
  776. double gsl_sf_psi_1(const double x)
  777. {
  778. EVAL_RESULT(gsl_sf_psi_1_e(x, &result));
  779. }
  780. double gsl_sf_psi_n(const int n, const double x)
  781. {
  782. EVAL_RESULT(gsl_sf_psi_n_e(n, x, &result));
  783. }