12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364656667686970717273747576777879808182838485868788899091929394959697989910010110210310410510610710810911011111211311411511611711811912012112212312412512612712812913013113213313413513613713813914014114214314414514614714814915015115215315415515615715815916016116216316416516616716816917017117217317417517617717817918018118218318418518618718818919019119219319419519619719819920020120220320420520620720820921021121221321421521621721821922022122222322422522622722822923023123223323423523623723823924024124224324424524624724824925025125225325425525625725825926026126226326426526626726826927027127227327427527627727827928028128228328428528628728828929029129229329429529629729829930030130230330430530630730830931031131231331431531631731831932032132232332432532632732832933033133233333433533633733833934034134234334434534634734834935035135235335435535635735835936036136236336436536636736836937037137237337437537637737837938038138238338438538638738838939039139239339439539639739839940040140240340440540640740840941041141241341441541641741841942042142242342442542642742842943043143243343443543643743843944044144244344444544644744844945045145245345445545645745845946046146246346446546646746846947047147247347447547647747847948048148248348448548648748848949049149249349449549649749849950050150250350450550650750850951051151251351451551651751851952052152252352452552652752852953053153253353453553653753853954054154254354454554654754854955055155255355455555655755855956056156256356456556656756856957057157257357457557657757857958058158258358458558658758858959059159259359459559659759859960060160260360460560660760860961061161261361461561661761861962062162262362462562662762862963063163263363463563663763863964064164264364464564664764864965065165265365465565665765865966066166266366466566666766866967067167267367467567667767867968068168268368468568668768868969069169269369469569669769869970070170270370470570670770870971071171271371471571671771871972072172272372472572672772872973073173273373473573673773873974074174274374474574674774874975075175275375475575675775875976076176276376476576676776876977077177277377477577677777877978078178278378478578678778878979079179279379479579679779879980080180280380480580680780880981081181281381481581681781881982082182282382482582682782882983083183283383483583683783883984084184284384484584684784884985085185285385485585685785885986086186286386486586686786886987087187287387487587687787887988088188288388488588688788888989089189289389489589689789889990090190290390490590690790890991091191291391491591691791891992092192292392492592692792892993093193293393493593693793893994094194294394494594694794894995095195295395495595695795895996096196296396496596696796896997097197297397497597697797897998098198298398498598698798898999099199299399499599699799899910001001100210031004100510061007100810091010101110121013101410151016101710181019102010211022102310241025102610271028102910301031103210331034103510361037103810391040104110421043104410451046104710481049105010511052105310541055105610571058105910601061106210631064106510661067106810691070107110721073107410751076107710781079108010811082108310841085108610871088108910901091109210931094109510961097109810991100110111021103110411051106110711081109111011111112111311141115111611171118111911201121112211231124112511261127112811291130113111321133113411351136113711381139114011411142114311441145114611471148114911501151115211531154115511561157115811591160116111621163116411651166116711681169117011711172117311741175117611771178117911801181118211831184118511861187118811891190119111921193119411951196119711981199120012011202120312041205120612071208120912101211121212131214121512161217121812191220122112221223122412251226122712281229123012311232123312341235123612371238123912401241124212431244124512461247124812491250125112521253125412551256125712581259126012611262126312641265126612671268126912701271127212731274127512761277127812791280128112821283128412851286128712881289129012911292129312941295129612971298129913001301130213031304130513061307130813091310131113121313131413151316131713181319132013211322132313241325132613271328132913301331133213331334133513361337133813391340134113421343134413451346134713481349135013511352135313541355135613571358135913601361136213631364136513661367136813691370137113721373137413751376137713781379138013811382138313841385138613871388138913901391139213931394139513961397139813991400140114021403140414051406140714081409141014111412141314141415141614171418141914201421142214231424142514261427142814291430143114321433143414351436143714381439144014411442144314441445144614471448144914501451145214531454145514561457145814591460146114621463146414651466146714681469147014711472147314741475147614771478147914801481148214831484148514861487148814891490149114921493149414951496149714981499150015011502150315041505150615071508150915101511151215131514151515161517151815191520152115221523152415251526152715281529153015311532153315341535153615371538153915401541154215431544154515461547154815491550155115521553155415551556155715581559156015611562156315641565156615671568156915701571157215731574157515761577157815791580158115821583158415851586158715881589159015911592159315941595159615971598159916001601160216031604160516061607160816091610161116121613161416151616161716181619162016211622162316241625162616271628162916301631163216331634163516361637163816391640164116421643164416451646164716481649165016511652165316541655165616571658165916601661166216631664166516661667166816691670167116721673167416751676167716781679168016811682168316841685168616871688168916901691169216931694169516961697169816991700170117021703170417051706170717081709171017111712171317141715171617171718171917201721172217231724172517261727172817291730173117321733173417351736173717381739174017411742174317441745174617471748174917501751175217531754175517561757175817591760176117621763176417651766176717681769177017711772177317741775177617771778177917801781178217831784178517861787178817891790179117921793179417951796179717981799180018011802180318041805180618071808180918101811181218131814181518161817181818191820182118221823182418251826182718281829183018311832183318341835183618371838183918401841184218431844184518461847184818491850185118521853185418551856185718581859186018611862186318641865186618671868186918701871187218731874187518761877187818791880188118821883188418851886188718881889189018911892189318941895189618971898189919001901190219031904190519061907190819091910191119121913191419151916191719181919192019211922192319241925192619271928192919301931193219331934193519361937193819391940194119421943194419451946194719481949195019511952195319541955195619571958195919601961196219631964196519661967196819691970197119721973197419751976197719781979198019811982198319841985198619871988198919901991199219931994199519961997199819992000200120022003200420052006200720082009201020112012201320142015201620172018201920202021202220232024202520262027202820292030203120322033203420352036203720382039204020412042204320442045204620472048204920502051205220532054205520562057205820592060206120622063206420652066206720682069207020712072207320742075207620772078207920802081208220832084208520862087208820892090209120922093209420952096209720982099210021012102210321042105210621072108210921102111211221132114211521162117211821192120212121222123212421252126212721282129213021312132213321342135213621372138213921402141214221432144214521462147214821492150215121522153215421552156215721582159216021612162216321642165216621672168216921702171217221732174217521762177217821792180218121822183218421852186218721882189219021912192219321942195219621972198219922002201220222032204220522062207220822092210221122122213221422152216221722182219222022212222222322242225222622272228222922302231223222332234223522362237223822392240224122422243224422452246224722482249225022512252225322542255225622572258225922602261226222632264226522662267226822692270227122722273227422752276227722782279228022812282228322842285228622872288228922902291229222932294229522962297229822992300230123022303230423052306230723082309231023112312231323142315231623172318231923202321232223232324232523262327232823292330233123322333233423352336233723382339234023412342234323442345234623472348234923502351235223532354235523562357235823592360236123622363236423652366236723682369237023712372237323742375237623772378237923802381238223832384238523862387238823892390239123922393239423952396239723982399240024012402240324042405240624072408240924102411241224132414241524162417241824192420242124222423242424252426242724282429243024312432243324342435243624372438243924402441244224432444244524462447244824492450245124522453245424552456245724582459246024612462246324642465246624672468246924702471247224732474247524762477247824792480248124822483248424852486248724882489249024912492249324942495249624972498249925002501250225032504250525062507250825092510251125122513251425152516251725182519252025212522252325242525252625272528252925302531253225332534253525362537253825392540254125422543254425452546254725482549255025512552255325542555255625572558255925602561256225632564256525662567256825692570257125722573257425752576257725782579258025812582258325842585258625872588258925902591259225932594259525962597259825992600260126022603260426052606260726082609261026112612261326142615261626172618261926202621262226232624262526262627262826292630263126322633263426352636263726382639264026412642264326442645264626472648264926502651265226532654265526562657265826592660266126622663266426652666266726682669267026712672267326742675267626772678267926802681268226832684268526862687268826892690269126922693269426952696269726982699270027012702270327042705270627072708270927102711271227132714271527162717271827192720272127222723272427252726272727282729273027312732273327342735273627372738273927402741274227432744274527462747274827492750275127522753275427552756275727582759276027612762276327642765276627672768276927702771277227732774277527762777277827792780278127822783278427852786278727882789279027912792279327942795279627972798279928002801280228032804280528062807280828092810281128122813281428152816281728182819282028212822282328242825282628272828282928302831283228332834283528362837283828392840284128422843284428452846284728482849285028512852285328542855285628572858285928602861286228632864286528662867286828692870287128722873287428752876287728782879288028812882288328842885288628872888288928902891289228932894289528962897289828992900290129022903290429052906290729082909291029112912291329142915291629172918291929202921292229232924292529262927292829292930293129322933293429352936293729382939294029412942294329442945294629472948294929502951295229532954295529562957295829592960296129622963296429652966296729682969297029712972297329742975297629772978297929802981298229832984298529862987298829892990299129922993299429952996299729982999300030013002300330043005300630073008300930103011301230133014301530163017301830193020302130223023302430253026302730283029303030313032303330343035303630373038303930403041304230433044304530463047304830493050305130523053305430553056305730583059306030613062306330643065306630673068306930703071307230733074307530763077307830793080308130823083308430853086308730883089309030913092309330943095309630973098309931003101310231033104310531063107310831093110311131123113311431153116311731183119312031213122312331243125312631273128312931303131313231333134313531363137313831393140314131423143314431453146314731483149315031513152315331543155315631573158315931603161316231633164316531663167316831693170317131723173317431753176317731783179318031813182318331843185318631873188318931903191319231933194319531963197319831993200320132023203320432053206320732083209321032113212321332143215321632173218321932203221322232233224322532263227322832293230323132323233323432353236323732383239324032413242324332443245324632473248324932503251325232533254325532563257325832593260326132623263326432653266326732683269327032713272327332743275327632773278327932803281328232833284328532863287328832893290329132923293329432953296329732983299330033013302330333043305330633073308330933103311331233133314331533163317331833193320332133223323332433253326332733283329333033313332333333343335333633373338333933403341334233433344334533463347334833493350335133523353335433553356335733583359336033613362336333643365336633673368336933703371337233733374337533763377337833793380338133823383338433853386338733883389339033913392339333943395339633973398339934003401340234033404340534063407340834093410341134123413341434153416341734183419342034213422342334243425342634273428342934303431343234333434343534363437343834393440344134423443344434453446344734483449345034513452345334543455345634573458345934603461346234633464346534663467346834693470347134723473347434753476347734783479348034813482348334843485348634873488348934903491349234933494349534963497349834993500350135023503350435053506350735083509351035113512351335143515351635173518351935203521352235233524352535263527352835293530353135323533353435353536353735383539354035413542354335443545354635473548354935503551355235533554355535563557355835593560356135623563356435653566356735683569357035713572357335743575357635773578357935803581358235833584358535863587358835893590359135923593359435953596359735983599360036013602360336043605360636073608360936103611361236133614361536163617361836193620362136223623362436253626362736283629363036313632363336343635363636373638363936403641364236433644364536463647364836493650365136523653365436553656 |
- # this program corresponds to special.py
- ### Means test is not done yet
- # E Means test is giving error (E)
- # F Means test is failing (F)
- # EF Means test is giving error and Failing
- #! Means test is segfaulting
- # 8 Means test runs forever
- ### test_besselpoly
- ### test_mathieu_a
- ### test_mathieu_even_coef
- ### test_mathieu_odd_coef
- ### test_modfresnelp
- ### test_modfresnelm
- # test_pbdv_seq
- ### test_pbvv_seq
- ### test_sph_harm
- import itertools
- import platform
- import sys
- import numpy as np
- from numpy import (array, isnan, r_, arange, finfo, pi, sin, cos, tan, exp,
- log, zeros, sqrt, asarray, inf, nan_to_num, real, arctan, float_)
- import pytest
- from pytest import raises as assert_raises
- from numpy.testing import (assert_equal, assert_almost_equal,
- assert_array_equal, assert_array_almost_equal, assert_approx_equal,
- assert_, assert_allclose, assert_array_almost_equal_nulp,
- suppress_warnings)
- from scipy import special
- import scipy.special._ufuncs as cephes
- from scipy.special import ellipe, ellipk, ellipkm1
- from scipy.special import elliprc, elliprd, elliprf, elliprg, elliprj
- from scipy.special import mathieu_odd_coef, mathieu_even_coef
- from scipy.special._testutils import with_special_errors, \
- assert_func_equal, FuncData
- import math
- class TestCephes:
- def test_airy(self):
- cephes.airy(0)
- def test_airye(self):
- cephes.airye(0)
- def test_binom(self):
- n = np.array([0.264, 4, 5.2, 17])
- k = np.array([2, 0.4, 7, 3.3])
- nk = np.array(np.broadcast_arrays(n[:,None], k[None,:])
- ).reshape(2, -1).T
- rknown = np.array([[-0.097152, 0.9263051596159367, 0.01858423645695389,
- -0.007581020651518199],[6, 2.0214389119675666, 0, 2.9827344527963846],
- [10.92, 2.22993515861399, -0.00585728, 10.468891352063146],
- [136, 3.5252179590758828, 19448, 1024.5526916174495]])
- assert_func_equal(cephes.binom, rknown.ravel(), nk, rtol=1e-13)
- # Test branches in implementation
- np.random.seed(1234)
- n = np.r_[np.arange(-7, 30), 1000*np.random.rand(30) - 500]
- k = np.arange(0, 102)
- nk = np.array(np.broadcast_arrays(n[:,None], k[None,:])
- ).reshape(2, -1).T
- assert_func_equal(cephes.binom,
- cephes.binom(nk[:,0], nk[:,1] * (1 + 1e-15)),
- nk,
- atol=1e-10, rtol=1e-10)
- def test_binom_2(self):
- # Test branches in implementation
- np.random.seed(1234)
- n = np.r_[np.logspace(1, 300, 20)]
- k = np.arange(0, 102)
- nk = np.array(np.broadcast_arrays(n[:,None], k[None,:])
- ).reshape(2, -1).T
- assert_func_equal(cephes.binom,
- cephes.binom(nk[:,0], nk[:,1] * (1 + 1e-15)),
- nk,
- atol=1e-10, rtol=1e-10)
- def test_binom_exact(self):
- @np.vectorize
- def binom_int(n, k):
- n = int(n)
- k = int(k)
- num = int(1)
- den = int(1)
- for i in range(1, k+1):
- num *= i + n - k
- den *= i
- return float(num/den)
- np.random.seed(1234)
- n = np.arange(1, 15)
- k = np.arange(0, 15)
- nk = np.array(np.broadcast_arrays(n[:,None], k[None,:])
- ).reshape(2, -1).T
- nk = nk[nk[:,0] >= nk[:,1]]
- assert_func_equal(cephes.binom,
- binom_int(nk[:,0], nk[:,1]),
- nk,
- atol=0, rtol=0)
- def test_binom_nooverflow_8346(self):
- # Test (binom(n, k) doesn't overflow prematurely */
- dataset = [
- (1000, 500, 2.70288240945436551e+299),
- (1002, 501, 1.08007396880791225e+300),
- (1004, 502, 4.31599279169058121e+300),
- (1006, 503, 1.72468101616263781e+301),
- (1008, 504, 6.89188009236419153e+301),
- (1010, 505, 2.75402257948335448e+302),
- (1012, 506, 1.10052048531923757e+303),
- (1014, 507, 4.39774063758732849e+303),
- (1016, 508, 1.75736486108312519e+304),
- (1018, 509, 7.02255427788423734e+304),
- (1020, 510, 2.80626776829962255e+305),
- (1022, 511, 1.12140876377061240e+306),
- (1024, 512, 4.48125455209897109e+306),
- (1026, 513, 1.79075474304149900e+307),
- (1028, 514, 7.15605105487789676e+307)
- ]
- dataset = np.asarray(dataset)
- FuncData(cephes.binom, dataset, (0, 1), 2, rtol=1e-12).check()
- def test_bdtr(self):
- assert_equal(cephes.bdtr(1,1,0.5),1.0)
- def test_bdtri(self):
- assert_equal(cephes.bdtri(1,3,0.5),0.5)
- def test_bdtrc(self):
- assert_equal(cephes.bdtrc(1,3,0.5),0.5)
- def test_bdtrin(self):
- assert_equal(cephes.bdtrin(1,0,1),5.0)
- def test_bdtrik(self):
- cephes.bdtrik(1,3,0.5)
- def test_bei(self):
- assert_equal(cephes.bei(0),0.0)
- def test_beip(self):
- assert_equal(cephes.beip(0),0.0)
- def test_ber(self):
- assert_equal(cephes.ber(0),1.0)
- def test_berp(self):
- assert_equal(cephes.berp(0),0.0)
- def test_besselpoly(self):
- assert_equal(cephes.besselpoly(0,0,0),1.0)
- def test_beta(self):
- assert_equal(cephes.beta(1,1),1.0)
- assert_allclose(cephes.beta(-100.3, 1e-200), cephes.gamma(1e-200))
- assert_allclose(cephes.beta(0.0342, 171), 24.070498359873497,
- rtol=1e-13, atol=0)
- def test_betainc(self):
- assert_equal(cephes.betainc(1,1,1),1.0)
- assert_allclose(cephes.betainc(0.0342, 171, 1e-10), 0.55269916901806648)
- def test_betaln(self):
- assert_equal(cephes.betaln(1,1),0.0)
- assert_allclose(cephes.betaln(-100.3, 1e-200), cephes.gammaln(1e-200))
- assert_allclose(cephes.betaln(0.0342, 170), 3.1811881124242447,
- rtol=1e-14, atol=0)
- def test_betaincinv(self):
- assert_equal(cephes.betaincinv(1,1,1),1.0)
- assert_allclose(cephes.betaincinv(0.0342, 171, 0.25),
- 8.4231316935498957e-21, rtol=3e-12, atol=0)
- def test_beta_inf(self):
- assert_(np.isinf(special.beta(-1, 2)))
- def test_btdtr(self):
- assert_equal(cephes.btdtr(1,1,1),1.0)
- def test_btdtri(self):
- assert_equal(cephes.btdtri(1,1,1),1.0)
- def test_btdtria(self):
- assert_equal(cephes.btdtria(1,1,1),5.0)
- def test_btdtrib(self):
- assert_equal(cephes.btdtrib(1,1,1),5.0)
- def test_cbrt(self):
- assert_approx_equal(cephes.cbrt(1),1.0)
- def test_chdtr(self):
- assert_equal(cephes.chdtr(1,0),0.0)
- def test_chdtrc(self):
- assert_equal(cephes.chdtrc(1,0),1.0)
- def test_chdtri(self):
- assert_equal(cephes.chdtri(1,1),0.0)
- def test_chdtriv(self):
- assert_equal(cephes.chdtriv(0,0),5.0)
- def test_chndtr(self):
- assert_equal(cephes.chndtr(0,1,0),0.0)
- # Each row holds (x, nu, lam, expected_value)
- # These values were computed using Wolfram Alpha with
- # CDF[NoncentralChiSquareDistribution[nu, lam], x]
- values = np.array([
- [25.00, 20.0, 400, 4.1210655112396197139e-57],
- [25.00, 8.00, 250, 2.3988026526832425878e-29],
- [0.001, 8.00, 40., 5.3761806201366039084e-24],
- [0.010, 8.00, 40., 5.45396231055999457039e-20],
- [20.00, 2.00, 107, 1.39390743555819597802e-9],
- [22.50, 2.00, 107, 7.11803307138105870671e-9],
- [25.00, 2.00, 107, 3.11041244829864897313e-8],
- [3.000, 2.00, 1.0, 0.62064365321954362734],
- [350.0, 300., 10., 0.93880128006276407710],
- [100.0, 13.5, 10., 0.99999999650104210949],
- [700.0, 20.0, 400, 0.99999999925680650105],
- [150.0, 13.5, 10., 0.99999999999999983046],
- [160.0, 13.5, 10., 0.99999999999999999518], # 1.0
- ])
- cdf = cephes.chndtr(values[:, 0], values[:, 1], values[:, 2])
- assert_allclose(cdf, values[:, 3], rtol=1e-12)
- assert_almost_equal(cephes.chndtr(np.inf, np.inf, 0), 2.0)
- assert_almost_equal(cephes.chndtr(2, 1, np.inf), 0.0)
- assert_(np.isnan(cephes.chndtr(np.nan, 1, 2)))
- assert_(np.isnan(cephes.chndtr(5, np.nan, 2)))
- assert_(np.isnan(cephes.chndtr(5, 1, np.nan)))
- def test_chndtridf(self):
- assert_equal(cephes.chndtridf(0,0,1),5.0)
- def test_chndtrinc(self):
- assert_equal(cephes.chndtrinc(0,1,0),5.0)
- def test_chndtrix(self):
- assert_equal(cephes.chndtrix(0,1,0),0.0)
- def test_cosdg(self):
- assert_equal(cephes.cosdg(0),1.0)
- def test_cosm1(self):
- assert_equal(cephes.cosm1(0),0.0)
- def test_cotdg(self):
- assert_almost_equal(cephes.cotdg(45),1.0)
- def test_dawsn(self):
- assert_equal(cephes.dawsn(0),0.0)
- assert_allclose(cephes.dawsn(1.23), 0.50053727749081767)
- def test_diric(self):
- # Test behavior near multiples of 2pi. Regression test for issue
- # described in gh-4001.
- n_odd = [1, 5, 25]
- x = np.array(2*np.pi + 5e-5).astype(np.float32)
- assert_almost_equal(special.diric(x, n_odd), 1.0, decimal=7)
- x = np.array(2*np.pi + 1e-9).astype(np.float64)
- assert_almost_equal(special.diric(x, n_odd), 1.0, decimal=15)
- x = np.array(2*np.pi + 1e-15).astype(np.float64)
- assert_almost_equal(special.diric(x, n_odd), 1.0, decimal=15)
- if hasattr(np, 'float128'):
- # No float128 available in 32-bit numpy
- x = np.array(2*np.pi + 1e-12).astype(np.float128)
- assert_almost_equal(special.diric(x, n_odd), 1.0, decimal=19)
- n_even = [2, 4, 24]
- x = np.array(2*np.pi + 1e-9).astype(np.float64)
- assert_almost_equal(special.diric(x, n_even), -1.0, decimal=15)
- # Test at some values not near a multiple of pi
- x = np.arange(0.2*np.pi, 1.0*np.pi, 0.2*np.pi)
- octave_result = [0.872677996249965, 0.539344662916632,
- 0.127322003750035, -0.206011329583298]
- assert_almost_equal(special.diric(x, 3), octave_result, decimal=15)
- def test_diric_broadcasting(self):
- x = np.arange(5)
- n = np.array([1, 3, 7])
- assert_(special.diric(x[:, np.newaxis], n).shape == (x.size, n.size))
- def test_ellipe(self):
- assert_equal(cephes.ellipe(1),1.0)
- def test_ellipeinc(self):
- assert_equal(cephes.ellipeinc(0,1),0.0)
- def test_ellipj(self):
- cephes.ellipj(0,1)
- def test_ellipk(self):
- assert_allclose(ellipk(0), pi/2)
- def test_ellipkinc(self):
- assert_equal(cephes.ellipkinc(0,0),0.0)
- def test_erf(self):
- assert_equal(cephes.erf(0), 0.0)
- def test_erf_symmetry(self):
- x = 5.905732037710919
- assert_equal(cephes.erf(x) + cephes.erf(-x), 0.0)
- def test_erfc(self):
- assert_equal(cephes.erfc(0), 1.0)
- def test_exp10(self):
- assert_approx_equal(cephes.exp10(2),100.0)
- def test_exp2(self):
- assert_equal(cephes.exp2(2),4.0)
- def test_expm1(self):
- assert_equal(cephes.expm1(0),0.0)
- assert_equal(cephes.expm1(np.inf), np.inf)
- assert_equal(cephes.expm1(-np.inf), -1)
- assert_equal(cephes.expm1(np.nan), np.nan)
- def test_expm1_complex(self):
- expm1 = cephes.expm1
- assert_equal(expm1(0 + 0j), 0 + 0j)
- assert_equal(expm1(complex(np.inf, 0)), complex(np.inf, 0))
- assert_equal(expm1(complex(np.inf, 1)), complex(np.inf, np.inf))
- assert_equal(expm1(complex(np.inf, 2)), complex(-np.inf, np.inf))
- assert_equal(expm1(complex(np.inf, 4)), complex(-np.inf, -np.inf))
- assert_equal(expm1(complex(np.inf, 5)), complex(np.inf, -np.inf))
- assert_equal(expm1(complex(1, np.inf)), complex(np.nan, np.nan))
- assert_equal(expm1(complex(0, np.inf)), complex(np.nan, np.nan))
- assert_equal(expm1(complex(np.inf, np.inf)), complex(np.inf, np.nan))
- assert_equal(expm1(complex(-np.inf, np.inf)), complex(-1, 0))
- assert_equal(expm1(complex(-np.inf, np.nan)), complex(-1, 0))
- assert_equal(expm1(complex(np.inf, np.nan)), complex(np.inf, np.nan))
- assert_equal(expm1(complex(0, np.nan)), complex(np.nan, np.nan))
- assert_equal(expm1(complex(1, np.nan)), complex(np.nan, np.nan))
- assert_equal(expm1(complex(np.nan, 1)), complex(np.nan, np.nan))
- assert_equal(expm1(complex(np.nan, np.nan)), complex(np.nan, np.nan))
- @pytest.mark.xfail(reason='The real part of expm1(z) bad at these points')
- def test_expm1_complex_hard(self):
- # The real part of this function is difficult to evaluate when
- # z.real = -log(cos(z.imag)).
- y = np.array([0.1, 0.2, 0.3, 5, 11, 20])
- x = -np.log(np.cos(y))
- z = x + 1j*y
- # evaluate using mpmath.expm1 with dps=1000
- expected = np.array([-5.5507901846769623e-17+0.10033467208545054j,
- 2.4289354732893695e-18+0.20271003550867248j,
- 4.5235500262585768e-17+0.30933624960962319j,
- 7.8234305217489006e-17-3.3805150062465863j,
- -1.3685191953697676e-16-225.95084645419513j,
- 8.7175620481291045e-17+2.2371609442247422j])
- found = cephes.expm1(z)
- # this passes.
- assert_array_almost_equal_nulp(found.imag, expected.imag, 3)
- # this fails.
- assert_array_almost_equal_nulp(found.real, expected.real, 20)
- def test_fdtr(self):
- assert_equal(cephes.fdtr(1, 1, 0), 0.0)
- # Computed using Wolfram Alpha: CDF[FRatioDistribution[1e-6, 5], 10]
- assert_allclose(cephes.fdtr(1e-6, 5, 10), 0.9999940790193488,
- rtol=1e-12)
- def test_fdtrc(self):
- assert_equal(cephes.fdtrc(1, 1, 0), 1.0)
- # Computed using Wolfram Alpha:
- # 1 - CDF[FRatioDistribution[2, 1/10], 1e10]
- assert_allclose(cephes.fdtrc(2, 0.1, 1e10), 0.27223784621293512,
- rtol=1e-12)
- def test_fdtri(self):
- assert_allclose(cephes.fdtri(1, 1, [0.499, 0.501]),
- array([0.9937365, 1.00630298]), rtol=1e-6)
- # From Wolfram Alpha:
- # CDF[FRatioDistribution[1/10, 1], 3] = 0.8756751669632105666874...
- p = 0.8756751669632105666874
- assert_allclose(cephes.fdtri(0.1, 1, p), 3, rtol=1e-12)
- @pytest.mark.xfail(reason='Returns nan on i686.')
- def test_fdtri_mysterious_failure(self):
- assert_allclose(cephes.fdtri(1, 1, 0.5), 1)
- def test_fdtridfd(self):
- assert_equal(cephes.fdtridfd(1,0,0),5.0)
- def test_fresnel(self):
- assert_equal(cephes.fresnel(0),(0.0,0.0))
- def test_gamma(self):
- assert_equal(cephes.gamma(5),24.0)
- def test_gammainccinv(self):
- assert_equal(cephes.gammainccinv(5,1),0.0)
- def test_gammaln(self):
- cephes.gammaln(10)
- def test_gammasgn(self):
- vals = np.array([-4, -3.5, -2.3, 1, 4.2], np.float64)
- assert_array_equal(cephes.gammasgn(vals), np.sign(cephes.rgamma(vals)))
- def test_gdtr(self):
- assert_equal(cephes.gdtr(1,1,0),0.0)
- def test_gdtr_inf(self):
- assert_equal(cephes.gdtr(1,1,np.inf),1.0)
- def test_gdtrc(self):
- assert_equal(cephes.gdtrc(1,1,0),1.0)
- def test_gdtria(self):
- assert_equal(cephes.gdtria(0,1,1),0.0)
- def test_gdtrib(self):
- cephes.gdtrib(1,0,1)
- # assert_equal(cephes.gdtrib(1,0,1),5.0)
- def test_gdtrix(self):
- cephes.gdtrix(1,1,.1)
- def test_hankel1(self):
- cephes.hankel1(1,1)
- def test_hankel1e(self):
- cephes.hankel1e(1,1)
- def test_hankel2(self):
- cephes.hankel2(1,1)
- def test_hankel2e(self):
- cephes.hankel2e(1,1)
- def test_hyp1f1(self):
- assert_approx_equal(cephes.hyp1f1(1,1,1), exp(1.0))
- assert_approx_equal(cephes.hyp1f1(3,4,-6), 0.026056422099537251095)
- cephes.hyp1f1(1,1,1)
- def test_hyp2f1(self):
- assert_equal(cephes.hyp2f1(1,1,1,0),1.0)
- def test_i0(self):
- assert_equal(cephes.i0(0),1.0)
- def test_i0e(self):
- assert_equal(cephes.i0e(0),1.0)
- def test_i1(self):
- assert_equal(cephes.i1(0),0.0)
- def test_i1e(self):
- assert_equal(cephes.i1e(0),0.0)
- def test_it2i0k0(self):
- cephes.it2i0k0(1)
- def test_it2j0y0(self):
- cephes.it2j0y0(1)
- def test_it2struve0(self):
- cephes.it2struve0(1)
- def test_itairy(self):
- cephes.itairy(1)
- def test_iti0k0(self):
- assert_equal(cephes.iti0k0(0),(0.0,0.0))
- def test_itj0y0(self):
- assert_equal(cephes.itj0y0(0),(0.0,0.0))
- def test_itmodstruve0(self):
- assert_equal(cephes.itmodstruve0(0),0.0)
- def test_itstruve0(self):
- assert_equal(cephes.itstruve0(0),0.0)
- def test_iv(self):
- assert_equal(cephes.iv(1,0),0.0)
- def _check_ive(self):
- assert_equal(cephes.ive(1,0),0.0)
- def test_j0(self):
- assert_equal(cephes.j0(0),1.0)
- def test_j1(self):
- assert_equal(cephes.j1(0),0.0)
- def test_jn(self):
- assert_equal(cephes.jn(0,0),1.0)
- def test_jv(self):
- assert_equal(cephes.jv(0,0),1.0)
- def _check_jve(self):
- assert_equal(cephes.jve(0,0),1.0)
- def test_k0(self):
- cephes.k0(2)
- def test_k0e(self):
- cephes.k0e(2)
- def test_k1(self):
- cephes.k1(2)
- def test_k1e(self):
- cephes.k1e(2)
- def test_kei(self):
- cephes.kei(2)
- def test_keip(self):
- assert_equal(cephes.keip(0),0.0)
- def test_ker(self):
- cephes.ker(2)
- def test_kerp(self):
- cephes.kerp(2)
- def _check_kelvin(self):
- cephes.kelvin(2)
- def test_kn(self):
- cephes.kn(1,1)
- def test_kolmogi(self):
- assert_equal(cephes.kolmogi(1),0.0)
- assert_(np.isnan(cephes.kolmogi(np.nan)))
- def test_kolmogorov(self):
- assert_equal(cephes.kolmogorov(0), 1.0)
- def test_kolmogp(self):
- assert_equal(cephes._kolmogp(0), -0.0)
- def test_kolmogc(self):
- assert_equal(cephes._kolmogc(0), 0.0)
- def test_kolmogci(self):
- assert_equal(cephes._kolmogci(0), 0.0)
- assert_(np.isnan(cephes._kolmogci(np.nan)))
- def _check_kv(self):
- cephes.kv(1,1)
- def _check_kve(self):
- cephes.kve(1,1)
- def test_log1p(self):
- log1p = cephes.log1p
- assert_equal(log1p(0), 0.0)
- assert_equal(log1p(-1), -np.inf)
- assert_equal(log1p(-2), np.nan)
- assert_equal(log1p(np.inf), np.inf)
- def test_log1p_complex(self):
- log1p = cephes.log1p
- c = complex
- assert_equal(log1p(0 + 0j), 0 + 0j)
- assert_equal(log1p(c(-1, 0)), c(-np.inf, 0))
- with suppress_warnings() as sup:
- sup.filter(RuntimeWarning, "invalid value encountered in multiply")
- assert_allclose(log1p(c(1, np.inf)), c(np.inf, np.pi/2))
- assert_equal(log1p(c(1, np.nan)), c(np.nan, np.nan))
- assert_allclose(log1p(c(-np.inf, 1)), c(np.inf, np.pi))
- assert_equal(log1p(c(np.inf, 1)), c(np.inf, 0))
- assert_allclose(log1p(c(-np.inf, np.inf)), c(np.inf, 3*np.pi/4))
- assert_allclose(log1p(c(np.inf, np.inf)), c(np.inf, np.pi/4))
- assert_equal(log1p(c(np.inf, np.nan)), c(np.inf, np.nan))
- assert_equal(log1p(c(-np.inf, np.nan)), c(np.inf, np.nan))
- assert_equal(log1p(c(np.nan, np.inf)), c(np.inf, np.nan))
- assert_equal(log1p(c(np.nan, 1)), c(np.nan, np.nan))
- assert_equal(log1p(c(np.nan, np.nan)), c(np.nan, np.nan))
- def test_lpmv(self):
- assert_equal(cephes.lpmv(0,0,1),1.0)
- def test_mathieu_a(self):
- assert_equal(cephes.mathieu_a(1,0),1.0)
- def test_mathieu_b(self):
- assert_equal(cephes.mathieu_b(1,0),1.0)
- def test_mathieu_cem(self):
- assert_equal(cephes.mathieu_cem(1,0,0),(1.0,0.0))
- # Test AMS 20.2.27
- @np.vectorize
- def ce_smallq(m, q, z):
- z *= np.pi/180
- if m == 0:
- return 2**(-0.5) * (1 - .5*q*cos(2*z)) # + O(q^2)
- elif m == 1:
- return cos(z) - q/8 * cos(3*z) # + O(q^2)
- elif m == 2:
- return cos(2*z) - q*(cos(4*z)/12 - 1/4) # + O(q^2)
- else:
- return cos(m*z) - q*(cos((m+2)*z)/(4*(m+1)) - cos((m-2)*z)/(4*(m-1))) # + O(q^2)
- m = np.arange(0, 100)
- q = np.r_[0, np.logspace(-30, -9, 10)]
- assert_allclose(cephes.mathieu_cem(m[:,None], q[None,:], 0.123)[0],
- ce_smallq(m[:,None], q[None,:], 0.123),
- rtol=1e-14, atol=0)
- def test_mathieu_sem(self):
- assert_equal(cephes.mathieu_sem(1,0,0),(0.0,1.0))
- # Test AMS 20.2.27
- @np.vectorize
- def se_smallq(m, q, z):
- z *= np.pi/180
- if m == 1:
- return sin(z) - q/8 * sin(3*z) # + O(q^2)
- elif m == 2:
- return sin(2*z) - q*sin(4*z)/12 # + O(q^2)
- else:
- return sin(m*z) - q*(sin((m+2)*z)/(4*(m+1)) - sin((m-2)*z)/(4*(m-1))) # + O(q^2)
- m = np.arange(1, 100)
- q = np.r_[0, np.logspace(-30, -9, 10)]
- assert_allclose(cephes.mathieu_sem(m[:,None], q[None,:], 0.123)[0],
- se_smallq(m[:,None], q[None,:], 0.123),
- rtol=1e-14, atol=0)
- def test_mathieu_modcem1(self):
- assert_equal(cephes.mathieu_modcem1(1,0,0),(0.0,0.0))
- def test_mathieu_modcem2(self):
- cephes.mathieu_modcem2(1,1,1)
- # Test reflection relation AMS 20.6.19
- m = np.arange(0, 4)[:,None,None]
- q = np.r_[np.logspace(-2, 2, 10)][None,:,None]
- z = np.linspace(0, 1, 7)[None,None,:]
- y1 = cephes.mathieu_modcem2(m, q, -z)[0]
- fr = -cephes.mathieu_modcem2(m, q, 0)[0] / cephes.mathieu_modcem1(m, q, 0)[0]
- y2 = -cephes.mathieu_modcem2(m, q, z)[0] - 2*fr*cephes.mathieu_modcem1(m, q, z)[0]
- assert_allclose(y1, y2, rtol=1e-10)
- def test_mathieu_modsem1(self):
- assert_equal(cephes.mathieu_modsem1(1,0,0),(0.0,0.0))
- def test_mathieu_modsem2(self):
- cephes.mathieu_modsem2(1,1,1)
- # Test reflection relation AMS 20.6.20
- m = np.arange(1, 4)[:,None,None]
- q = np.r_[np.logspace(-2, 2, 10)][None,:,None]
- z = np.linspace(0, 1, 7)[None,None,:]
- y1 = cephes.mathieu_modsem2(m, q, -z)[0]
- fr = cephes.mathieu_modsem2(m, q, 0)[1] / cephes.mathieu_modsem1(m, q, 0)[1]
- y2 = cephes.mathieu_modsem2(m, q, z)[0] - 2*fr*cephes.mathieu_modsem1(m, q, z)[0]
- assert_allclose(y1, y2, rtol=1e-10)
- def test_mathieu_overflow(self):
- # Check that these return NaNs instead of causing a SEGV
- assert_equal(cephes.mathieu_cem(10000, 0, 1.3), (np.nan, np.nan))
- assert_equal(cephes.mathieu_sem(10000, 0, 1.3), (np.nan, np.nan))
- assert_equal(cephes.mathieu_cem(10000, 1.5, 1.3), (np.nan, np.nan))
- assert_equal(cephes.mathieu_sem(10000, 1.5, 1.3), (np.nan, np.nan))
- assert_equal(cephes.mathieu_modcem1(10000, 1.5, 1.3), (np.nan, np.nan))
- assert_equal(cephes.mathieu_modsem1(10000, 1.5, 1.3), (np.nan, np.nan))
- assert_equal(cephes.mathieu_modcem2(10000, 1.5, 1.3), (np.nan, np.nan))
- assert_equal(cephes.mathieu_modsem2(10000, 1.5, 1.3), (np.nan, np.nan))
- def test_mathieu_ticket_1847(self):
- # Regression test --- this call had some out-of-bounds access
- # and could return nan occasionally
- for k in range(60):
- v = cephes.mathieu_modsem2(2, 100, -1)
- # Values from ACM TOMS 804 (derivate by numerical differentiation)
- assert_allclose(v[0], 0.1431742913063671074347, rtol=1e-10)
- assert_allclose(v[1], 0.9017807375832909144719, rtol=1e-4)
- def test_modfresnelm(self):
- cephes.modfresnelm(0)
- def test_modfresnelp(self):
- cephes.modfresnelp(0)
- def _check_modstruve(self):
- assert_equal(cephes.modstruve(1,0),0.0)
- def test_nbdtr(self):
- assert_equal(cephes.nbdtr(1,1,1),1.0)
- def test_nbdtrc(self):
- assert_equal(cephes.nbdtrc(1,1,1),0.0)
- def test_nbdtri(self):
- assert_equal(cephes.nbdtri(1,1,1),1.0)
- def __check_nbdtrik(self):
- cephes.nbdtrik(1,.4,.5)
- def test_nbdtrin(self):
- assert_equal(cephes.nbdtrin(1,0,0),5.0)
- def test_ncfdtr(self):
- assert_equal(cephes.ncfdtr(1,1,1,0),0.0)
- def test_ncfdtri(self):
- assert_equal(cephes.ncfdtri(1, 1, 1, 0), 0.0)
- f = [0.5, 1, 1.5]
- p = cephes.ncfdtr(2, 3, 1.5, f)
- assert_allclose(cephes.ncfdtri(2, 3, 1.5, p), f)
- def test_ncfdtridfd(self):
- dfd = [1, 2, 3]
- p = cephes.ncfdtr(2, dfd, 0.25, 15)
- assert_allclose(cephes.ncfdtridfd(2, p, 0.25, 15), dfd)
- def test_ncfdtridfn(self):
- dfn = [0.1, 1, 2, 3, 1e4]
- p = cephes.ncfdtr(dfn, 2, 0.25, 15)
- assert_allclose(cephes.ncfdtridfn(p, 2, 0.25, 15), dfn, rtol=1e-5)
- def test_ncfdtrinc(self):
- nc = [0.5, 1.5, 2.0]
- p = cephes.ncfdtr(2, 3, nc, 15)
- assert_allclose(cephes.ncfdtrinc(2, 3, p, 15), nc)
- def test_nctdtr(self):
- assert_equal(cephes.nctdtr(1,0,0),0.5)
- assert_equal(cephes.nctdtr(9, 65536, 45), 0.0)
- assert_approx_equal(cephes.nctdtr(np.inf, 1., 1.), 0.5, 5)
- assert_(np.isnan(cephes.nctdtr(2., np.inf, 10.)))
- assert_approx_equal(cephes.nctdtr(2., 1., np.inf), 1.)
- assert_(np.isnan(cephes.nctdtr(np.nan, 1., 1.)))
- assert_(np.isnan(cephes.nctdtr(2., np.nan, 1.)))
- assert_(np.isnan(cephes.nctdtr(2., 1., np.nan)))
- def __check_nctdtridf(self):
- cephes.nctdtridf(1,0.5,0)
- def test_nctdtrinc(self):
- cephes.nctdtrinc(1,0,0)
- def test_nctdtrit(self):
- cephes.nctdtrit(.1,0.2,.5)
- def test_nrdtrimn(self):
- assert_approx_equal(cephes.nrdtrimn(0.5,1,1),1.0)
- def test_nrdtrisd(self):
- assert_allclose(cephes.nrdtrisd(0.5,0.5,0.5), 0.0,
- atol=0, rtol=0)
- def test_obl_ang1(self):
- cephes.obl_ang1(1,1,1,0)
- def test_obl_ang1_cv(self):
- result = cephes.obl_ang1_cv(1,1,1,1,0)
- assert_almost_equal(result[0],1.0)
- assert_almost_equal(result[1],0.0)
- def _check_obl_cv(self):
- assert_equal(cephes.obl_cv(1,1,0),2.0)
- def test_obl_rad1(self):
- cephes.obl_rad1(1,1,1,0)
- def test_obl_rad1_cv(self):
- cephes.obl_rad1_cv(1,1,1,1,0)
- def test_obl_rad2(self):
- cephes.obl_rad2(1,1,1,0)
- def test_obl_rad2_cv(self):
- cephes.obl_rad2_cv(1,1,1,1,0)
- def test_pbdv(self):
- assert_equal(cephes.pbdv(1,0),(0.0,1.0))
- def test_pbvv(self):
- cephes.pbvv(1,0)
- def test_pbwa(self):
- cephes.pbwa(1,0)
- def test_pdtr(self):
- val = cephes.pdtr(0, 1)
- assert_almost_equal(val, np.exp(-1))
- # Edge case: m = 0.
- val = cephes.pdtr([0, 1, 2], 0)
- assert_array_equal(val, [1, 1, 1])
- def test_pdtrc(self):
- val = cephes.pdtrc(0, 1)
- assert_almost_equal(val, 1 - np.exp(-1))
- # Edge case: m = 0.
- val = cephes.pdtrc([0, 1, 2], 0.0)
- assert_array_equal(val, [0, 0, 0])
- def test_pdtri(self):
- with suppress_warnings() as sup:
- sup.filter(RuntimeWarning, "floating point number truncated to an integer")
- cephes.pdtri(0.5,0.5)
- def test_pdtrik(self):
- k = cephes.pdtrik(0.5, 1)
- assert_almost_equal(cephes.gammaincc(k + 1, 1), 0.5)
- # Edge case: m = 0 or very small.
- k = cephes.pdtrik([[0], [0.25], [0.95]], [0, 1e-20, 1e-6])
- assert_array_equal(k, np.zeros((3, 3)))
- def test_pro_ang1(self):
- cephes.pro_ang1(1,1,1,0)
- def test_pro_ang1_cv(self):
- assert_array_almost_equal(cephes.pro_ang1_cv(1,1,1,1,0),
- array((1.0,0.0)))
- def _check_pro_cv(self):
- assert_equal(cephes.pro_cv(1,1,0),2.0)
- def test_pro_rad1(self):
- cephes.pro_rad1(1,1,1,0.1)
- def test_pro_rad1_cv(self):
- cephes.pro_rad1_cv(1,1,1,1,0)
- def test_pro_rad2(self):
- cephes.pro_rad2(1,1,1,0)
- def test_pro_rad2_cv(self):
- cephes.pro_rad2_cv(1,1,1,1,0)
- def test_psi(self):
- cephes.psi(1)
- def test_radian(self):
- assert_equal(cephes.radian(0,0,0),0)
- def test_rgamma(self):
- assert_equal(cephes.rgamma(1),1.0)
- def test_round(self):
- assert_equal(cephes.round(3.4),3.0)
- assert_equal(cephes.round(-3.4),-3.0)
- assert_equal(cephes.round(3.6),4.0)
- assert_equal(cephes.round(-3.6),-4.0)
- assert_equal(cephes.round(3.5),4.0)
- assert_equal(cephes.round(-3.5),-4.0)
- def test_shichi(self):
- cephes.shichi(1)
- def test_sici(self):
- cephes.sici(1)
- s, c = cephes.sici(np.inf)
- assert_almost_equal(s, np.pi * 0.5)
- assert_almost_equal(c, 0)
- s, c = cephes.sici(-np.inf)
- assert_almost_equal(s, -np.pi * 0.5)
- assert_(np.isnan(c), "cosine integral(-inf) is not nan")
- def test_sindg(self):
- assert_equal(cephes.sindg(90),1.0)
- def test_smirnov(self):
- assert_equal(cephes.smirnov(1,.1),0.9)
- assert_(np.isnan(cephes.smirnov(1,np.nan)))
- def test_smirnovp(self):
- assert_equal(cephes._smirnovp(1, .1), -1)
- assert_equal(cephes._smirnovp(2, 0.75), -2*(0.25)**(2-1))
- assert_equal(cephes._smirnovp(3, 0.75), -3*(0.25)**(3-1))
- assert_(np.isnan(cephes._smirnovp(1, np.nan)))
- def test_smirnovc(self):
- assert_equal(cephes._smirnovc(1,.1),0.1)
- assert_(np.isnan(cephes._smirnovc(1,np.nan)))
- x10 = np.linspace(0, 1, 11, endpoint=True)
- assert_almost_equal(cephes._smirnovc(3, x10), 1-cephes.smirnov(3, x10))
- x4 = np.linspace(0, 1, 5, endpoint=True)
- assert_almost_equal(cephes._smirnovc(4, x4), 1-cephes.smirnov(4, x4))
- def test_smirnovi(self):
- assert_almost_equal(cephes.smirnov(1,cephes.smirnovi(1,0.4)),0.4)
- assert_almost_equal(cephes.smirnov(1,cephes.smirnovi(1,0.6)),0.6)
- assert_(np.isnan(cephes.smirnovi(1,np.nan)))
- def test_smirnovci(self):
- assert_almost_equal(cephes._smirnovc(1,cephes._smirnovci(1,0.4)),0.4)
- assert_almost_equal(cephes._smirnovc(1,cephes._smirnovci(1,0.6)),0.6)
- assert_(np.isnan(cephes._smirnovci(1,np.nan)))
- def test_spence(self):
- assert_equal(cephes.spence(1),0.0)
- def test_stdtr(self):
- assert_equal(cephes.stdtr(1,0),0.5)
- assert_almost_equal(cephes.stdtr(1,1), 0.75)
- assert_almost_equal(cephes.stdtr(1,2), 0.852416382349)
- def test_stdtridf(self):
- cephes.stdtridf(0.7,1)
- def test_stdtrit(self):
- cephes.stdtrit(1,0.7)
- def test_struve(self):
- assert_equal(cephes.struve(0,0),0.0)
- def test_tandg(self):
- assert_equal(cephes.tandg(45),1.0)
- def test_tklmbda(self):
- assert_almost_equal(cephes.tklmbda(1,1),1.0)
- def test_y0(self):
- cephes.y0(1)
- def test_y1(self):
- cephes.y1(1)
- def test_yn(self):
- cephes.yn(1,1)
- def test_yv(self):
- cephes.yv(1,1)
- def _check_yve(self):
- cephes.yve(1,1)
- def test_wofz(self):
- z = [complex(624.2,-0.26123), complex(-0.4,3.), complex(0.6,2.),
- complex(-1.,1.), complex(-1.,-9.), complex(-1.,9.),
- complex(-0.0000000234545,1.1234), complex(-3.,5.1),
- complex(-53,30.1), complex(0.0,0.12345),
- complex(11,1), complex(-22,-2), complex(9,-28),
- complex(21,-33), complex(1e5,1e5), complex(1e14,1e14)
- ]
- w = [
- complex(-3.78270245518980507452677445620103199303131110e-7,
- 0.000903861276433172057331093754199933411710053155),
- complex(0.1764906227004816847297495349730234591778719532788,
- -0.02146550539468457616788719893991501311573031095617),
- complex(0.2410250715772692146133539023007113781272362309451,
- 0.06087579663428089745895459735240964093522265589350),
- complex(0.30474420525691259245713884106959496013413834051768,
- -0.20821893820283162728743734725471561394145872072738),
- complex(7.317131068972378096865595229600561710140617977e34,
- 8.321873499714402777186848353320412813066170427e34),
- complex(0.0615698507236323685519612934241429530190806818395,
- -0.00676005783716575013073036218018565206070072304635),
- complex(0.3960793007699874918961319170187598400134746631,
- -5.593152259116644920546186222529802777409274656e-9),
- complex(0.08217199226739447943295069917990417630675021771804,
- -0.04701291087643609891018366143118110965272615832184),
- complex(0.00457246000350281640952328010227885008541748668738,
- -0.00804900791411691821818731763401840373998654987934),
- complex(0.8746342859608052666092782112565360755791467973338452,
- 0.),
- complex(0.00468190164965444174367477874864366058339647648741,
- 0.0510735563901306197993676329845149741675029197050),
- complex(-0.0023193175200187620902125853834909543869428763219,
- -0.025460054739731556004902057663500272721780776336),
- complex(9.11463368405637174660562096516414499772662584e304,
- 3.97101807145263333769664875189354358563218932e305),
- complex(-4.4927207857715598976165541011143706155432296e281,
- -2.8019591213423077494444700357168707775769028e281),
- complex(2.820947917809305132678577516325951485807107151e-6,
- 2.820947917668257736791638444590253942253354058e-6),
- complex(2.82094791773878143474039725787438662716372268e-15,
- 2.82094791773878143474039725773333923127678361e-15)
- ]
- assert_func_equal(cephes.wofz, w, z, rtol=1e-13)
- class TestAiry:
- def test_airy(self):
- # This tests the airy function to ensure 8 place accuracy in computation
- x = special.airy(.99)
- assert_array_almost_equal(x,array([0.13689066,-0.16050153,1.19815925,0.92046818]),8)
- x = special.airy(.41)
- assert_array_almost_equal(x,array([0.25238916,-.23480512,0.80686202,0.51053919]),8)
- x = special.airy(-.36)
- assert_array_almost_equal(x,array([0.44508477,-0.23186773,0.44939534,0.48105354]),8)
- def test_airye(self):
- a = special.airye(0.01)
- b = special.airy(0.01)
- b1 = [None]*4
- for n in range(2):
- b1[n] = b[n]*exp(2.0/3.0*0.01*sqrt(0.01))
- for n in range(2,4):
- b1[n] = b[n]*exp(-abs(real(2.0/3.0*0.01*sqrt(0.01))))
- assert_array_almost_equal(a,b1,6)
- def test_bi_zeros(self):
- bi = special.bi_zeros(2)
- bia = (array([-1.17371322, -3.2710930]),
- array([-2.29443968, -4.07315509]),
- array([-0.45494438, 0.39652284]),
- array([0.60195789, -0.76031014]))
- assert_array_almost_equal(bi,bia,4)
- bi = special.bi_zeros(5)
- assert_array_almost_equal(bi[0],array([-1.173713222709127,
- -3.271093302836352,
- -4.830737841662016,
- -6.169852128310251,
- -7.376762079367764]),11)
- assert_array_almost_equal(bi[1],array([-2.294439682614122,
- -4.073155089071828,
- -5.512395729663599,
- -6.781294445990305,
- -7.940178689168587]),10)
- assert_array_almost_equal(bi[2],array([-0.454944383639657,
- 0.396522836094465,
- -0.367969161486959,
- 0.349499116831805,
- -0.336026240133662]),11)
- assert_array_almost_equal(bi[3],array([0.601957887976239,
- -0.760310141492801,
- 0.836991012619261,
- -0.88947990142654,
- 0.929983638568022]),10)
- def test_ai_zeros(self):
- ai = special.ai_zeros(1)
- assert_array_almost_equal(ai,(array([-2.33810741]),
- array([-1.01879297]),
- array([0.5357]),
- array([0.7012])),4)
- def test_ai_zeros_big(self):
- z, zp, ai_zpx, aip_zx = special.ai_zeros(50000)
- ai_z, aip_z, _, _ = special.airy(z)
- ai_zp, aip_zp, _, _ = special.airy(zp)
- ai_envelope = 1/abs(z)**(1./4)
- aip_envelope = abs(zp)**(1./4)
- # Check values
- assert_allclose(ai_zpx, ai_zp, rtol=1e-10)
- assert_allclose(aip_zx, aip_z, rtol=1e-10)
- # Check they are zeros
- assert_allclose(ai_z/ai_envelope, 0, atol=1e-10, rtol=0)
- assert_allclose(aip_zp/aip_envelope, 0, atol=1e-10, rtol=0)
- # Check first zeros, DLMF 9.9.1
- assert_allclose(z[:6],
- [-2.3381074105, -4.0879494441, -5.5205598281,
- -6.7867080901, -7.9441335871, -9.0226508533], rtol=1e-10)
- assert_allclose(zp[:6],
- [-1.0187929716, -3.2481975822, -4.8200992112,
- -6.1633073556, -7.3721772550, -8.4884867340], rtol=1e-10)
- def test_bi_zeros_big(self):
- z, zp, bi_zpx, bip_zx = special.bi_zeros(50000)
- _, _, bi_z, bip_z = special.airy(z)
- _, _, bi_zp, bip_zp = special.airy(zp)
- bi_envelope = 1/abs(z)**(1./4)
- bip_envelope = abs(zp)**(1./4)
- # Check values
- assert_allclose(bi_zpx, bi_zp, rtol=1e-10)
- assert_allclose(bip_zx, bip_z, rtol=1e-10)
- # Check they are zeros
- assert_allclose(bi_z/bi_envelope, 0, atol=1e-10, rtol=0)
- assert_allclose(bip_zp/bip_envelope, 0, atol=1e-10, rtol=0)
- # Check first zeros, DLMF 9.9.2
- assert_allclose(z[:6],
- [-1.1737132227, -3.2710933028, -4.8307378417,
- -6.1698521283, -7.3767620794, -8.4919488465], rtol=1e-10)
- assert_allclose(zp[:6],
- [-2.2944396826, -4.0731550891, -5.5123957297,
- -6.7812944460, -7.9401786892, -9.0195833588], rtol=1e-10)
- class TestAssocLaguerre:
- def test_assoc_laguerre(self):
- a1 = special.genlaguerre(11,1)
- a2 = special.assoc_laguerre(.2,11,1)
- assert_array_almost_equal(a2,a1(.2),8)
- a2 = special.assoc_laguerre(1,11,1)
- assert_array_almost_equal(a2,a1(1),8)
- class TestBesselpoly:
- def test_besselpoly(self):
- pass
- class TestKelvin:
- def test_bei(self):
- mbei = special.bei(2)
- assert_almost_equal(mbei, 0.9722916273066613,5) # this may not be exact
- def test_beip(self):
- mbeip = special.beip(2)
- assert_almost_equal(mbeip,0.91701361338403631,5) # this may not be exact
- def test_ber(self):
- mber = special.ber(2)
- assert_almost_equal(mber,0.75173418271380821,5) # this may not be exact
- def test_berp(self):
- mberp = special.berp(2)
- assert_almost_equal(mberp,-0.49306712470943909,5) # this may not be exact
- def test_bei_zeros(self):
- # Abramowitz & Stegun, Table 9.12
- bi = special.bei_zeros(5)
- assert_array_almost_equal(bi,array([5.02622,
- 9.45541,
- 13.89349,
- 18.33398,
- 22.77544]),4)
- def test_beip_zeros(self):
- bip = special.beip_zeros(5)
- assert_array_almost_equal(bip,array([3.772673304934953,
- 8.280987849760042,
- 12.742147523633703,
- 17.193431752512542,
- 21.641143941167325]),8)
- def test_ber_zeros(self):
- ber = special.ber_zeros(5)
- assert_array_almost_equal(ber,array([2.84892,
- 7.23883,
- 11.67396,
- 16.11356,
- 20.55463]),4)
- def test_berp_zeros(self):
- brp = special.berp_zeros(5)
- assert_array_almost_equal(brp,array([6.03871,
- 10.51364,
- 14.96844,
- 19.41758,
- 23.86430]),4)
- def test_kelvin(self):
- mkelv = special.kelvin(2)
- assert_array_almost_equal(mkelv,(special.ber(2) + special.bei(2)*1j,
- special.ker(2) + special.kei(2)*1j,
- special.berp(2) + special.beip(2)*1j,
- special.kerp(2) + special.keip(2)*1j),8)
- def test_kei(self):
- mkei = special.kei(2)
- assert_almost_equal(mkei,-0.20240006776470432,5)
- def test_keip(self):
- mkeip = special.keip(2)
- assert_almost_equal(mkeip,0.21980790991960536,5)
- def test_ker(self):
- mker = special.ker(2)
- assert_almost_equal(mker,-0.041664513991509472,5)
- def test_kerp(self):
- mkerp = special.kerp(2)
- assert_almost_equal(mkerp,-0.10660096588105264,5)
- def test_kei_zeros(self):
- kei = special.kei_zeros(5)
- assert_array_almost_equal(kei,array([3.91467,
- 8.34422,
- 12.78256,
- 17.22314,
- 21.66464]),4)
- def test_keip_zeros(self):
- keip = special.keip_zeros(5)
- assert_array_almost_equal(keip,array([4.93181,
- 9.40405,
- 13.85827,
- 18.30717,
- 22.75379]),4)
- # numbers come from 9.9 of A&S pg. 381
- def test_kelvin_zeros(self):
- tmp = special.kelvin_zeros(5)
- berz,beiz,kerz,keiz,berpz,beipz,kerpz,keipz = tmp
- assert_array_almost_equal(berz,array([2.84892,
- 7.23883,
- 11.67396,
- 16.11356,
- 20.55463]),4)
- assert_array_almost_equal(beiz,array([5.02622,
- 9.45541,
- 13.89349,
- 18.33398,
- 22.77544]),4)
- assert_array_almost_equal(kerz,array([1.71854,
- 6.12728,
- 10.56294,
- 15.00269,
- 19.44382]),4)
- assert_array_almost_equal(keiz,array([3.91467,
- 8.34422,
- 12.78256,
- 17.22314,
- 21.66464]),4)
- assert_array_almost_equal(berpz,array([6.03871,
- 10.51364,
- 14.96844,
- 19.41758,
- 23.86430]),4)
- assert_array_almost_equal(beipz,array([3.77267,
- # table from 1927 had 3.77320
- # but this is more accurate
- 8.28099,
- 12.74215,
- 17.19343,
- 21.64114]),4)
- assert_array_almost_equal(kerpz,array([2.66584,
- 7.17212,
- 11.63218,
- 16.08312,
- 20.53068]),4)
- assert_array_almost_equal(keipz,array([4.93181,
- 9.40405,
- 13.85827,
- 18.30717,
- 22.75379]),4)
- def test_ker_zeros(self):
- ker = special.ker_zeros(5)
- assert_array_almost_equal(ker,array([1.71854,
- 6.12728,
- 10.56294,
- 15.00269,
- 19.44381]),4)
- def test_kerp_zeros(self):
- kerp = special.kerp_zeros(5)
- assert_array_almost_equal(kerp,array([2.66584,
- 7.17212,
- 11.63218,
- 16.08312,
- 20.53068]),4)
- class TestBernoulli:
- def test_bernoulli(self):
- brn = special.bernoulli(5)
- assert_array_almost_equal(brn,array([1.0000,
- -0.5000,
- 0.1667,
- 0.0000,
- -0.0333,
- 0.0000]),4)
- class TestBeta:
- def test_beta(self):
- bet = special.beta(2,4)
- betg = (special.gamma(2)*special.gamma(4))/special.gamma(6)
- assert_almost_equal(bet,betg,8)
- def test_betaln(self):
- betln = special.betaln(2,4)
- bet = log(abs(special.beta(2,4)))
- assert_almost_equal(betln,bet,8)
- def test_betainc(self):
- btinc = special.betainc(1,1,.2)
- assert_almost_equal(btinc,0.2,8)
- def test_betaincinv(self):
- y = special.betaincinv(2,4,.5)
- comp = special.betainc(2,4,y)
- assert_almost_equal(comp,.5,5)
- class TestCombinatorics:
- def test_comb(self):
- assert_array_almost_equal(special.comb([10, 10], [3, 4]), [120., 210.])
- assert_almost_equal(special.comb(10, 3), 120.)
- assert_equal(special.comb(10, 3, exact=True), 120)
- assert_equal(special.comb(10, 3, exact=True, repetition=True), 220)
- assert_allclose([special.comb(20, k, exact=True) for k in range(21)],
- special.comb(20, list(range(21))), atol=1e-15)
- ii = np.iinfo(int).max + 1
- assert_equal(special.comb(ii, ii-1, exact=True), ii)
- expected = 100891344545564193334812497256
- assert special.comb(100, 50, exact=True) == expected
- @pytest.mark.parametrize("repetition", [True, False])
- @pytest.mark.parametrize("legacy", [True, False])
- @pytest.mark.parametrize("k", [3.5, 3])
- @pytest.mark.parametrize("N", [4.5, 4])
- def test_comb_legacy(self, N, k, legacy, repetition):
- # test is only relevant for exact=True
- if legacy and (N != int(N) or k != int(k)):
- with pytest.warns(
- DeprecationWarning,
- match=r"Non-integer arguments are currently being cast to",
- ):
- result = special.comb(N, k, exact=True, legacy=legacy,
- repetition=repetition)
- else:
- result = special.comb(N, k, exact=True, legacy=legacy,
- repetition=repetition)
- if legacy:
- # for exact=True and legacy=True, cast input arguments, else don't
- if repetition:
- # the casting in legacy mode happens AFTER transforming N & k,
- # so rounding can change (e.g. both floats, but sum to int);
- # hence we need to emulate the repetition-transformation here
- N, k = int(N + k - 1), int(k)
- repetition = False
- else:
- N, k = int(N), int(k)
- # expected result is the same as with exact=False
- expected = special.comb(N, k, legacy=legacy, repetition=repetition)
- assert_equal(result, expected)
- def test_comb_with_np_int64(self):
- n = 70
- k = 30
- np_n = np.int64(n)
- np_k = np.int64(k)
- res_np = special.comb(np_n, np_k, exact=True)
- res_py = special.comb(n, k, exact=True)
- assert res_np == res_py
- def test_comb_zeros(self):
- assert_equal(special.comb(2, 3, exact=True), 0)
- assert_equal(special.comb(-1, 3, exact=True), 0)
- assert_equal(special.comb(2, -1, exact=True), 0)
- assert_equal(special.comb(2, -1, exact=False), 0)
- assert_array_almost_equal(special.comb([2, -1, 2, 10], [3, 3, -1, 3]),
- [0., 0., 0., 120.])
- def test_perm(self):
- assert_array_almost_equal(special.perm([10, 10], [3, 4]), [720., 5040.])
- assert_almost_equal(special.perm(10, 3), 720.)
- assert_equal(special.perm(10, 3, exact=True), 720)
- def test_perm_zeros(self):
- assert_equal(special.perm(2, 3, exact=True), 0)
- assert_equal(special.perm(-1, 3, exact=True), 0)
- assert_equal(special.perm(2, -1, exact=True), 0)
- assert_equal(special.perm(2, -1, exact=False), 0)
- assert_array_almost_equal(special.perm([2, -1, 2, 10], [3, 3, -1, 3]),
- [0., 0., 0., 720.])
- class TestTrigonometric:
- def test_cbrt(self):
- cb = special.cbrt(27)
- cbrl = 27**(1.0/3.0)
- assert_approx_equal(cb,cbrl)
- def test_cbrtmore(self):
- cb1 = special.cbrt(27.9)
- cbrl1 = 27.9**(1.0/3.0)
- assert_almost_equal(cb1,cbrl1,8)
- def test_cosdg(self):
- cdg = special.cosdg(90)
- cdgrl = cos(pi/2.0)
- assert_almost_equal(cdg,cdgrl,8)
- def test_cosdgmore(self):
- cdgm = special.cosdg(30)
- cdgmrl = cos(pi/6.0)
- assert_almost_equal(cdgm,cdgmrl,8)
- def test_cosm1(self):
- cs = (special.cosm1(0),special.cosm1(.3),special.cosm1(pi/10))
- csrl = (cos(0)-1,cos(.3)-1,cos(pi/10)-1)
- assert_array_almost_equal(cs,csrl,8)
- def test_cotdg(self):
- ct = special.cotdg(30)
- ctrl = tan(pi/6.0)**(-1)
- assert_almost_equal(ct,ctrl,8)
- def test_cotdgmore(self):
- ct1 = special.cotdg(45)
- ctrl1 = tan(pi/4.0)**(-1)
- assert_almost_equal(ct1,ctrl1,8)
- def test_specialpoints(self):
- assert_almost_equal(special.cotdg(45), 1.0, 14)
- assert_almost_equal(special.cotdg(-45), -1.0, 14)
- assert_almost_equal(special.cotdg(90), 0.0, 14)
- assert_almost_equal(special.cotdg(-90), 0.0, 14)
- assert_almost_equal(special.cotdg(135), -1.0, 14)
- assert_almost_equal(special.cotdg(-135), 1.0, 14)
- assert_almost_equal(special.cotdg(225), 1.0, 14)
- assert_almost_equal(special.cotdg(-225), -1.0, 14)
- assert_almost_equal(special.cotdg(270), 0.0, 14)
- assert_almost_equal(special.cotdg(-270), 0.0, 14)
- assert_almost_equal(special.cotdg(315), -1.0, 14)
- assert_almost_equal(special.cotdg(-315), 1.0, 14)
- assert_almost_equal(special.cotdg(765), 1.0, 14)
- def test_sinc(self):
- # the sinc implementation and more extensive sinc tests are in numpy
- assert_array_equal(special.sinc([0]), 1)
- assert_equal(special.sinc(0.0), 1.0)
- def test_sindg(self):
- sn = special.sindg(90)
- assert_equal(sn,1.0)
- def test_sindgmore(self):
- snm = special.sindg(30)
- snmrl = sin(pi/6.0)
- assert_almost_equal(snm,snmrl,8)
- snm1 = special.sindg(45)
- snmrl1 = sin(pi/4.0)
- assert_almost_equal(snm1,snmrl1,8)
- class TestTandg:
- def test_tandg(self):
- tn = special.tandg(30)
- tnrl = tan(pi/6.0)
- assert_almost_equal(tn,tnrl,8)
- def test_tandgmore(self):
- tnm = special.tandg(45)
- tnmrl = tan(pi/4.0)
- assert_almost_equal(tnm,tnmrl,8)
- tnm1 = special.tandg(60)
- tnmrl1 = tan(pi/3.0)
- assert_almost_equal(tnm1,tnmrl1,8)
- def test_specialpoints(self):
- assert_almost_equal(special.tandg(0), 0.0, 14)
- assert_almost_equal(special.tandg(45), 1.0, 14)
- assert_almost_equal(special.tandg(-45), -1.0, 14)
- assert_almost_equal(special.tandg(135), -1.0, 14)
- assert_almost_equal(special.tandg(-135), 1.0, 14)
- assert_almost_equal(special.tandg(180), 0.0, 14)
- assert_almost_equal(special.tandg(-180), 0.0, 14)
- assert_almost_equal(special.tandg(225), 1.0, 14)
- assert_almost_equal(special.tandg(-225), -1.0, 14)
- assert_almost_equal(special.tandg(315), -1.0, 14)
- assert_almost_equal(special.tandg(-315), 1.0, 14)
- class TestEllip:
- def test_ellipj_nan(self):
- """Regression test for #912."""
- special.ellipj(0.5, np.nan)
- def test_ellipj(self):
- el = special.ellipj(0.2,0)
- rel = [sin(0.2),cos(0.2),1.0,0.20]
- assert_array_almost_equal(el,rel,13)
- def test_ellipk(self):
- elk = special.ellipk(.2)
- assert_almost_equal(elk,1.659623598610528,11)
- assert_equal(special.ellipkm1(0.0), np.inf)
- assert_equal(special.ellipkm1(1.0), pi/2)
- assert_equal(special.ellipkm1(np.inf), 0.0)
- assert_equal(special.ellipkm1(np.nan), np.nan)
- assert_equal(special.ellipkm1(-1), np.nan)
- assert_allclose(special.ellipk(-10), 0.7908718902387385)
- def test_ellipkinc(self):
- elkinc = special.ellipkinc(pi/2,.2)
- elk = special.ellipk(0.2)
- assert_almost_equal(elkinc,elk,15)
- alpha = 20*pi/180
- phi = 45*pi/180
- m = sin(alpha)**2
- elkinc = special.ellipkinc(phi,m)
- assert_almost_equal(elkinc,0.79398143,8)
- # From pg. 614 of A & S
- assert_equal(special.ellipkinc(pi/2, 0.0), pi/2)
- assert_equal(special.ellipkinc(pi/2, 1.0), np.inf)
- assert_equal(special.ellipkinc(pi/2, -np.inf), 0.0)
- assert_equal(special.ellipkinc(pi/2, np.nan), np.nan)
- assert_equal(special.ellipkinc(pi/2, 2), np.nan)
- assert_equal(special.ellipkinc(0, 0.5), 0.0)
- assert_equal(special.ellipkinc(np.inf, 0.5), np.inf)
- assert_equal(special.ellipkinc(-np.inf, 0.5), -np.inf)
- assert_equal(special.ellipkinc(np.inf, np.inf), np.nan)
- assert_equal(special.ellipkinc(np.inf, -np.inf), np.nan)
- assert_equal(special.ellipkinc(-np.inf, -np.inf), np.nan)
- assert_equal(special.ellipkinc(-np.inf, np.inf), np.nan)
- assert_equal(special.ellipkinc(np.nan, 0.5), np.nan)
- assert_equal(special.ellipkinc(np.nan, np.nan), np.nan)
- assert_allclose(special.ellipkinc(0.38974112035318718, 1), 0.4, rtol=1e-14)
- assert_allclose(special.ellipkinc(1.5707, -10), 0.79084284661724946)
- def test_ellipkinc_2(self):
- # Regression test for gh-3550
- # ellipkinc(phi, mbad) was NaN and mvals[2:6] were twice the correct value
- mbad = 0.68359375000000011
- phi = 0.9272952180016123
- m = np.nextafter(mbad, 0)
- mvals = []
- for j in range(10):
- mvals.append(m)
- m = np.nextafter(m, 1)
- f = special.ellipkinc(phi, mvals)
- assert_array_almost_equal_nulp(f, np.full_like(f, 1.0259330100195334), 1)
- # this bug also appears at phi + n * pi for at least small n
- f1 = special.ellipkinc(phi + pi, mvals)
- assert_array_almost_equal_nulp(f1, np.full_like(f1, 5.1296650500976675), 2)
- def test_ellipkinc_singular(self):
- # ellipkinc(phi, 1) has closed form and is finite only for phi in (-pi/2, pi/2)
- xlog = np.logspace(-300, -17, 25)
- xlin = np.linspace(1e-17, 0.1, 25)
- xlin2 = np.linspace(0.1, pi/2, 25, endpoint=False)
- assert_allclose(special.ellipkinc(xlog, 1), np.arcsinh(np.tan(xlog)), rtol=1e14)
- assert_allclose(special.ellipkinc(xlin, 1), np.arcsinh(np.tan(xlin)), rtol=1e14)
- assert_allclose(special.ellipkinc(xlin2, 1), np.arcsinh(np.tan(xlin2)), rtol=1e14)
- assert_equal(special.ellipkinc(np.pi/2, 1), np.inf)
- assert_allclose(special.ellipkinc(-xlog, 1), np.arcsinh(np.tan(-xlog)), rtol=1e14)
- assert_allclose(special.ellipkinc(-xlin, 1), np.arcsinh(np.tan(-xlin)), rtol=1e14)
- assert_allclose(special.ellipkinc(-xlin2, 1), np.arcsinh(np.tan(-xlin2)), rtol=1e14)
- assert_equal(special.ellipkinc(-np.pi/2, 1), np.inf)
- def test_ellipe(self):
- ele = special.ellipe(.2)
- assert_almost_equal(ele,1.4890350580958529,8)
- assert_equal(special.ellipe(0.0), pi/2)
- assert_equal(special.ellipe(1.0), 1.0)
- assert_equal(special.ellipe(-np.inf), np.inf)
- assert_equal(special.ellipe(np.nan), np.nan)
- assert_equal(special.ellipe(2), np.nan)
- assert_allclose(special.ellipe(-10), 3.6391380384177689)
- def test_ellipeinc(self):
- eleinc = special.ellipeinc(pi/2,.2)
- ele = special.ellipe(0.2)
- assert_almost_equal(eleinc,ele,14)
- # pg 617 of A & S
- alpha, phi = 52*pi/180,35*pi/180
- m = sin(alpha)**2
- eleinc = special.ellipeinc(phi,m)
- assert_almost_equal(eleinc, 0.58823065, 8)
- assert_equal(special.ellipeinc(pi/2, 0.0), pi/2)
- assert_equal(special.ellipeinc(pi/2, 1.0), 1.0)
- assert_equal(special.ellipeinc(pi/2, -np.inf), np.inf)
- assert_equal(special.ellipeinc(pi/2, np.nan), np.nan)
- assert_equal(special.ellipeinc(pi/2, 2), np.nan)
- assert_equal(special.ellipeinc(0, 0.5), 0.0)
- assert_equal(special.ellipeinc(np.inf, 0.5), np.inf)
- assert_equal(special.ellipeinc(-np.inf, 0.5), -np.inf)
- assert_equal(special.ellipeinc(np.inf, -np.inf), np.inf)
- assert_equal(special.ellipeinc(-np.inf, -np.inf), -np.inf)
- assert_equal(special.ellipeinc(np.inf, np.inf), np.nan)
- assert_equal(special.ellipeinc(-np.inf, np.inf), np.nan)
- assert_equal(special.ellipeinc(np.nan, 0.5), np.nan)
- assert_equal(special.ellipeinc(np.nan, np.nan), np.nan)
- assert_allclose(special.ellipeinc(1.5707, -10), 3.6388185585822876)
- def test_ellipeinc_2(self):
- # Regression test for gh-3550
- # ellipeinc(phi, mbad) was NaN and mvals[2:6] were twice the correct value
- mbad = 0.68359375000000011
- phi = 0.9272952180016123
- m = np.nextafter(mbad, 0)
- mvals = []
- for j in range(10):
- mvals.append(m)
- m = np.nextafter(m, 1)
- f = special.ellipeinc(phi, mvals)
- assert_array_almost_equal_nulp(f, np.full_like(f, 0.84442884574781019), 2)
- # this bug also appears at phi + n * pi for at least small n
- f1 = special.ellipeinc(phi + pi, mvals)
- assert_array_almost_equal_nulp(f1, np.full_like(f1, 3.3471442287390509), 4)
- class TestEllipCarlson(object):
- """Test for Carlson elliptic integrals ellipr[cdfgj].
- The special values used in these tests can be found in Sec. 3 of Carlson
- (1994), https://arxiv.org/abs/math/9409227
- """
- def test_elliprc(self):
- assert_allclose(elliprc(1, 1), 1)
- assert elliprc(1, inf) == 0.0
- assert isnan(elliprc(1, 0))
- assert elliprc(1, complex(1, inf)) == 0.0
- args = array([[0.0, 0.25],
- [2.25, 2.0],
- [0.0, 1.0j],
- [-1.0j, 1.0j],
- [0.25, -2.0],
- [1.0j, -1.0]])
- expected_results = array([np.pi,
- np.log(2.0),
- 1.1107207345396 * (1.0-1.0j),
- 1.2260849569072-0.34471136988768j,
- np.log(2.0) / 3.0,
- 0.77778596920447+0.19832484993429j])
- for i, arr in enumerate(args):
- assert_allclose(elliprc(*arr), expected_results[i])
- def test_elliprd(self):
- assert_allclose(elliprd(1, 1, 1), 1)
- assert_allclose(elliprd(0, 2, 1) / 3.0, 0.59907011736779610371)
- assert elliprd(1, 1, inf) == 0.0
- assert np.isinf(elliprd(1, 1, 0))
- assert np.isinf(elliprd(1, 1, complex(0, 0)))
- assert np.isinf(elliprd(0, 1, complex(0, 0)))
- assert isnan(elliprd(1, 1, -np.finfo(np.double).tiny / 2.0))
- assert isnan(elliprd(1, 1, complex(-1, 0)))
- args = array([[0.0, 2.0, 1.0],
- [2.0, 3.0, 4.0],
- [1.0j, -1.0j, 2.0],
- [0.0, 1.0j, -1.0j],
- [0.0, -1.0+1.0j, 1.0j],
- [-2.0-1.0j, -1.0j, -1.0+1.0j]])
- expected_results = array([1.7972103521034,
- 0.16510527294261,
- 0.65933854154220,
- 1.2708196271910+2.7811120159521j,
- -1.8577235439239-0.96193450888839j,
- 1.8249027393704-1.2218475784827j])
- for i, arr in enumerate(args):
- assert_allclose(elliprd(*arr), expected_results[i])
- def test_elliprf(self):
- assert_allclose(elliprf(1, 1, 1), 1)
- assert_allclose(elliprf(0, 1, 2), 1.31102877714605990523)
- assert elliprf(1, inf, 1) == 0.0
- assert np.isinf(elliprf(0, 1, 0))
- assert isnan(elliprf(1, 1, -1))
- assert elliprf(complex(inf), 0, 1) == 0.0
- assert isnan(elliprf(1, 1, complex(-inf, 1)))
- args = array([[1.0, 2.0, 0.0],
- [1.0j, -1.0j, 0.0],
- [0.5, 1.0, 0.0],
- [-1.0+1.0j, 1.0j, 0.0],
- [2.0, 3.0, 4.0],
- [1.0j, -1.0j, 2.0],
- [-1.0+1.0j, 1.0j, 1.0-1.0j]])
- expected_results = array([1.3110287771461,
- 1.8540746773014,
- 1.8540746773014,
- 0.79612586584234-1.2138566698365j,
- 0.58408284167715,
- 1.0441445654064,
- 0.93912050218619-0.53296252018635j])
- for i, arr in enumerate(args):
- assert_allclose(elliprf(*arr), expected_results[i])
- def test_elliprg(self):
- assert_allclose(elliprg(1, 1, 1), 1)
- assert_allclose(elliprg(0, 0, 1), 0.5)
- assert_allclose(elliprg(0, 0, 0), 0)
- assert np.isinf(elliprg(1, inf, 1))
- assert np.isinf(elliprg(complex(inf), 1, 1))
- args = array([[0.0, 16.0, 16.0],
- [2.0, 3.0, 4.0],
- [0.0, 1.0j, -1.0j],
- [-1.0+1.0j, 1.0j, 0.0],
- [-1.0j, -1.0+1.0j, 1.0j],
- [0.0, 0.0796, 4.0]])
- expected_results = array([np.pi,
- 1.7255030280692,
- 0.42360654239699,
- 0.44660591677018+0.70768352357515j,
- 0.36023392184473+0.40348623401722j,
- 1.0284758090288])
- for i, arr in enumerate(args):
- assert_allclose(elliprg(*arr), expected_results[i])
- def test_elliprj(self):
- assert_allclose(elliprj(1, 1, 1, 1), 1)
- assert elliprj(1, 1, inf, 1) == 0.0
- assert isnan(elliprj(1, 0, 0, 0))
- assert isnan(elliprj(-1, 1, 1, 1))
- assert elliprj(1, 1, 1, inf) == 0.0
- args = array([[0.0, 1.0, 2.0, 3.0],
- [2.0, 3.0, 4.0, 5.0],
- [2.0, 3.0, 4.0, -1.0+1.0j],
- [1.0j, -1.0j, 0.0, 2.0],
- [-1.0+1.0j, -1.0-1.0j, 1.0, 2.0],
- [1.0j, -1.0j, 0.0, 1.0-1.0j],
- [-1.0+1.0j, -1.0-1.0j, 1.0, -3.0+1.0j],
- [2.0, 3.0, 4.0, -0.5], # Cauchy principal value
- [2.0, 3.0, 4.0, -5.0]]) # Cauchy principal value
- expected_results = array([0.77688623778582,
- 0.14297579667157,
- 0.13613945827771-0.38207561624427j,
- 1.6490011662711,
- 0.94148358841220,
- 1.8260115229009+1.2290661908643j,
- -0.61127970812028-1.0684038390007j,
- 0.24723819703052, # Cauchy principal value
- -0.12711230042964]) # Caucny principal value
- for i, arr in enumerate(args):
- assert_allclose(elliprj(*arr), expected_results[i])
- @pytest.mark.xfail(reason="Insufficient accuracy on 32-bit")
- def test_elliprj_hard(self):
- assert_allclose(elliprj(6.483625725195452e-08,
- 1.1649136528196886e-27,
- 3.6767340167168e+13,
- 0.493704617023468),
- 8.63426920644241857617477551054e-6,
- rtol=5e-15, atol=1e-20)
- assert_allclose(elliprj(14.375105857849121,
- 9.993988969725365e-11,
- 1.72844262269944e-26,
- 5.898871222598245e-06),
- 829774.1424801627252574054378691828,
- rtol=5e-15, atol=1e-20)
- class TestEllipLegendreCarlsonIdentities(object):
- """Test identities expressing the Legendre elliptic integrals in terms
- of Carlson's symmetric integrals. These identities can be found
- in the DLMF https://dlmf.nist.gov/19.25#i .
- """
- def setup_class(self):
- self.m_n1_1 = np.arange(-1., 1., 0.01)
- # For double, this is -(2**1024)
- self.max_neg = finfo(float_).min
- # Lots of very negative numbers
- self.very_neg_m = -1. * 2.**arange(-1 +
- np.log2(-self.max_neg), 0.,
- -1.)
- self.ms_up_to_1 = np.concatenate(([self.max_neg],
- self.very_neg_m,
- self.m_n1_1))
- def test_k(self):
- """Test identity:
- K(m) = R_F(0, 1-m, 1)
- """
- m = self.ms_up_to_1
- assert_allclose(ellipk(m), elliprf(0., 1.-m, 1.))
- def test_km1(self):
- """Test identity:
- K(m) = R_F(0, 1-m, 1)
- But with the ellipkm1 function
- """
- # For double, this is 2**-1022
- tiny = finfo(float_).tiny
- # All these small powers of 2, up to 2**-1
- m1 = tiny * 2.**arange(0., -np.log2(tiny))
- assert_allclose(ellipkm1(m1), elliprf(0., m1, 1.))
- def test_e(self):
- """Test identity:
- E(m) = 2*R_G(0, 1-k^2, 1)
- """
- m = self.ms_up_to_1
- assert_allclose(ellipe(m), 2.*elliprg(0., 1.-m, 1.))
- class TestErf:
- def test_erf(self):
- er = special.erf(.25)
- assert_almost_equal(er,0.2763263902,8)
- def test_erf_zeros(self):
- erz = special.erf_zeros(5)
- erzr = array([1.45061616+1.88094300j,
- 2.24465928+2.61657514j,
- 2.83974105+3.17562810j,
- 3.33546074+3.64617438j,
- 3.76900557+4.06069723j])
- assert_array_almost_equal(erz,erzr,4)
- def _check_variant_func(self, func, other_func, rtol, atol=0):
- np.random.seed(1234)
- n = 10000
- x = np.random.pareto(0.02, n) * (2*np.random.randint(0, 2, n) - 1)
- y = np.random.pareto(0.02, n) * (2*np.random.randint(0, 2, n) - 1)
- z = x + 1j*y
- with np.errstate(all='ignore'):
- w = other_func(z)
- w_real = other_func(x).real
- mask = np.isfinite(w)
- w = w[mask]
- z = z[mask]
- mask = np.isfinite(w_real)
- w_real = w_real[mask]
- x = x[mask]
- # test both real and complex variants
- assert_func_equal(func, w, z, rtol=rtol, atol=atol)
- assert_func_equal(func, w_real, x, rtol=rtol, atol=atol)
- def test_erfc_consistent(self):
- self._check_variant_func(
- cephes.erfc,
- lambda z: 1 - cephes.erf(z),
- rtol=1e-12,
- atol=1e-14 # <- the test function loses precision
- )
- def test_erfcx_consistent(self):
- self._check_variant_func(
- cephes.erfcx,
- lambda z: np.exp(z*z) * cephes.erfc(z),
- rtol=1e-12
- )
- def test_erfi_consistent(self):
- self._check_variant_func(
- cephes.erfi,
- lambda z: -1j * cephes.erf(1j*z),
- rtol=1e-12
- )
- def test_dawsn_consistent(self):
- self._check_variant_func(
- cephes.dawsn,
- lambda z: sqrt(pi)/2 * np.exp(-z*z) * cephes.erfi(z),
- rtol=1e-12
- )
- def test_erf_nan_inf(self):
- vals = [np.nan, -np.inf, np.inf]
- expected = [np.nan, -1, 1]
- assert_allclose(special.erf(vals), expected, rtol=1e-15)
- def test_erfc_nan_inf(self):
- vals = [np.nan, -np.inf, np.inf]
- expected = [np.nan, 2, 0]
- assert_allclose(special.erfc(vals), expected, rtol=1e-15)
- def test_erfcx_nan_inf(self):
- vals = [np.nan, -np.inf, np.inf]
- expected = [np.nan, np.inf, 0]
- assert_allclose(special.erfcx(vals), expected, rtol=1e-15)
- def test_erfi_nan_inf(self):
- vals = [np.nan, -np.inf, np.inf]
- expected = [np.nan, -np.inf, np.inf]
- assert_allclose(special.erfi(vals), expected, rtol=1e-15)
- def test_dawsn_nan_inf(self):
- vals = [np.nan, -np.inf, np.inf]
- expected = [np.nan, -0.0, 0.0]
- assert_allclose(special.dawsn(vals), expected, rtol=1e-15)
- def test_wofz_nan_inf(self):
- vals = [np.nan, -np.inf, np.inf]
- expected = [np.nan + np.nan * 1.j, 0.-0.j, 0.+0.j]
- assert_allclose(special.wofz(vals), expected, rtol=1e-15)
- class TestEuler:
- def test_euler(self):
- eu0 = special.euler(0)
- eu1 = special.euler(1)
- eu2 = special.euler(2) # just checking segfaults
- assert_allclose(eu0, [1], rtol=1e-15)
- assert_allclose(eu1, [1, 0], rtol=1e-15)
- assert_allclose(eu2, [1, 0, -1], rtol=1e-15)
- eu24 = special.euler(24)
- mathworld = [1,1,5,61,1385,50521,2702765,199360981,
- 19391512145,2404879675441,
- 370371188237525,69348874393137901,
- 15514534163557086905]
- correct = zeros((25,),'d')
- for k in range(0,13):
- if (k % 2):
- correct[2*k] = -float(mathworld[k])
- else:
- correct[2*k] = float(mathworld[k])
- with np.errstate(all='ignore'):
- err = nan_to_num((eu24-correct)/correct)
- errmax = max(err)
- assert_almost_equal(errmax, 0.0, 14)
- class TestExp:
- def test_exp2(self):
- ex = special.exp2(2)
- exrl = 2**2
- assert_equal(ex,exrl)
- def test_exp2more(self):
- exm = special.exp2(2.5)
- exmrl = 2**(2.5)
- assert_almost_equal(exm,exmrl,8)
- def test_exp10(self):
- ex = special.exp10(2)
- exrl = 10**2
- assert_approx_equal(ex,exrl)
- def test_exp10more(self):
- exm = special.exp10(2.5)
- exmrl = 10**(2.5)
- assert_almost_equal(exm,exmrl,8)
- def test_expm1(self):
- ex = (special.expm1(2),special.expm1(3),special.expm1(4))
- exrl = (exp(2)-1,exp(3)-1,exp(4)-1)
- assert_array_almost_equal(ex,exrl,8)
- def test_expm1more(self):
- ex1 = (special.expm1(2),special.expm1(2.1),special.expm1(2.2))
- exrl1 = (exp(2)-1,exp(2.1)-1,exp(2.2)-1)
- assert_array_almost_equal(ex1,exrl1,8)
- class TestFactorialFunctions:
- def test_factorial(self):
- # Some known values, float math
- assert_array_almost_equal(special.factorial(0), 1)
- assert_array_almost_equal(special.factorial(1), 1)
- assert_array_almost_equal(special.factorial(2), 2)
- assert_array_almost_equal([6., 24., 120.],
- special.factorial([3, 4, 5], exact=False))
- assert_array_almost_equal(special.factorial([[5, 3], [4, 3]]),
- [[120, 6], [24, 6]])
- # Some known values, integer math
- assert_equal(special.factorial(0, exact=True), 1)
- assert_equal(special.factorial(1, exact=True), 1)
- assert_equal(special.factorial(2, exact=True), 2)
- assert_equal(special.factorial(5, exact=True), 120)
- assert_equal(special.factorial(15, exact=True), 1307674368000)
- # ndarray shape is maintained
- assert_equal(special.factorial([7, 4, 15, 10], exact=True),
- [5040, 24, 1307674368000, 3628800])
- assert_equal(special.factorial([[5, 3], [4, 3]], True),
- [[120, 6], [24, 6]])
- # object arrays
- assert_equal(special.factorial(np.arange(-3, 22), True),
- special.factorial(np.arange(-3, 22), False))
- # int64 array
- assert_equal(special.factorial(np.arange(-3, 15), True),
- special.factorial(np.arange(-3, 15), False))
- # int32 array
- assert_equal(special.factorial(np.arange(-3, 5), True),
- special.factorial(np.arange(-3, 5), False))
- # Consistent output for n < 0
- for exact in (True, False):
- assert_array_equal(0, special.factorial(-3, exact))
- assert_array_equal([1, 2, 0, 0],
- special.factorial([1, 2, -5, -4], exact))
- for n in range(0, 22):
- # Compare all with math.factorial
- correct = math.factorial(n)
- assert_array_equal(correct, special.factorial(n, True))
- assert_array_equal(correct, special.factorial([n], True)[0])
- assert_allclose(float(correct), special.factorial(n, False))
- assert_allclose(float(correct), special.factorial([n], False)[0])
- # Compare exact=True vs False, scalar vs array
- assert_array_equal(special.factorial(n, True),
- special.factorial(n, False))
- assert_array_equal(special.factorial([n], True),
- special.factorial([n], False))
- @pytest.mark.parametrize('x, exact', [
- (1, True),
- (1, False),
- (np.array(1), True),
- (np.array(1), False),
- ])
- def test_factorial_0d_return_type(self, x, exact):
- assert np.isscalar(special.factorial(x, exact=exact))
- def test_factorial2(self):
- assert_array_almost_equal([105., 384., 945.],
- special.factorial2([7, 8, 9], exact=False))
- assert_equal(special.factorial2(7, exact=True), 105)
- def test_factorialk(self):
- assert_equal(special.factorialk(5, 1, exact=True), 120)
- assert_equal(special.factorialk(5, 3, exact=True), 10)
- @pytest.mark.parametrize('x, exact', [
- (np.nan, True),
- (np.nan, False),
- (np.array([np.nan]), True),
- (np.array([np.nan]), False),
- ])
- def test_nan_inputs(self, x, exact):
- result = special.factorial(x, exact=exact)
- assert_(np.isnan(result))
- # GH-13122: special.factorial() argument should be an array of integers.
- # On Python 3.10, math.factorial() reject float.
- # On Python 3.9, a DeprecationWarning is emitted.
- # A numpy array casts all integers to float if the array contains a
- # single NaN.
- @pytest.mark.skipif(sys.version_info >= (3, 10),
- reason="Python 3.10+ math.factorial() requires int")
- def test_mixed_nan_inputs(self):
- x = np.array([np.nan, 1, 2, 3, np.nan])
- with suppress_warnings() as sup:
- sup.filter(DeprecationWarning, "Using factorial\\(\\) with floats is deprecated")
- result = special.factorial(x, exact=True)
- assert_equal(np.array([np.nan, 1, 2, 6, np.nan]), result)
- result = special.factorial(x, exact=False)
- assert_equal(np.array([np.nan, 1, 2, 6, np.nan]), result)
- class TestFresnel:
- @pytest.mark.parametrize("z, s, c", [
- # some positive value
- (.5, 0.064732432859999287, 0.49234422587144644),
- (.5 + .0j, 0.064732432859999287, 0.49234422587144644),
- # negative half annulus
- # https://github.com/scipy/scipy/issues/12309
- # Reference values can be reproduced with
- # https://www.wolframalpha.com/input/?i=FresnelS%5B-2.0+%2B+0.1i%5D
- # https://www.wolframalpha.com/input/?i=FresnelC%5B-2.0+%2B+0.1i%5D
- (
- -2.0 + 0.1j,
- -0.3109538687728942-0.0005870728836383176j,
- -0.4879956866358554+0.10670801832903172j
- ),
- (
- -0.1 - 1.5j,
- -0.03918309471866977+0.7197508454568574j,
- 0.09605692502968956-0.43625191013617465j
- ),
- # a different algorithm kicks in for "large" values, i.e., |z| >= 4.5,
- # make sure to test both float and complex values; a different
- # algorithm is used
- (6.0, 0.44696076, 0.49953147),
- (6.0 + 0.0j, 0.44696076, 0.49953147),
- (6.0j, -0.44696076j, 0.49953147j),
- (-6.0 + 0.0j, -0.44696076, -0.49953147),
- (-6.0j, 0.44696076j, -0.49953147j),
- # inf
- (np.inf, 0.5, 0.5),
- (-np.inf, -0.5, -0.5),
- ])
- def test_fresnel_values(self, z, s, c):
- frs = array(special.fresnel(z))
- assert_array_almost_equal(frs, array([s, c]), 8)
- # values from pg 329 Table 7.11 of A & S
- # slightly corrected in 4th decimal place
- def test_fresnel_zeros(self):
- szo, czo = special.fresnel_zeros(5)
- assert_array_almost_equal(szo,
- array([2.0093+0.2885j,
- 2.8335+0.2443j,
- 3.4675+0.2185j,
- 4.0026+0.2009j,
- 4.4742+0.1877j]),3)
- assert_array_almost_equal(czo,
- array([1.7437+0.3057j,
- 2.6515+0.2529j,
- 3.3204+0.2240j,
- 3.8757+0.2047j,
- 4.3611+0.1907j]),3)
- vals1 = special.fresnel(szo)[0]
- vals2 = special.fresnel(czo)[1]
- assert_array_almost_equal(vals1,0,14)
- assert_array_almost_equal(vals2,0,14)
- def test_fresnelc_zeros(self):
- szo, czo = special.fresnel_zeros(6)
- frc = special.fresnelc_zeros(6)
- assert_array_almost_equal(frc,czo,12)
- def test_fresnels_zeros(self):
- szo, czo = special.fresnel_zeros(5)
- frs = special.fresnels_zeros(5)
- assert_array_almost_equal(frs,szo,12)
- class TestGamma:
- def test_gamma(self):
- gam = special.gamma(5)
- assert_equal(gam,24.0)
- def test_gammaln(self):
- gamln = special.gammaln(3)
- lngam = log(special.gamma(3))
- assert_almost_equal(gamln,lngam,8)
- def test_gammainccinv(self):
- gccinv = special.gammainccinv(.5,.5)
- gcinv = special.gammaincinv(.5,.5)
- assert_almost_equal(gccinv,gcinv,8)
- @with_special_errors
- def test_gammaincinv(self):
- y = special.gammaincinv(.4,.4)
- x = special.gammainc(.4,y)
- assert_almost_equal(x,0.4,1)
- y = special.gammainc(10, 0.05)
- x = special.gammaincinv(10, 2.5715803516000736e-20)
- assert_almost_equal(0.05, x, decimal=10)
- assert_almost_equal(y, 2.5715803516000736e-20, decimal=10)
- x = special.gammaincinv(50, 8.20754777388471303050299243573393e-18)
- assert_almost_equal(11.0, x, decimal=10)
- @with_special_errors
- def test_975(self):
- # Regression test for ticket #975 -- switch point in algorithm
- # check that things work OK at the point, immediately next floats
- # around it, and a bit further away
- pts = [0.25,
- np.nextafter(0.25, 0), 0.25 - 1e-12,
- np.nextafter(0.25, 1), 0.25 + 1e-12]
- for xp in pts:
- y = special.gammaincinv(.4, xp)
- x = special.gammainc(0.4, y)
- assert_allclose(x, xp, rtol=1e-12)
- def test_rgamma(self):
- rgam = special.rgamma(8)
- rlgam = 1/special.gamma(8)
- assert_almost_equal(rgam,rlgam,8)
- def test_infinity(self):
- assert_(np.isinf(special.gamma(-1)))
- assert_equal(special.rgamma(-1), 0)
- class TestHankel:
- def test_negv1(self):
- assert_almost_equal(special.hankel1(-3,2), -special.hankel1(3,2), 14)
- def test_hankel1(self):
- hank1 = special.hankel1(1,.1)
- hankrl = (special.jv(1,.1) + special.yv(1,.1)*1j)
- assert_almost_equal(hank1,hankrl,8)
- def test_negv1e(self):
- assert_almost_equal(special.hankel1e(-3,2), -special.hankel1e(3,2), 14)
- def test_hankel1e(self):
- hank1e = special.hankel1e(1,.1)
- hankrle = special.hankel1(1,.1)*exp(-.1j)
- assert_almost_equal(hank1e,hankrle,8)
- def test_negv2(self):
- assert_almost_equal(special.hankel2(-3,2), -special.hankel2(3,2), 14)
- def test_hankel2(self):
- hank2 = special.hankel2(1,.1)
- hankrl2 = (special.jv(1,.1) - special.yv(1,.1)*1j)
- assert_almost_equal(hank2,hankrl2,8)
- def test_neg2e(self):
- assert_almost_equal(special.hankel2e(-3,2), -special.hankel2e(3,2), 14)
- def test_hankl2e(self):
- hank2e = special.hankel2e(1,.1)
- hankrl2e = special.hankel2e(1,.1)
- assert_almost_equal(hank2e,hankrl2e,8)
- class TestHyper:
- def test_h1vp(self):
- h1 = special.h1vp(1,.1)
- h1real = (special.jvp(1,.1) + special.yvp(1,.1)*1j)
- assert_almost_equal(h1,h1real,8)
- def test_h2vp(self):
- h2 = special.h2vp(1,.1)
- h2real = (special.jvp(1,.1) - special.yvp(1,.1)*1j)
- assert_almost_equal(h2,h2real,8)
- def test_hyp0f1(self):
- # scalar input
- assert_allclose(special.hyp0f1(2.5, 0.5), 1.21482702689997, rtol=1e-12)
- assert_allclose(special.hyp0f1(2.5, 0), 1.0, rtol=1e-15)
- # float input, expected values match mpmath
- x = special.hyp0f1(3.0, [-1.5, -1, 0, 1, 1.5])
- expected = np.array([0.58493659229143, 0.70566805723127, 1.0,
- 1.37789689539747, 1.60373685288480])
- assert_allclose(x, expected, rtol=1e-12)
- # complex input
- x = special.hyp0f1(3.0, np.array([-1.5, -1, 0, 1, 1.5]) + 0.j)
- assert_allclose(x, expected.astype(complex), rtol=1e-12)
- # test broadcasting
- x1 = [0.5, 1.5, 2.5]
- x2 = [0, 1, 0.5]
- x = special.hyp0f1(x1, x2)
- expected = [1.0, 1.8134302039235093, 1.21482702689997]
- assert_allclose(x, expected, rtol=1e-12)
- x = special.hyp0f1(np.row_stack([x1] * 2), x2)
- assert_allclose(x, np.row_stack([expected] * 2), rtol=1e-12)
- assert_raises(ValueError, special.hyp0f1,
- np.row_stack([x1] * 3), [0, 1])
- def test_hyp0f1_gh5764(self):
- # Just checks the point that failed; there's a more systematic
- # test in test_mpmath
- res = special.hyp0f1(0.8, 0.5 + 0.5*1J)
- # The expected value was generated using mpmath
- assert_almost_equal(res, 1.6139719776441115 + 1J*0.80893054061790665)
- def test_hyp1f1(self):
- hyp1 = special.hyp1f1(.1,.1,.3)
- assert_almost_equal(hyp1, 1.3498588075760032,7)
- # test contributed by Moritz Deger (2008-05-29)
- # https://github.com/scipy/scipy/issues/1186 (Trac #659)
- # reference data obtained from mathematica [ a, b, x, m(a,b,x)]:
- # produced with test_hyp1f1.nb
- ref_data = array([[-8.38132975e+00, -1.28436461e+01, -2.91081397e+01, 1.04178330e+04],
- [2.91076882e+00, -6.35234333e+00, -1.27083993e+01, 6.68132725e+00],
- [-1.42938258e+01, 1.80869131e-01, 1.90038728e+01, 1.01385897e+05],
- [5.84069088e+00, 1.33187908e+01, 2.91290106e+01, 1.59469411e+08],
- [-2.70433202e+01, -1.16274873e+01, -2.89582384e+01, 1.39900152e+24],
- [4.26344966e+00, -2.32701773e+01, 1.91635759e+01, 6.13816915e+21],
- [1.20514340e+01, -3.40260240e+00, 7.26832235e+00, 1.17696112e+13],
- [2.77372955e+01, -1.99424687e+00, 3.61332246e+00, 3.07419615e+13],
- [1.50310939e+01, -2.91198675e+01, -1.53581080e+01, -3.79166033e+02],
- [1.43995827e+01, 9.84311196e+00, 1.93204553e+01, 2.55836264e+10],
- [-4.08759686e+00, 1.34437025e+01, -1.42072843e+01, 1.70778449e+01],
- [8.05595738e+00, -1.31019838e+01, 1.52180721e+01, 3.06233294e+21],
- [1.81815804e+01, -1.42908793e+01, 9.57868793e+00, -2.84771348e+20],
- [-2.49671396e+01, 1.25082843e+01, -1.71562286e+01, 2.36290426e+07],
- [2.67277673e+01, 1.70315414e+01, 6.12701450e+00, 7.77917232e+03],
- [2.49565476e+01, 2.91694684e+01, 6.29622660e+00, 2.35300027e+02],
- [6.11924542e+00, -1.59943768e+00, 9.57009289e+00, 1.32906326e+11],
- [-1.47863653e+01, 2.41691301e+01, -1.89981821e+01, 2.73064953e+03],
- [2.24070483e+01, -2.93647433e+00, 8.19281432e+00, -6.42000372e+17],
- [8.04042600e-01, 1.82710085e+01, -1.97814534e+01, 5.48372441e-01],
- [1.39590390e+01, 1.97318686e+01, 2.37606635e+00, 5.51923681e+00],
- [-4.66640483e+00, -2.00237930e+01, 7.40365095e+00, 4.50310752e+00],
- [2.76821999e+01, -6.36563968e+00, 1.11533984e+01, -9.28725179e+23],
- [-2.56764457e+01, 1.24544906e+00, 1.06407572e+01, 1.25922076e+01],
- [3.20447808e+00, 1.30874383e+01, 2.26098014e+01, 2.03202059e+04],
- [-1.24809647e+01, 4.15137113e+00, -2.92265700e+01, 2.39621411e+08],
- [2.14778108e+01, -2.35162960e+00, -1.13758664e+01, 4.46882152e-01],
- [-9.85469168e+00, -3.28157680e+00, 1.67447548e+01, -1.07342390e+07],
- [1.08122310e+01, -2.47353236e+01, -1.15622349e+01, -2.91733796e+03],
- [-2.67933347e+01, -3.39100709e+00, 2.56006986e+01, -5.29275382e+09],
- [-8.60066776e+00, -8.02200924e+00, 1.07231926e+01, 1.33548320e+06],
- [-1.01724238e-01, -1.18479709e+01, -2.55407104e+01, 1.55436570e+00],
- [-3.93356771e+00, 2.11106818e+01, -2.57598485e+01, 2.13467840e+01],
- [3.74750503e+00, 1.55687633e+01, -2.92841720e+01, 1.43873509e-02],
- [6.99726781e+00, 2.69855571e+01, -1.63707771e+01, 3.08098673e-02],
- [-2.31996011e+01, 3.47631054e+00, 9.75119815e-01, 1.79971073e-02],
- [2.38951044e+01, -2.91460190e+01, -2.50774708e+00, 9.56934814e+00],
- [1.52730825e+01, 5.77062507e+00, 1.21922003e+01, 1.32345307e+09],
- [1.74673917e+01, 1.89723426e+01, 4.94903250e+00, 9.90859484e+01],
- [1.88971241e+01, 2.86255413e+01, 5.52360109e-01, 1.44165360e+00],
- [1.02002319e+01, -1.66855152e+01, -2.55426235e+01, 6.56481554e+02],
- [-1.79474153e+01, 1.22210200e+01, -1.84058212e+01, 8.24041812e+05],
- [-1.36147103e+01, 1.32365492e+00, -7.22375200e+00, 9.92446491e+05],
- [7.57407832e+00, 2.59738234e+01, -1.34139168e+01, 3.64037761e-02],
- [2.21110169e+00, 1.28012666e+01, 1.62529102e+01, 1.33433085e+02],
- [-2.64297569e+01, -1.63176658e+01, -1.11642006e+01, -2.44797251e+13],
- [-2.46622944e+01, -3.02147372e+00, 8.29159315e+00, -3.21799070e+05],
- [-1.37215095e+01, -1.96680183e+01, 2.91940118e+01, 3.21457520e+12],
- [-5.45566105e+00, 2.81292086e+01, 1.72548215e-01, 9.66973000e-01],
- [-1.55751298e+00, -8.65703373e+00, 2.68622026e+01, -3.17190834e+16],
- [2.45393609e+01, -2.70571903e+01, 1.96815505e+01, 1.80708004e+37],
- [5.77482829e+00, 1.53203143e+01, 2.50534322e+01, 1.14304242e+06],
- [-1.02626819e+01, 2.36887658e+01, -2.32152102e+01, 7.28965646e+02],
- [-1.30833446e+00, -1.28310210e+01, 1.87275544e+01, -9.33487904e+12],
- [5.83024676e+00, -1.49279672e+01, 2.44957538e+01, -7.61083070e+27],
- [-2.03130747e+01, 2.59641715e+01, -2.06174328e+01, 4.54744859e+04],
- [1.97684551e+01, -2.21410519e+01, -2.26728740e+01, 3.53113026e+06],
- [2.73673444e+01, 2.64491725e+01, 1.57599882e+01, 1.07385118e+07],
- [5.73287971e+00, 1.21111904e+01, 1.33080171e+01, 2.63220467e+03],
- [-2.82751072e+01, 2.08605881e+01, 9.09838900e+00, -6.60957033e-07],
- [1.87270691e+01, -1.74437016e+01, 1.52413599e+01, 6.59572851e+27],
- [6.60681457e+00, -2.69449855e+00, 9.78972047e+00, -2.38587870e+12],
- [1.20895561e+01, -2.51355765e+01, 2.30096101e+01, 7.58739886e+32],
- [-2.44682278e+01, 2.10673441e+01, -1.36705538e+01, 4.54213550e+04],
- [-4.50665152e+00, 3.72292059e+00, -4.83403707e+00, 2.68938214e+01],
- [-7.46540049e+00, -1.08422222e+01, -1.72203805e+01, -2.09402162e+02],
- [-2.00307551e+01, -7.50604431e+00, -2.78640020e+01, 4.15985444e+19],
- [1.99890876e+01, 2.20677419e+01, -2.51301778e+01, 1.23840297e-09],
- [2.03183823e+01, -7.66942559e+00, 2.10340070e+01, 1.46285095e+31],
- [-2.90315825e+00, -2.55785967e+01, -9.58779316e+00, 2.65714264e-01],
- [2.73960829e+01, -1.80097203e+01, -2.03070131e+00, 2.52908999e+02],
- [-2.11708058e+01, -2.70304032e+01, 2.48257944e+01, 3.09027527e+08],
- [2.21959758e+01, 4.00258675e+00, -1.62853977e+01, -9.16280090e-09],
- [1.61661840e+01, -2.26845150e+01, 2.17226940e+01, -8.24774394e+33],
- [-3.35030306e+00, 1.32670581e+00, 9.39711214e+00, -1.47303163e+01],
- [7.23720726e+00, -2.29763909e+01, 2.34709682e+01, -9.20711735e+29],
- [2.71013568e+01, 1.61951087e+01, -7.11388906e-01, 2.98750911e-01],
- [8.40057933e+00, -7.49665220e+00, 2.95587388e+01, 6.59465635e+29],
- [-1.51603423e+01, 1.94032322e+01, -7.60044357e+00, 1.05186941e+02],
- [-8.83788031e+00, -2.72018313e+01, 1.88269907e+00, 1.81687019e+00],
- [-1.87283712e+01, 5.87479570e+00, -1.91210203e+01, 2.52235612e+08],
- [-5.61338513e-01, 2.69490237e+01, 1.16660111e-01, 9.97567783e-01],
- [-5.44354025e+00, -1.26721408e+01, -4.66831036e+00, 1.06660735e-01],
- [-2.18846497e+00, 2.33299566e+01, 9.62564397e+00, 3.03842061e-01],
- [6.65661299e+00, -2.39048713e+01, 1.04191807e+01, 4.73700451e+13],
- [-2.57298921e+01, -2.60811296e+01, 2.74398110e+01, -5.32566307e+11],
- [-1.11431826e+01, -1.59420160e+01, -1.84880553e+01, -1.01514747e+02],
- [6.50301931e+00, 2.59859051e+01, -2.33270137e+01, 1.22760500e-02],
- [-1.94987891e+01, -2.62123262e+01, 3.90323225e+00, 1.71658894e+01],
- [7.26164601e+00, -1.41469402e+01, 2.81499763e+01, -2.50068329e+31],
- [-1.52424040e+01, 2.99719005e+01, -2.85753678e+01, 1.31906693e+04],
- [5.24149291e+00, -1.72807223e+01, 2.22129493e+01, 2.50748475e+25],
- [3.63207230e-01, -9.54120862e-02, -2.83874044e+01, 9.43854939e-01],
- [-2.11326457e+00, -1.25707023e+01, 1.17172130e+00, 1.20812698e+00],
- [2.48513582e+00, 1.03652647e+01, -1.84625148e+01, 6.47910997e-02],
- [2.65395942e+01, 2.74794672e+01, 1.29413428e+01, 2.89306132e+05],
- [-9.49445460e+00, 1.59930921e+01, -1.49596331e+01, 3.27574841e+02],
- [-5.89173945e+00, 9.96742426e+00, 2.60318889e+01, -3.15842908e-01],
- [-1.15387239e+01, -2.21433107e+01, -2.17686413e+01, 1.56724718e-01],
- [-5.30592244e+00, -2.42752190e+01, 1.29734035e+00, 1.31985534e+00]])
- for a,b,c,expected in ref_data:
- result = special.hyp1f1(a,b,c)
- assert_(abs(expected - result)/expected < 1e-4)
- def test_hyp1f1_gh2957(self):
- hyp1 = special.hyp1f1(0.5, 1.5, -709.7827128933)
- hyp2 = special.hyp1f1(0.5, 1.5, -709.7827128934)
- assert_almost_equal(hyp1, hyp2, 12)
- def test_hyp1f1_gh2282(self):
- hyp = special.hyp1f1(0.5, 1.5, -1000)
- assert_almost_equal(hyp, 0.028024956081989643, 12)
- def test_hyp2f1(self):
- # a collection of special cases taken from AMS 55
- values = [[0.5, 1, 1.5, 0.2**2, 0.5/0.2*log((1+0.2)/(1-0.2))],
- [0.5, 1, 1.5, -0.2**2, 1./0.2*arctan(0.2)],
- [1, 1, 2, 0.2, -1/0.2*log(1-0.2)],
- [3, 3.5, 1.5, 0.2**2,
- 0.5/0.2/(-5)*((1+0.2)**(-5)-(1-0.2)**(-5))],
- [-3, 3, 0.5, sin(0.2)**2, cos(2*3*0.2)],
- [3, 4, 8, 1, special.gamma(8)*special.gamma(8-4-3)/special.gamma(8-3)/special.gamma(8-4)],
- [3, 2, 3-2+1, -1, 1./2**3*sqrt(pi) *
- special.gamma(1+3-2)/special.gamma(1+0.5*3-2)/special.gamma(0.5+0.5*3)],
- [5, 2, 5-2+1, -1, 1./2**5*sqrt(pi) *
- special.gamma(1+5-2)/special.gamma(1+0.5*5-2)/special.gamma(0.5+0.5*5)],
- [4, 0.5+4, 1.5-2*4, -1./3, (8./9)**(-2*4)*special.gamma(4./3) *
- special.gamma(1.5-2*4)/special.gamma(3./2)/special.gamma(4./3-2*4)],
- # and some others
- # ticket #424
- [1.5, -0.5, 1.0, -10.0, 4.1300097765277476484],
- # negative integer a or b, with c-a-b integer and x > 0.9
- [-2,3,1,0.95,0.715],
- [2,-3,1,0.95,-0.007],
- [-6,3,1,0.95,0.0000810625],
- [2,-5,1,0.95,-0.000029375],
- # huge negative integers
- (10, -900, 10.5, 0.99, 1.91853705796607664803709475658e-24),
- (10, -900, -10.5, 0.99, 3.54279200040355710199058559155e-18),
- ]
- for i, (a, b, c, x, v) in enumerate(values):
- cv = special.hyp2f1(a, b, c, x)
- assert_almost_equal(cv, v, 8, err_msg='test #%d' % i)
- def test_hyperu(self):
- val1 = special.hyperu(1,0.1,100)
- assert_almost_equal(val1,0.0098153,7)
- a,b = [0.3,0.6,1.2,-2.7],[1.5,3.2,-0.4,-3.2]
- a,b = asarray(a), asarray(b)
- z = 0.5
- hypu = special.hyperu(a,b,z)
- hprl = (pi/sin(pi*b))*(special.hyp1f1(a,b,z) /
- (special.gamma(1+a-b)*special.gamma(b)) -
- z**(1-b)*special.hyp1f1(1+a-b,2-b,z)
- / (special.gamma(a)*special.gamma(2-b)))
- assert_array_almost_equal(hypu,hprl,12)
- def test_hyperu_gh2287(self):
- assert_almost_equal(special.hyperu(1, 1.5, 20.2),
- 0.048360918656699191, 12)
- class TestBessel:
- def test_itj0y0(self):
- it0 = array(special.itj0y0(.2))
- assert_array_almost_equal(it0,array([0.19933433254006822, -0.34570883800412566]),8)
- def test_it2j0y0(self):
- it2 = array(special.it2j0y0(.2))
- assert_array_almost_equal(it2,array([0.0049937546274601858, -0.43423067011231614]),8)
- def test_negv_iv(self):
- assert_equal(special.iv(3,2), special.iv(-3,2))
- def test_j0(self):
- oz = special.j0(.1)
- ozr = special.jn(0,.1)
- assert_almost_equal(oz,ozr,8)
- def test_j1(self):
- o1 = special.j1(.1)
- o1r = special.jn(1,.1)
- assert_almost_equal(o1,o1r,8)
- def test_jn(self):
- jnnr = special.jn(1,.2)
- assert_almost_equal(jnnr,0.099500832639235995,8)
- def test_negv_jv(self):
- assert_almost_equal(special.jv(-3,2), -special.jv(3,2), 14)
- def test_jv(self):
- values = [[0, 0.1, 0.99750156206604002],
- [2./3, 1e-8, 0.3239028506761532e-5],
- [2./3, 1e-10, 0.1503423854873779e-6],
- [3.1, 1e-10, 0.1711956265409013e-32],
- [2./3, 4.0, -0.2325440850267039],
- ]
- for i, (v, x, y) in enumerate(values):
- yc = special.jv(v, x)
- assert_almost_equal(yc, y, 8, err_msg='test #%d' % i)
- def test_negv_jve(self):
- assert_almost_equal(special.jve(-3,2), -special.jve(3,2), 14)
- def test_jve(self):
- jvexp = special.jve(1,.2)
- assert_almost_equal(jvexp,0.099500832639235995,8)
- jvexp1 = special.jve(1,.2+1j)
- z = .2+1j
- jvexpr = special.jv(1,z)*exp(-abs(z.imag))
- assert_almost_equal(jvexp1,jvexpr,8)
- def test_jn_zeros(self):
- jn0 = special.jn_zeros(0,5)
- jn1 = special.jn_zeros(1,5)
- assert_array_almost_equal(jn0,array([2.4048255577,
- 5.5200781103,
- 8.6537279129,
- 11.7915344391,
- 14.9309177086]),4)
- assert_array_almost_equal(jn1,array([3.83171,
- 7.01559,
- 10.17347,
- 13.32369,
- 16.47063]),4)
- jn102 = special.jn_zeros(102,5)
- assert_allclose(jn102, array([110.89174935992040343,
- 117.83464175788308398,
- 123.70194191713507279,
- 129.02417238949092824,
- 134.00114761868422559]), rtol=1e-13)
- jn301 = special.jn_zeros(301,5)
- assert_allclose(jn301, array([313.59097866698830153,
- 323.21549776096288280,
- 331.22338738656748796,
- 338.39676338872084500,
- 345.03284233056064157]), rtol=1e-13)
- def test_jn_zeros_slow(self):
- jn0 = special.jn_zeros(0, 300)
- assert_allclose(jn0[260-1], 816.02884495068867280, rtol=1e-13)
- assert_allclose(jn0[280-1], 878.86068707124422606, rtol=1e-13)
- assert_allclose(jn0[300-1], 941.69253065317954064, rtol=1e-13)
- jn10 = special.jn_zeros(10, 300)
- assert_allclose(jn10[260-1], 831.67668514305631151, rtol=1e-13)
- assert_allclose(jn10[280-1], 894.51275095371316931, rtol=1e-13)
- assert_allclose(jn10[300-1], 957.34826370866539775, rtol=1e-13)
- jn3010 = special.jn_zeros(3010,5)
- assert_allclose(jn3010, array([3036.86590780927,
- 3057.06598526482,
- 3073.66360690272,
- 3088.37736494778,
- 3101.86438139042]), rtol=1e-8)
- def test_jnjnp_zeros(self):
- jn = special.jn
- def jnp(n, x):
- return (jn(n-1,x) - jn(n+1,x))/2
- for nt in range(1, 30):
- z, n, m, t = special.jnjnp_zeros(nt)
- for zz, nn, tt in zip(z, n, t):
- if tt == 0:
- assert_allclose(jn(nn, zz), 0, atol=1e-6)
- elif tt == 1:
- assert_allclose(jnp(nn, zz), 0, atol=1e-6)
- else:
- raise AssertionError("Invalid t return for nt=%d" % nt)
- def test_jnp_zeros(self):
- jnp = special.jnp_zeros(1,5)
- assert_array_almost_equal(jnp, array([1.84118,
- 5.33144,
- 8.53632,
- 11.70600,
- 14.86359]),4)
- jnp = special.jnp_zeros(443,5)
- assert_allclose(special.jvp(443, jnp), 0, atol=1e-15)
- def test_jnyn_zeros(self):
- jnz = special.jnyn_zeros(1,5)
- assert_array_almost_equal(jnz,(array([3.83171,
- 7.01559,
- 10.17347,
- 13.32369,
- 16.47063]),
- array([1.84118,
- 5.33144,
- 8.53632,
- 11.70600,
- 14.86359]),
- array([2.19714,
- 5.42968,
- 8.59601,
- 11.74915,
- 14.89744]),
- array([3.68302,
- 6.94150,
- 10.12340,
- 13.28576,
- 16.44006])),5)
- def test_jvp(self):
- jvprim = special.jvp(2,2)
- jv0 = (special.jv(1,2)-special.jv(3,2))/2
- assert_almost_equal(jvprim,jv0,10)
- def test_k0(self):
- ozk = special.k0(.1)
- ozkr = special.kv(0,.1)
- assert_almost_equal(ozk,ozkr,8)
- def test_k0e(self):
- ozke = special.k0e(.1)
- ozker = special.kve(0,.1)
- assert_almost_equal(ozke,ozker,8)
- def test_k1(self):
- o1k = special.k1(.1)
- o1kr = special.kv(1,.1)
- assert_almost_equal(o1k,o1kr,8)
- def test_k1e(self):
- o1ke = special.k1e(.1)
- o1ker = special.kve(1,.1)
- assert_almost_equal(o1ke,o1ker,8)
- def test_jacobi(self):
- a = 5*np.random.random() - 1
- b = 5*np.random.random() - 1
- P0 = special.jacobi(0,a,b)
- P1 = special.jacobi(1,a,b)
- P2 = special.jacobi(2,a,b)
- P3 = special.jacobi(3,a,b)
- assert_array_almost_equal(P0.c,[1],13)
- assert_array_almost_equal(P1.c,array([a+b+2,a-b])/2.0,13)
- cp = [(a+b+3)*(a+b+4), 4*(a+b+3)*(a+2), 4*(a+1)*(a+2)]
- p2c = [cp[0],cp[1]-2*cp[0],cp[2]-cp[1]+cp[0]]
- assert_array_almost_equal(P2.c,array(p2c)/8.0,13)
- cp = [(a+b+4)*(a+b+5)*(a+b+6),6*(a+b+4)*(a+b+5)*(a+3),
- 12*(a+b+4)*(a+2)*(a+3),8*(a+1)*(a+2)*(a+3)]
- p3c = [cp[0],cp[1]-3*cp[0],cp[2]-2*cp[1]+3*cp[0],cp[3]-cp[2]+cp[1]-cp[0]]
- assert_array_almost_equal(P3.c,array(p3c)/48.0,13)
- def test_kn(self):
- kn1 = special.kn(0,.2)
- assert_almost_equal(kn1,1.7527038555281462,8)
- def test_negv_kv(self):
- assert_equal(special.kv(3.0, 2.2), special.kv(-3.0, 2.2))
- def test_kv0(self):
- kv0 = special.kv(0,.2)
- assert_almost_equal(kv0, 1.7527038555281462, 10)
- def test_kv1(self):
- kv1 = special.kv(1,0.2)
- assert_almost_equal(kv1, 4.775972543220472, 10)
- def test_kv2(self):
- kv2 = special.kv(2,0.2)
- assert_almost_equal(kv2, 49.51242928773287, 10)
- def test_kn_largeorder(self):
- assert_allclose(special.kn(32, 1), 1.7516596664574289e+43)
- def test_kv_largearg(self):
- assert_equal(special.kv(0, 1e19), 0)
- def test_negv_kve(self):
- assert_equal(special.kve(3.0, 2.2), special.kve(-3.0, 2.2))
- def test_kve(self):
- kve1 = special.kve(0,.2)
- kv1 = special.kv(0,.2)*exp(.2)
- assert_almost_equal(kve1,kv1,8)
- z = .2+1j
- kve2 = special.kve(0,z)
- kv2 = special.kv(0,z)*exp(z)
- assert_almost_equal(kve2,kv2,8)
- def test_kvp_v0n1(self):
- z = 2.2
- assert_almost_equal(-special.kv(1,z), special.kvp(0,z, n=1), 10)
- def test_kvp_n1(self):
- v = 3.
- z = 2.2
- xc = -special.kv(v+1,z) + v/z*special.kv(v,z)
- x = special.kvp(v,z, n=1)
- assert_almost_equal(xc, x, 10) # this function (kvp) is broken
- def test_kvp_n2(self):
- v = 3.
- z = 2.2
- xc = (z**2+v**2-v)/z**2 * special.kv(v,z) + special.kv(v+1,z)/z
- x = special.kvp(v, z, n=2)
- assert_almost_equal(xc, x, 10)
- def test_y0(self):
- oz = special.y0(.1)
- ozr = special.yn(0,.1)
- assert_almost_equal(oz,ozr,8)
- def test_y1(self):
- o1 = special.y1(.1)
- o1r = special.yn(1,.1)
- assert_almost_equal(o1,o1r,8)
- def test_y0_zeros(self):
- yo,ypo = special.y0_zeros(2)
- zo,zpo = special.y0_zeros(2,complex=1)
- all = r_[yo,zo]
- allval = r_[ypo,zpo]
- assert_array_almost_equal(abs(special.yv(0.0,all)),0.0,11)
- assert_array_almost_equal(abs(special.yv(1,all)-allval),0.0,11)
- def test_y1_zeros(self):
- y1 = special.y1_zeros(1)
- assert_array_almost_equal(y1,(array([2.19714]),array([0.52079])),5)
- def test_y1p_zeros(self):
- y1p = special.y1p_zeros(1,complex=1)
- assert_array_almost_equal(y1p,(array([0.5768+0.904j]), array([-0.7635+0.5892j])),3)
- def test_yn_zeros(self):
- an = special.yn_zeros(4,2)
- assert_array_almost_equal(an,array([5.64515, 9.36162]),5)
- an = special.yn_zeros(443,5)
- assert_allclose(an, [450.13573091578090314, 463.05692376675001542,
- 472.80651546418663566, 481.27353184725625838,
- 488.98055964441374646], rtol=1e-15)
- def test_ynp_zeros(self):
- ao = special.ynp_zeros(0,2)
- assert_array_almost_equal(ao,array([2.19714133, 5.42968104]),6)
- ao = special.ynp_zeros(43,5)
- assert_allclose(special.yvp(43, ao), 0, atol=1e-15)
- ao = special.ynp_zeros(443,5)
- assert_allclose(special.yvp(443, ao), 0, atol=1e-9)
- def test_ynp_zeros_large_order(self):
- ao = special.ynp_zeros(443,5)
- assert_allclose(special.yvp(443, ao), 0, atol=1e-14)
- def test_yn(self):
- yn2n = special.yn(1,.2)
- assert_almost_equal(yn2n,-3.3238249881118471,8)
- def test_negv_yv(self):
- assert_almost_equal(special.yv(-3,2), -special.yv(3,2), 14)
- def test_yv(self):
- yv2 = special.yv(1,.2)
- assert_almost_equal(yv2,-3.3238249881118471,8)
- def test_negv_yve(self):
- assert_almost_equal(special.yve(-3,2), -special.yve(3,2), 14)
- def test_yve(self):
- yve2 = special.yve(1,.2)
- assert_almost_equal(yve2,-3.3238249881118471,8)
- yve2r = special.yv(1,.2+1j)*exp(-1)
- yve22 = special.yve(1,.2+1j)
- assert_almost_equal(yve22,yve2r,8)
- def test_yvp(self):
- yvpr = (special.yv(1,.2) - special.yv(3,.2))/2.0
- yvp1 = special.yvp(2,.2)
- assert_array_almost_equal(yvp1,yvpr,10)
- def _cephes_vs_amos_points(self):
- """Yield points at which to compare Cephes implementation to AMOS"""
- # check several points, including large-amplitude ones
- v = [-120, -100.3, -20., -10., -1., -.5, 0., 1., 12.49, 120., 301]
- z = [-1300, -11, -10, -1, 1., 10., 200.5, 401., 600.5, 700.6, 1300,
- 10003]
- yield from itertools.product(v, z)
- # check half-integers; these are problematic points at least
- # for cephes/iv
- yield from itertools.product(0.5 + arange(-60, 60), [3.5])
- def check_cephes_vs_amos(self, f1, f2, rtol=1e-11, atol=0, skip=None):
- for v, z in self._cephes_vs_amos_points():
- if skip is not None and skip(v, z):
- continue
- c1, c2, c3 = f1(v, z), f1(v,z+0j), f2(int(v), z)
- if np.isinf(c1):
- assert_(np.abs(c2) >= 1e300, (v, z))
- elif np.isnan(c1):
- assert_(c2.imag != 0, (v, z))
- else:
- assert_allclose(c1, c2, err_msg=(v, z), rtol=rtol, atol=atol)
- if v == int(v):
- assert_allclose(c3, c2, err_msg=(v, z),
- rtol=rtol, atol=atol)
- @pytest.mark.xfail(platform.machine() == 'ppc64le',
- reason="fails on ppc64le")
- def test_jv_cephes_vs_amos(self):
- self.check_cephes_vs_amos(special.jv, special.jn, rtol=1e-10, atol=1e-305)
- @pytest.mark.xfail(platform.machine() == 'ppc64le',
- reason="fails on ppc64le")
- def test_yv_cephes_vs_amos(self):
- self.check_cephes_vs_amos(special.yv, special.yn, rtol=1e-11, atol=1e-305)
- def test_yv_cephes_vs_amos_only_small_orders(self):
- skipper = lambda v, z: (abs(v) > 50)
- self.check_cephes_vs_amos(special.yv, special.yn, rtol=1e-11, atol=1e-305, skip=skipper)
- def test_iv_cephes_vs_amos(self):
- with np.errstate(all='ignore'):
- self.check_cephes_vs_amos(special.iv, special.iv, rtol=5e-9, atol=1e-305)
- @pytest.mark.slow
- def test_iv_cephes_vs_amos_mass_test(self):
- N = 1000000
- np.random.seed(1)
- v = np.random.pareto(0.5, N) * (-1)**np.random.randint(2, size=N)
- x = np.random.pareto(0.2, N) * (-1)**np.random.randint(2, size=N)
- imsk = (np.random.randint(8, size=N) == 0)
- v[imsk] = v[imsk].astype(int)
- with np.errstate(all='ignore'):
- c1 = special.iv(v, x)
- c2 = special.iv(v, x+0j)
- # deal with differences in the inf and zero cutoffs
- c1[abs(c1) > 1e300] = np.inf
- c2[abs(c2) > 1e300] = np.inf
- c1[abs(c1) < 1e-300] = 0
- c2[abs(c2) < 1e-300] = 0
- dc = abs(c1/c2 - 1)
- dc[np.isnan(dc)] = 0
- k = np.argmax(dc)
- # Most error apparently comes from AMOS and not our implementation;
- # there are some problems near integer orders there
- assert_(dc[k] < 2e-7, (v[k], x[k], special.iv(v[k], x[k]), special.iv(v[k], x[k]+0j)))
- def test_kv_cephes_vs_amos(self):
- self.check_cephes_vs_amos(special.kv, special.kn, rtol=1e-9, atol=1e-305)
- self.check_cephes_vs_amos(special.kv, special.kv, rtol=1e-9, atol=1e-305)
- def test_ticket_623(self):
- assert_allclose(special.jv(3, 4), 0.43017147387562193)
- assert_allclose(special.jv(301, 1300), 0.0183487151115275)
- assert_allclose(special.jv(301, 1296.0682), -0.0224174325312048)
- def test_ticket_853(self):
- """Negative-order Bessels"""
- # cephes
- assert_allclose(special.jv(-1, 1), -0.4400505857449335)
- assert_allclose(special.jv(-2, 1), 0.1149034849319005)
- assert_allclose(special.yv(-1, 1), 0.7812128213002887)
- assert_allclose(special.yv(-2, 1), -1.650682606816255)
- assert_allclose(special.iv(-1, 1), 0.5651591039924851)
- assert_allclose(special.iv(-2, 1), 0.1357476697670383)
- assert_allclose(special.kv(-1, 1), 0.6019072301972347)
- assert_allclose(special.kv(-2, 1), 1.624838898635178)
- assert_allclose(special.jv(-0.5, 1), 0.43109886801837607952)
- assert_allclose(special.yv(-0.5, 1), 0.6713967071418031)
- assert_allclose(special.iv(-0.5, 1), 1.231200214592967)
- assert_allclose(special.kv(-0.5, 1), 0.4610685044478945)
- # amos
- assert_allclose(special.jv(-1, 1+0j), -0.4400505857449335)
- assert_allclose(special.jv(-2, 1+0j), 0.1149034849319005)
- assert_allclose(special.yv(-1, 1+0j), 0.7812128213002887)
- assert_allclose(special.yv(-2, 1+0j), -1.650682606816255)
- assert_allclose(special.iv(-1, 1+0j), 0.5651591039924851)
- assert_allclose(special.iv(-2, 1+0j), 0.1357476697670383)
- assert_allclose(special.kv(-1, 1+0j), 0.6019072301972347)
- assert_allclose(special.kv(-2, 1+0j), 1.624838898635178)
- assert_allclose(special.jv(-0.5, 1+0j), 0.43109886801837607952)
- assert_allclose(special.jv(-0.5, 1+1j), 0.2628946385649065-0.827050182040562j)
- assert_allclose(special.yv(-0.5, 1+0j), 0.6713967071418031)
- assert_allclose(special.yv(-0.5, 1+1j), 0.967901282890131+0.0602046062142816j)
- assert_allclose(special.iv(-0.5, 1+0j), 1.231200214592967)
- assert_allclose(special.iv(-0.5, 1+1j), 0.77070737376928+0.39891821043561j)
- assert_allclose(special.kv(-0.5, 1+0j), 0.4610685044478945)
- assert_allclose(special.kv(-0.5, 1+1j), 0.06868578341999-0.38157825981268j)
- assert_allclose(special.jve(-0.5,1+0.3j), special.jv(-0.5, 1+0.3j)*exp(-0.3))
- assert_allclose(special.yve(-0.5,1+0.3j), special.yv(-0.5, 1+0.3j)*exp(-0.3))
- assert_allclose(special.ive(-0.5,0.3+1j), special.iv(-0.5, 0.3+1j)*exp(-0.3))
- assert_allclose(special.kve(-0.5,0.3+1j), special.kv(-0.5, 0.3+1j)*exp(0.3+1j))
- assert_allclose(special.hankel1(-0.5, 1+1j), special.jv(-0.5, 1+1j) + 1j*special.yv(-0.5,1+1j))
- assert_allclose(special.hankel2(-0.5, 1+1j), special.jv(-0.5, 1+1j) - 1j*special.yv(-0.5,1+1j))
- def test_ticket_854(self):
- """Real-valued Bessel domains"""
- assert_(isnan(special.jv(0.5, -1)))
- assert_(isnan(special.iv(0.5, -1)))
- assert_(isnan(special.yv(0.5, -1)))
- assert_(isnan(special.yv(1, -1)))
- assert_(isnan(special.kv(0.5, -1)))
- assert_(isnan(special.kv(1, -1)))
- assert_(isnan(special.jve(0.5, -1)))
- assert_(isnan(special.ive(0.5, -1)))
- assert_(isnan(special.yve(0.5, -1)))
- assert_(isnan(special.yve(1, -1)))
- assert_(isnan(special.kve(0.5, -1)))
- assert_(isnan(special.kve(1, -1)))
- assert_(isnan(special.airye(-1)[0:2]).all(), special.airye(-1))
- assert_(not isnan(special.airye(-1)[2:4]).any(), special.airye(-1))
- def test_gh_7909(self):
- assert_(special.kv(1.5, 0) == np.inf)
- assert_(special.kve(1.5, 0) == np.inf)
- def test_ticket_503(self):
- """Real-valued Bessel I overflow"""
- assert_allclose(special.iv(1, 700), 1.528500390233901e302)
- assert_allclose(special.iv(1000, 1120), 1.301564549405821e301)
- def test_iv_hyperg_poles(self):
- assert_allclose(special.iv(-0.5, 1), 1.231200214592967)
- def iv_series(self, v, z, n=200):
- k = arange(0, n).astype(float_)
- r = (v+2*k)*log(.5*z) - special.gammaln(k+1) - special.gammaln(v+k+1)
- r[isnan(r)] = inf
- r = exp(r)
- err = abs(r).max() * finfo(float_).eps * n + abs(r[-1])*10
- return r.sum(), err
- def test_i0_series(self):
- for z in [1., 10., 200.5]:
- value, err = self.iv_series(0, z)
- assert_allclose(special.i0(z), value, atol=err, err_msg=z)
- def test_i1_series(self):
- for z in [1., 10., 200.5]:
- value, err = self.iv_series(1, z)
- assert_allclose(special.i1(z), value, atol=err, err_msg=z)
- def test_iv_series(self):
- for v in [-20., -10., -1., 0., 1., 12.49, 120.]:
- for z in [1., 10., 200.5, -1+2j]:
- value, err = self.iv_series(v, z)
- assert_allclose(special.iv(v, z), value, atol=err, err_msg=(v, z))
- def test_i0(self):
- values = [[0.0, 1.0],
- [1e-10, 1.0],
- [0.1, 0.9071009258],
- [0.5, 0.6450352706],
- [1.0, 0.4657596077],
- [2.5, 0.2700464416],
- [5.0, 0.1835408126],
- [20.0, 0.0897803119],
- ]
- for i, (x, v) in enumerate(values):
- cv = special.i0(x) * exp(-x)
- assert_almost_equal(cv, v, 8, err_msg='test #%d' % i)
- def test_i0e(self):
- oize = special.i0e(.1)
- oizer = special.ive(0,.1)
- assert_almost_equal(oize,oizer,8)
- def test_i1(self):
- values = [[0.0, 0.0],
- [1e-10, 0.4999999999500000e-10],
- [0.1, 0.0452984468],
- [0.5, 0.1564208032],
- [1.0, 0.2079104154],
- [5.0, 0.1639722669],
- [20.0, 0.0875062222],
- ]
- for i, (x, v) in enumerate(values):
- cv = special.i1(x) * exp(-x)
- assert_almost_equal(cv, v, 8, err_msg='test #%d' % i)
- def test_i1e(self):
- oi1e = special.i1e(.1)
- oi1er = special.ive(1,.1)
- assert_almost_equal(oi1e,oi1er,8)
- def test_iti0k0(self):
- iti0 = array(special.iti0k0(5))
- assert_array_almost_equal(iti0,array([31.848667776169801, 1.5673873907283657]),5)
- def test_it2i0k0(self):
- it2k = special.it2i0k0(.1)
- assert_array_almost_equal(it2k,array([0.0012503906973464409, 3.3309450354686687]),6)
- def test_iv(self):
- iv1 = special.iv(0,.1)*exp(-.1)
- assert_almost_equal(iv1,0.90710092578230106,10)
- def test_negv_ive(self):
- assert_equal(special.ive(3,2), special.ive(-3,2))
- def test_ive(self):
- ive1 = special.ive(0,.1)
- iv1 = special.iv(0,.1)*exp(-.1)
- assert_almost_equal(ive1,iv1,10)
- def test_ivp0(self):
- assert_almost_equal(special.iv(1,2), special.ivp(0,2), 10)
- def test_ivp(self):
- y = (special.iv(0,2) + special.iv(2,2))/2
- x = special.ivp(1,2)
- assert_almost_equal(x,y,10)
- class TestLaguerre:
- def test_laguerre(self):
- lag0 = special.laguerre(0)
- lag1 = special.laguerre(1)
- lag2 = special.laguerre(2)
- lag3 = special.laguerre(3)
- lag4 = special.laguerre(4)
- lag5 = special.laguerre(5)
- assert_array_almost_equal(lag0.c,[1],13)
- assert_array_almost_equal(lag1.c,[-1,1],13)
- assert_array_almost_equal(lag2.c,array([1,-4,2])/2.0,13)
- assert_array_almost_equal(lag3.c,array([-1,9,-18,6])/6.0,13)
- assert_array_almost_equal(lag4.c,array([1,-16,72,-96,24])/24.0,13)
- assert_array_almost_equal(lag5.c,array([-1,25,-200,600,-600,120])/120.0,13)
- def test_genlaguerre(self):
- k = 5*np.random.random() - 0.9
- lag0 = special.genlaguerre(0,k)
- lag1 = special.genlaguerre(1,k)
- lag2 = special.genlaguerre(2,k)
- lag3 = special.genlaguerre(3,k)
- assert_equal(lag0.c,[1])
- assert_equal(lag1.c,[-1,k+1])
- assert_almost_equal(lag2.c,array([1,-2*(k+2),(k+1.)*(k+2.)])/2.0)
- assert_almost_equal(lag3.c,array([-1,3*(k+3),-3*(k+2)*(k+3),(k+1)*(k+2)*(k+3)])/6.0)
- # Base polynomials come from Abrahmowitz and Stegan
- class TestLegendre:
- def test_legendre(self):
- leg0 = special.legendre(0)
- leg1 = special.legendre(1)
- leg2 = special.legendre(2)
- leg3 = special.legendre(3)
- leg4 = special.legendre(4)
- leg5 = special.legendre(5)
- assert_equal(leg0.c, [1])
- assert_equal(leg1.c, [1,0])
- assert_almost_equal(leg2.c, array([3,0,-1])/2.0, decimal=13)
- assert_almost_equal(leg3.c, array([5,0,-3,0])/2.0)
- assert_almost_equal(leg4.c, array([35,0,-30,0,3])/8.0)
- assert_almost_equal(leg5.c, array([63,0,-70,0,15,0])/8.0)
- class TestLambda:
- def test_lmbda(self):
- lam = special.lmbda(1,.1)
- lamr = (array([special.jn(0,.1), 2*special.jn(1,.1)/.1]),
- array([special.jvp(0,.1), -2*special.jv(1,.1)/.01 + 2*special.jvp(1,.1)/.1]))
- assert_array_almost_equal(lam,lamr,8)
- class TestLog1p:
- def test_log1p(self):
- l1p = (special.log1p(10), special.log1p(11), special.log1p(12))
- l1prl = (log(11), log(12), log(13))
- assert_array_almost_equal(l1p,l1prl,8)
- def test_log1pmore(self):
- l1pm = (special.log1p(1), special.log1p(1.1), special.log1p(1.2))
- l1pmrl = (log(2),log(2.1),log(2.2))
- assert_array_almost_equal(l1pm,l1pmrl,8)
- class TestLegendreFunctions:
- def test_clpmn(self):
- z = 0.5+0.3j
- clp = special.clpmn(2, 2, z, 3)
- assert_array_almost_equal(clp,
- (array([[1.0000, z, 0.5*(3*z*z-1)],
- [0.0000, sqrt(z*z-1), 3*z*sqrt(z*z-1)],
- [0.0000, 0.0000, 3*(z*z-1)]]),
- array([[0.0000, 1.0000, 3*z],
- [0.0000, z/sqrt(z*z-1), 3*(2*z*z-1)/sqrt(z*z-1)],
- [0.0000, 0.0000, 6*z]])),
- 7)
- def test_clpmn_close_to_real_2(self):
- eps = 1e-10
- m = 1
- n = 3
- x = 0.5
- clp_plus = special.clpmn(m, n, x+1j*eps, 2)[0][m, n]
- clp_minus = special.clpmn(m, n, x-1j*eps, 2)[0][m, n]
- assert_array_almost_equal(array([clp_plus, clp_minus]),
- array([special.lpmv(m, n, x),
- special.lpmv(m, n, x)]),
- 7)
- def test_clpmn_close_to_real_3(self):
- eps = 1e-10
- m = 1
- n = 3
- x = 0.5
- clp_plus = special.clpmn(m, n, x+1j*eps, 3)[0][m, n]
- clp_minus = special.clpmn(m, n, x-1j*eps, 3)[0][m, n]
- assert_array_almost_equal(array([clp_plus, clp_minus]),
- array([special.lpmv(m, n, x)*np.exp(-0.5j*m*np.pi),
- special.lpmv(m, n, x)*np.exp(0.5j*m*np.pi)]),
- 7)
- def test_clpmn_across_unit_circle(self):
- eps = 1e-7
- m = 1
- n = 1
- x = 1j
- for type in [2, 3]:
- assert_almost_equal(special.clpmn(m, n, x+1j*eps, type)[0][m, n],
- special.clpmn(m, n, x-1j*eps, type)[0][m, n], 6)
- def test_inf(self):
- for z in (1, -1):
- for n in range(4):
- for m in range(1, n):
- lp = special.clpmn(m, n, z)
- assert_(np.isinf(lp[1][1,1:]).all())
- lp = special.lpmn(m, n, z)
- assert_(np.isinf(lp[1][1,1:]).all())
- def test_deriv_clpmn(self):
- # data inside and outside of the unit circle
- zvals = [0.5+0.5j, -0.5+0.5j, -0.5-0.5j, 0.5-0.5j,
- 1+1j, -1+1j, -1-1j, 1-1j]
- m = 2
- n = 3
- for type in [2, 3]:
- for z in zvals:
- for h in [1e-3, 1e-3j]:
- approx_derivative = (special.clpmn(m, n, z+0.5*h, type)[0]
- - special.clpmn(m, n, z-0.5*h, type)[0])/h
- assert_allclose(special.clpmn(m, n, z, type)[1],
- approx_derivative,
- rtol=1e-4)
- def test_lpmn(self):
- lp = special.lpmn(0,2,.5)
- assert_array_almost_equal(lp,(array([[1.00000,
- 0.50000,
- -0.12500]]),
- array([[0.00000,
- 1.00000,
- 1.50000]])),4)
- def test_lpn(self):
- lpnf = special.lpn(2,.5)
- assert_array_almost_equal(lpnf,(array([1.00000,
- 0.50000,
- -0.12500]),
- array([0.00000,
- 1.00000,
- 1.50000])),4)
- def test_lpmv(self):
- lp = special.lpmv(0,2,.5)
- assert_almost_equal(lp,-0.125,7)
- lp = special.lpmv(0,40,.001)
- assert_almost_equal(lp,0.1252678976534484,7)
- # XXX: this is outside the domain of the current implementation,
- # so ensure it returns a NaN rather than a wrong answer.
- with np.errstate(all='ignore'):
- lp = special.lpmv(-1,-1,.001)
- assert_(lp != 0 or np.isnan(lp))
- def test_lqmn(self):
- lqmnf = special.lqmn(0,2,.5)
- lqf = special.lqn(2,.5)
- assert_array_almost_equal(lqmnf[0][0],lqf[0],4)
- assert_array_almost_equal(lqmnf[1][0],lqf[1],4)
- def test_lqmn_gt1(self):
- """algorithm for real arguments changes at 1.0001
- test against analytical result for m=2, n=1
- """
- x0 = 1.0001
- delta = 0.00002
- for x in (x0-delta, x0+delta):
- lq = special.lqmn(2, 1, x)[0][-1, -1]
- expected = 2/(x*x-1)
- assert_almost_equal(lq, expected)
- def test_lqmn_shape(self):
- a, b = special.lqmn(4, 4, 1.1)
- assert_equal(a.shape, (5, 5))
- assert_equal(b.shape, (5, 5))
- a, b = special.lqmn(4, 0, 1.1)
- assert_equal(a.shape, (5, 1))
- assert_equal(b.shape, (5, 1))
- def test_lqn(self):
- lqf = special.lqn(2,.5)
- assert_array_almost_equal(lqf,(array([0.5493, -0.7253, -0.8187]),
- array([1.3333, 1.216, -0.8427])),4)
- class TestMathieu:
- def test_mathieu_a(self):
- pass
- def test_mathieu_even_coef(self):
- special.mathieu_even_coef(2,5)
- # Q not defined broken and cannot figure out proper reporting order
- def test_mathieu_odd_coef(self):
- # same problem as above
- pass
- class TestFresnelIntegral:
- def test_modfresnelp(self):
- pass
- def test_modfresnelm(self):
- pass
- class TestOblCvSeq:
- def test_obl_cv_seq(self):
- obl = special.obl_cv_seq(0,3,1)
- assert_array_almost_equal(obl,array([-0.348602,
- 1.393206,
- 5.486800,
- 11.492120]),5)
- class TestParabolicCylinder:
- def test_pbdn_seq(self):
- pb = special.pbdn_seq(1,.1)
- assert_array_almost_equal(pb,(array([0.9975,
- 0.0998]),
- array([-0.0499,
- 0.9925])),4)
- def test_pbdv(self):
- special.pbdv(1,.2)
- 1/2*(.2)*special.pbdv(1,.2)[0] - special.pbdv(0,.2)[0]
- def test_pbdv_seq(self):
- pbn = special.pbdn_seq(1,.1)
- pbv = special.pbdv_seq(1,.1)
- assert_array_almost_equal(pbv,(real(pbn[0]),real(pbn[1])),4)
- def test_pbdv_points(self):
- # simple case
- eta = np.linspace(-10, 10, 5)
- z = 2**(eta/2)*np.sqrt(np.pi)/special.gamma(.5-.5*eta)
- assert_allclose(special.pbdv(eta, 0.)[0], z, rtol=1e-14, atol=1e-14)
- # some points
- assert_allclose(special.pbdv(10.34, 20.44)[0], 1.3731383034455e-32, rtol=1e-12)
- assert_allclose(special.pbdv(-9.53, 3.44)[0], 3.166735001119246e-8, rtol=1e-12)
- def test_pbdv_gradient(self):
- x = np.linspace(-4, 4, 8)[:,None]
- eta = np.linspace(-10, 10, 5)[None,:]
- p = special.pbdv(eta, x)
- eps = 1e-7 + 1e-7*abs(x)
- dp = (special.pbdv(eta, x + eps)[0] - special.pbdv(eta, x - eps)[0]) / eps / 2.
- assert_allclose(p[1], dp, rtol=1e-6, atol=1e-6)
- def test_pbvv_gradient(self):
- x = np.linspace(-4, 4, 8)[:,None]
- eta = np.linspace(-10, 10, 5)[None,:]
- p = special.pbvv(eta, x)
- eps = 1e-7 + 1e-7*abs(x)
- dp = (special.pbvv(eta, x + eps)[0] - special.pbvv(eta, x - eps)[0]) / eps / 2.
- assert_allclose(p[1], dp, rtol=1e-6, atol=1e-6)
- class TestPolygamma:
- # from Table 6.2 (pg. 271) of A&S
- def test_polygamma(self):
- poly2 = special.polygamma(2,1)
- poly3 = special.polygamma(3,1)
- assert_almost_equal(poly2,-2.4041138063,10)
- assert_almost_equal(poly3,6.4939394023,10)
- # Test polygamma(0, x) == psi(x)
- x = [2, 3, 1.1e14]
- assert_almost_equal(special.polygamma(0, x), special.psi(x))
- # Test broadcasting
- n = [0, 1, 2]
- x = [0.5, 1.5, 2.5]
- expected = [-1.9635100260214238, 0.93480220054467933,
- -0.23620405164172739]
- assert_almost_equal(special.polygamma(n, x), expected)
- expected = np.row_stack([expected]*2)
- assert_almost_equal(special.polygamma(n, np.row_stack([x]*2)),
- expected)
- assert_almost_equal(special.polygamma(np.row_stack([n]*2), x),
- expected)
- class TestProCvSeq:
- def test_pro_cv_seq(self):
- prol = special.pro_cv_seq(0,3,1)
- assert_array_almost_equal(prol,array([0.319000,
- 2.593084,
- 6.533471,
- 12.514462]),5)
- class TestPsi:
- def test_psi(self):
- ps = special.psi(1)
- assert_almost_equal(ps,-0.57721566490153287,8)
- class TestRadian:
- def test_radian(self):
- rad = special.radian(90,0,0)
- assert_almost_equal(rad,pi/2.0,5)
- def test_radianmore(self):
- rad1 = special.radian(90,1,60)
- assert_almost_equal(rad1,pi/2+0.0005816135199345904,5)
- class TestRiccati:
- def test_riccati_jn(self):
- N, x = 2, 0.2
- S = np.empty((N, N))
- for n in range(N):
- j = special.spherical_jn(n, x)
- jp = special.spherical_jn(n, x, derivative=True)
- S[0,n] = x*j
- S[1,n] = x*jp + j
- assert_array_almost_equal(S, special.riccati_jn(n, x), 8)
- def test_riccati_yn(self):
- N, x = 2, 0.2
- C = np.empty((N, N))
- for n in range(N):
- y = special.spherical_yn(n, x)
- yp = special.spherical_yn(n, x, derivative=True)
- C[0,n] = x*y
- C[1,n] = x*yp + y
- assert_array_almost_equal(C, special.riccati_yn(n, x), 8)
- class TestRound:
- def test_round(self):
- rnd = list(map(int,(special.round(10.1),special.round(10.4),special.round(10.5),special.round(10.6))))
- # Note: According to the documentation, scipy.special.round is
- # supposed to round to the nearest even number if the fractional
- # part is exactly 0.5. On some platforms, this does not appear
- # to work and thus this test may fail. However, this unit test is
- # correctly written.
- rndrl = (10,10,10,11)
- assert_array_equal(rnd,rndrl)
- def test_sph_harm():
- # Tests derived from tables in
- # https://en.wikipedia.org/wiki/Table_of_spherical_harmonics
- sh = special.sph_harm
- pi = np.pi
- exp = np.exp
- sqrt = np.sqrt
- sin = np.sin
- cos = np.cos
- assert_array_almost_equal(sh(0,0,0,0),
- 0.5/sqrt(pi))
- assert_array_almost_equal(sh(-2,2,0.,pi/4),
- 0.25*sqrt(15./(2.*pi)) *
- (sin(pi/4))**2.)
- assert_array_almost_equal(sh(-2,2,0.,pi/2),
- 0.25*sqrt(15./(2.*pi)))
- assert_array_almost_equal(sh(2,2,pi,pi/2),
- 0.25*sqrt(15/(2.*pi)) *
- exp(0+2.*pi*1j)*sin(pi/2.)**2.)
- assert_array_almost_equal(sh(2,4,pi/4.,pi/3.),
- (3./8.)*sqrt(5./(2.*pi)) *
- exp(0+2.*pi/4.*1j) *
- sin(pi/3.)**2. *
- (7.*cos(pi/3.)**2.-1))
- assert_array_almost_equal(sh(4,4,pi/8.,pi/6.),
- (3./16.)*sqrt(35./(2.*pi)) *
- exp(0+4.*pi/8.*1j)*sin(pi/6.)**4.)
- def test_sph_harm_ufunc_loop_selection():
- # see https://github.com/scipy/scipy/issues/4895
- dt = np.dtype(np.complex128)
- assert_equal(special.sph_harm(0, 0, 0, 0).dtype, dt)
- assert_equal(special.sph_harm([0], 0, 0, 0).dtype, dt)
- assert_equal(special.sph_harm(0, [0], 0, 0).dtype, dt)
- assert_equal(special.sph_harm(0, 0, [0], 0).dtype, dt)
- assert_equal(special.sph_harm(0, 0, 0, [0]).dtype, dt)
- assert_equal(special.sph_harm([0], [0], [0], [0]).dtype, dt)
- class TestStruve:
- def _series(self, v, z, n=100):
- """Compute Struve function & error estimate from its power series."""
- k = arange(0, n)
- r = (-1)**k * (.5*z)**(2*k+v+1)/special.gamma(k+1.5)/special.gamma(k+v+1.5)
- err = abs(r).max() * finfo(float_).eps * n
- return r.sum(), err
- def test_vs_series(self):
- """Check Struve function versus its power series"""
- for v in [-20, -10, -7.99, -3.4, -1, 0, 1, 3.4, 12.49, 16]:
- for z in [1, 10, 19, 21, 30]:
- value, err = self._series(v, z)
- assert_allclose(special.struve(v, z), value, rtol=0, atol=err), (v, z)
- def test_some_values(self):
- assert_allclose(special.struve(-7.99, 21), 0.0467547614113, rtol=1e-7)
- assert_allclose(special.struve(-8.01, 21), 0.0398716951023, rtol=1e-8)
- assert_allclose(special.struve(-3.0, 200), 0.0142134427432, rtol=1e-12)
- assert_allclose(special.struve(-8.0, -41), 0.0192469727846, rtol=1e-11)
- assert_equal(special.struve(-12, -41), -special.struve(-12, 41))
- assert_equal(special.struve(+12, -41), -special.struve(+12, 41))
- assert_equal(special.struve(-11, -41), +special.struve(-11, 41))
- assert_equal(special.struve(+11, -41), +special.struve(+11, 41))
- assert_(isnan(special.struve(-7.1, -1)))
- assert_(isnan(special.struve(-10.1, -1)))
- def test_regression_679(self):
- """Regression test for #679"""
- assert_allclose(special.struve(-1.0, 20 - 1e-8), special.struve(-1.0, 20 + 1e-8))
- assert_allclose(special.struve(-2.0, 20 - 1e-8), special.struve(-2.0, 20 + 1e-8))
- assert_allclose(special.struve(-4.3, 20 - 1e-8), special.struve(-4.3, 20 + 1e-8))
- def test_chi2_smalldf():
- assert_almost_equal(special.chdtr(0.6,3), 0.957890536704110)
- def test_ch2_inf():
- assert_equal(special.chdtr(0.7,np.inf), 1.0)
- def test_chi2c_smalldf():
- assert_almost_equal(special.chdtrc(0.6,3), 1-0.957890536704110)
- def test_chi2_inv_smalldf():
- assert_almost_equal(special.chdtri(0.6,1-0.957890536704110), 3)
- def test_agm_simple():
- rtol = 1e-13
- # Gauss's constant
- assert_allclose(1/special.agm(1, np.sqrt(2)), 0.834626841674073186,
- rtol=rtol)
- # These values were computed using Wolfram Alpha, with the
- # function ArithmeticGeometricMean[a, b].
- agm13 = 1.863616783244897
- agm15 = 2.604008190530940
- agm35 = 3.936235503649555
- assert_allclose(special.agm([[1], [3]], [1, 3, 5]),
- [[1, agm13, agm15],
- [agm13, 3, agm35]], rtol=rtol)
- # Computed by the iteration formula using mpmath,
- # with mpmath.mp.prec = 1000:
- agm12 = 1.4567910310469068
- assert_allclose(special.agm(1, 2), agm12, rtol=rtol)
- assert_allclose(special.agm(2, 1), agm12, rtol=rtol)
- assert_allclose(special.agm(-1, -2), -agm12, rtol=rtol)
- assert_allclose(special.agm(24, 6), 13.458171481725614, rtol=rtol)
- assert_allclose(special.agm(13, 123456789.5), 11111458.498599306,
- rtol=rtol)
- assert_allclose(special.agm(1e30, 1), 2.229223055945383e+28, rtol=rtol)
- assert_allclose(special.agm(1e-22, 1), 0.030182566420169886, rtol=rtol)
- assert_allclose(special.agm(1e150, 1e180), 2.229223055945383e+178,
- rtol=rtol)
- assert_allclose(special.agm(1e180, 1e-150), 2.0634722510162677e+177,
- rtol=rtol)
- assert_allclose(special.agm(1e-150, 1e-170), 3.3112619670463756e-152,
- rtol=rtol)
- fi = np.finfo(1.0)
- assert_allclose(special.agm(fi.tiny, fi.max), 1.9892072050015473e+305,
- rtol=rtol)
- assert_allclose(special.agm(0.75*fi.max, fi.max), 1.564904312298045e+308,
- rtol=rtol)
- assert_allclose(special.agm(fi.tiny, 3*fi.tiny), 4.1466849866735005e-308,
- rtol=rtol)
- # zero, nan and inf cases.
- assert_equal(special.agm(0, 0), 0)
- assert_equal(special.agm(99, 0), 0)
- assert_equal(special.agm(-1, 10), np.nan)
- assert_equal(special.agm(0, np.inf), np.nan)
- assert_equal(special.agm(np.inf, 0), np.nan)
- assert_equal(special.agm(0, -np.inf), np.nan)
- assert_equal(special.agm(-np.inf, 0), np.nan)
- assert_equal(special.agm(np.inf, -np.inf), np.nan)
- assert_equal(special.agm(-np.inf, np.inf), np.nan)
- assert_equal(special.agm(1, np.nan), np.nan)
- assert_equal(special.agm(np.nan, -1), np.nan)
- assert_equal(special.agm(1, np.inf), np.inf)
- assert_equal(special.agm(np.inf, 1), np.inf)
- assert_equal(special.agm(-1, -np.inf), -np.inf)
- assert_equal(special.agm(-np.inf, -1), -np.inf)
- def test_legacy():
- # Legacy behavior: truncating arguments to integers
- with suppress_warnings() as sup:
- sup.filter(RuntimeWarning, "floating point number truncated to an integer")
- assert_equal(special.expn(1, 0.3), special.expn(1.8, 0.3))
- assert_equal(special.nbdtrc(1, 2, 0.3), special.nbdtrc(1.8, 2.8, 0.3))
- assert_equal(special.nbdtr(1, 2, 0.3), special.nbdtr(1.8, 2.8, 0.3))
- assert_equal(special.nbdtri(1, 2, 0.3), special.nbdtri(1.8, 2.8, 0.3))
- assert_equal(special.pdtri(1, 0.3), special.pdtri(1.8, 0.3))
- assert_equal(special.kn(1, 0.3), special.kn(1.8, 0.3))
- assert_equal(special.yn(1, 0.3), special.yn(1.8, 0.3))
- assert_equal(special.smirnov(1, 0.3), special.smirnov(1.8, 0.3))
- assert_equal(special.smirnovi(1, 0.3), special.smirnovi(1.8, 0.3))
- @with_special_errors
- def test_error_raising():
- assert_raises(special.SpecialFunctionError, special.iv, 1, 1e99j)
- def test_xlogy():
- def xfunc(x, y):
- with np.errstate(invalid='ignore'):
- if x == 0 and not np.isnan(y):
- return x
- else:
- return x*np.log(y)
- z1 = np.asarray([(0,0), (0, np.nan), (0, np.inf), (1.0, 2.0)], dtype=float)
- z2 = np.r_[z1, [(0, 1j), (1, 1j)]]
- w1 = np.vectorize(xfunc)(z1[:,0], z1[:,1])
- assert_func_equal(special.xlogy, w1, z1, rtol=1e-13, atol=1e-13)
- w2 = np.vectorize(xfunc)(z2[:,0], z2[:,1])
- assert_func_equal(special.xlogy, w2, z2, rtol=1e-13, atol=1e-13)
- def test_xlog1py():
- def xfunc(x, y):
- with np.errstate(invalid='ignore'):
- if x == 0 and not np.isnan(y):
- return x
- else:
- return x * np.log1p(y)
- z1 = np.asarray([(0,0), (0, np.nan), (0, np.inf), (1.0, 2.0),
- (1, 1e-30)], dtype=float)
- w1 = np.vectorize(xfunc)(z1[:,0], z1[:,1])
- assert_func_equal(special.xlog1py, w1, z1, rtol=1e-13, atol=1e-13)
- def test_entr():
- def xfunc(x):
- if x < 0:
- return -np.inf
- else:
- return -special.xlogy(x, x)
- values = (0, 0.5, 1.0, np.inf)
- signs = [-1, 1]
- arr = []
- for sgn, v in itertools.product(signs, values):
- arr.append(sgn * v)
- z = np.array(arr, dtype=float)
- w = np.vectorize(xfunc, otypes=[np.float64])(z)
- assert_func_equal(special.entr, w, z, rtol=1e-13, atol=1e-13)
- def test_kl_div():
- def xfunc(x, y):
- if x < 0 or y < 0 or (y == 0 and x != 0):
- # extension of natural domain to preserve convexity
- return np.inf
- elif np.isposinf(x) or np.isposinf(y):
- # limits within the natural domain
- return np.inf
- elif x == 0:
- return y
- else:
- return special.xlogy(x, x/y) - x + y
- values = (0, 0.5, 1.0)
- signs = [-1, 1]
- arr = []
- for sgna, va, sgnb, vb in itertools.product(signs, values, signs, values):
- arr.append((sgna*va, sgnb*vb))
- z = np.array(arr, dtype=float)
- w = np.vectorize(xfunc, otypes=[np.float64])(z[:,0], z[:,1])
- assert_func_equal(special.kl_div, w, z, rtol=1e-13, atol=1e-13)
- def test_rel_entr():
- def xfunc(x, y):
- if x > 0 and y > 0:
- return special.xlogy(x, x/y)
- elif x == 0 and y >= 0:
- return 0
- else:
- return np.inf
- values = (0, 0.5, 1.0)
- signs = [-1, 1]
- arr = []
- for sgna, va, sgnb, vb in itertools.product(signs, values, signs, values):
- arr.append((sgna*va, sgnb*vb))
- z = np.array(arr, dtype=float)
- w = np.vectorize(xfunc, otypes=[np.float64])(z[:,0], z[:,1])
- assert_func_equal(special.rel_entr, w, z, rtol=1e-13, atol=1e-13)
- def test_huber():
- assert_equal(special.huber(-1, 1.5), np.inf)
- assert_allclose(special.huber(2, 1.5), 0.5 * np.square(1.5))
- assert_allclose(special.huber(2, 2.5), 2 * (2.5 - 0.5 * 2))
- def xfunc(delta, r):
- if delta < 0:
- return np.inf
- elif np.abs(r) < delta:
- return 0.5 * np.square(r)
- else:
- return delta * (np.abs(r) - 0.5 * delta)
- z = np.random.randn(10, 2)
- w = np.vectorize(xfunc, otypes=[np.float64])(z[:,0], z[:,1])
- assert_func_equal(special.huber, w, z, rtol=1e-13, atol=1e-13)
- def test_pseudo_huber():
- def xfunc(delta, r):
- if delta < 0:
- return np.inf
- elif (not delta) or (not r):
- return 0
- else:
- return delta**2 * (np.sqrt(1 + (r/delta)**2) - 1)
- z = np.array(np.random.randn(10, 2).tolist() + [[0, 0.5], [0.5, 0]])
- w = np.vectorize(xfunc, otypes=[np.float64])(z[:,0], z[:,1])
- assert_func_equal(special.pseudo_huber, w, z, rtol=1e-13, atol=1e-13)
- def test_pseudo_huber_small_r():
- delta = 1.0
- r = 1e-18
- y = special.pseudo_huber(delta, r)
- # expected computed with mpmath:
- # import mpmath
- # mpmath.mp.dps = 200
- # r = mpmath.mpf(1e-18)
- # expected = float(mpmath.sqrt(1 + r**2) - 1)
- expected = 5.0000000000000005e-37
- assert_allclose(y, expected, rtol=1e-13)
- def test_runtime_warning():
- with pytest.warns(RuntimeWarning,
- match=r'Too many predicted coefficients'):
- mathieu_odd_coef(1000, 1000)
- with pytest.warns(RuntimeWarning,
- match=r'Too many predicted coefficients'):
- mathieu_even_coef(1000, 1000)
|