PNG  IHDRX cHRMz&u0`:pQ<bKGD pHYsodtIME MeqIDATxw]Wug^Qd˶ 6`!N:!@xI~)%7%@Bh&`lnjVF29gΨ4E$|>cɚ{gk= %,a KX%,a KX%,a KX%,a KX%,a KX%,a KX%, b` ǟzeאfp]<!SJmɤY޲ڿ,%c ~ع9VH.!Ͳz&QynֺTkRR.BLHi٪:l;@(!MԴ=žI,:o&N'Kù\vRmJ雵֫AWic H@" !: Cé||]k-Ha oݜ:y F())u]aG7*JV@J415p=sZH!=!DRʯvɱh~V\}v/GKY$n]"X"}t@ xS76^[bw4dsce)2dU0 CkMa-U5tvLƀ~mlMwfGE/-]7XAƟ`׮g ewxwC4\[~7@O-Q( a*XGƒ{ ՟}$_y3tĐƤatgvێi|K=uVyrŲlLӪuܿzwk$m87k( `múcE)"@rK( z4$D; 2kW=Xb$V[Ru819קR~qloѱDyįݎ*mxw]y5e4K@ЃI0A D@"BDk_)N\8͜9dz"fK0zɿvM /.:2O{ Nb=M=7>??Zuo32 DLD@D| &+֎C #B8ַ`bOb $D#ͮҪtx]%`ES`Ru[=¾!@Od37LJ0!OIR4m]GZRJu$‡c=%~s@6SKy?CeIh:[vR@Lh | (BhAMy=݃  G"'wzn޺~8ԽSh ~T*A:xR[ܹ?X[uKL_=fDȊ؂p0}7=D$Ekq!/t.*2ʼnDbŞ}DijYaȲ(""6HA;:LzxQ‘(SQQ}*PL*fc\s `/d'QXW, e`#kPGZuŞuO{{wm[&NBTiiI0bukcA9<4@SӊH*؎4U/'2U5.(9JuDfrޱtycU%j(:RUbArLֺN)udA':uGQN"-"Is.*+k@ `Ojs@yU/ H:l;@yyTn}_yw!VkRJ4P)~y#)r,D =ě"Q]ci'%HI4ZL0"MJy 8A{ aN<8D"1#IJi >XjX֔#@>-{vN!8tRݻ^)N_╗FJEk]CT՟ YP:_|H1@ CBk]yKYp|og?*dGvzنzӴzjֺNkC~AbZƷ`.H)=!QͷVTT(| u78y֮}|[8-Vjp%2JPk[}ԉaH8Wpqhwr:vWª<}l77_~{s۴V+RCģ%WRZ\AqHifɤL36: #F:p]Bq/z{0CU6ݳEv_^k7'>sq*+kH%a`0ԣisqにtү04gVgW΂iJiS'3w.w}l6MC2uԯ|>JF5`fV5m`Y**Db1FKNttu]4ccsQNnex/87+}xaUW9y>ͯ骵G{䩓Գ3+vU}~jJ.NFRD7<aJDB1#ҳgSb,+CS?/ VG J?|?,2#M9}B)MiE+G`-wo߫V`fio(}S^4e~V4bHOYb"b#E)dda:'?}׮4繏`{7Z"uny-?ǹ;0MKx{:_pÚmFמ:F " .LFQLG)Q8qN q¯¯3wOvxDb\. BKD9_NN &L:4D{mm o^tֽ:q!ƥ}K+<"m78N< ywsard5+вz~mnG)=}lYݧNj'QJS{S :UYS-952?&O-:W}(!6Mk4+>A>j+i|<<|;ر^߉=HE|V#F)Emm#}/"y GII웻Jі94+v뾧xu~5C95~ūH>c@덉pʃ1/4-A2G%7>m;–Y,cyyaln" ?ƻ!ʪ<{~h~i y.zZB̃/,雋SiC/JFMmBH&&FAbϓO^tubbb_hZ{_QZ-sύodFgO(6]TJA˯#`۶ɟ( %$&+V'~hiYy>922 Wp74Zkq+Ovn錄c>8~GqܲcWꂎz@"1A.}T)uiW4="jJ2W7mU/N0gcqܗOO}?9/wìXžΏ0 >֩(V^Rh32!Hj5`;O28؇2#ݕf3 ?sJd8NJ@7O0 b־?lldщ̡&|9C.8RTWwxWy46ah嘦mh٤&l zCy!PY?: CJyв]dm4ǜҐR޻RլhX{FƯanшQI@x' ao(kUUuxW_Ñ줮[w8 FRJ(8˼)_mQ _!RJhm=!cVmm ?sFOnll6Qk}alY}; "baӌ~M0w,Ggw2W:G/k2%R,_=u`WU R.9T"v,<\Ik޽/2110Ӿxc0gyC&Ny޽JҢrV6N ``یeA16"J³+Rj*;BϜkZPJaÍ<Jyw:NP8/D$ 011z֊Ⱳ3ι֘k1V_"h!JPIΣ'ɜ* aEAd:ݺ>y<}Lp&PlRfTb1]o .2EW\ͮ]38؋rTJsǏP@芎sF\> P^+dYJLbJ C-xϐn> ι$nj,;Ǖa FU *择|h ~izť3ᤓ`K'-f tL7JK+vf2)V'-sFuB4i+m+@My=O҈0"|Yxoj,3]:cо3 $#uŘ%Y"y죯LebqtҢVzq¼X)~>4L׶m~[1_k?kxֺQ`\ |ٛY4Ѯr!)N9{56(iNq}O()Em]=F&u?$HypWUeB\k]JɩSع9 Zqg4ZĊo oMcjZBU]B\TUd34ݝ~:7ڶSUsB0Z3srx 7`:5xcx !qZA!;%͚7&P H<WL!džOb5kF)xor^aujƍ7 Ǡ8/p^(L>ὴ-B,{ۇWzֺ^k]3\EE@7>lYBȝR.oHnXO/}sB|.i@ɥDB4tcm,@ӣgdtJ!lH$_vN166L__'Z)y&kH;:,Y7=J 9cG) V\hjiE;gya~%ks_nC~Er er)muuMg2;֫R)Md) ,¶ 2-wr#F7<-BBn~_(o=KO㭇[Xv eN_SMgSҐ BS헃D%g_N:/pe -wkG*9yYSZS.9cREL !k}<4_Xs#FmҶ:7R$i,fi!~' # !6/S6y@kZkZcX)%5V4P]VGYq%H1!;e1MV<!ϐHO021Dp= HMs~~a)ަu7G^];git!Frl]H/L$=AeUvZE4P\.,xi {-~p?2b#amXAHq)MWǾI_r`S Hz&|{ +ʖ_= (YS(_g0a03M`I&'9vl?MM+m~}*xT۲(fY*V4x@29s{DaY"toGNTO+xCAO~4Ϳ;p`Ѫ:>Ҵ7K 3}+0 387x\)a"/E>qpWB=1 ¨"MP(\xp߫́A3+J] n[ʼnӼaTbZUWb={~2ooKױӰp(CS\S筐R*JغV&&"FA}J>G֐p1ٸbk7 ŘH$JoN <8s^yk_[;gy-;߉DV{c B yce% aJhDȶ 2IdйIB/^n0tNtџdcKj4϶v~- CBcgqx9= PJ) dMsjpYB] GD4RDWX +h{y`,3ꊕ$`zj*N^TP4L:Iz9~6s) Ga:?y*J~?OrMwP\](21sZUD ?ܟQ5Q%ggW6QdO+\@ ̪X'GxN @'4=ˋ+*VwN ne_|(/BDfj5(Dq<*tNt1х!MV.C0 32b#?n0pzj#!38}޴o1KovCJ`8ŗ_"]] rDUy޲@ Ȗ-;xџ'^Y`zEd?0„ DAL18IS]VGq\4o !swV7ˣι%4FѮ~}6)OgS[~Q vcYbL!wG3 7띸*E Pql8=jT\꘿I(z<[6OrR8ºC~ډ]=rNl[g|v TMTղb-o}OrP^Q]<98S¤!k)G(Vkwyqyr޽Nv`N/e p/~NAOk \I:G6]4+K;j$R:Mi #*[AȚT,ʰ,;N{HZTGMoּy) ]%dHء9Պ䠬|<45,\=[bƟ8QXeB3- &dҩ^{>/86bXmZ]]yޚN[(WAHL$YAgDKp=5GHjU&99v簪C0vygln*P)9^͞}lMuiH!̍#DoRBn9l@ xA/_v=ȺT{7Yt2N"4!YN`ae >Q<XMydEB`VU}u]嫇.%e^ánE87Mu\t`cP=AD/G)sI"@MP;)]%fH9'FNsj1pVhY&9=0pfuJ&gޤx+k:!r˭wkl03׼Ku C &ѓYt{.O.zҏ z}/tf_wEp2gvX)GN#I ݭ߽v/ .& и(ZF{e"=V!{zW`, ]+LGz"(UJp|j( #V4, 8B 0 9OkRrlɱl94)'VH9=9W|>PS['G(*I1==C<5"Pg+x'K5EMd؞Af8lG ?D FtoB[je?{k3zQ vZ;%Ɠ,]E>KZ+T/ EJxOZ1i #T<@ I}q9/t'zi(EMqw`mYkU6;[t4DPeckeM;H}_g pMww}k6#H㶏+b8雡Sxp)&C $@'b,fPߑt$RbJ'vznuS ~8='72_`{q纶|Q)Xk}cPz9p7O:'|G~8wx(a 0QCko|0ASD>Ip=4Q, d|F8RcU"/KM opKle M3#i0c%<7׿p&pZq[TR"BpqauIp$ 8~Ĩ!8Սx\ւdT>>Z40ks7 z2IQ}ItԀ<-%S⍤};zIb$I 5K}Q͙D8UguWE$Jh )cu4N tZl+[]M4k8֦Zeq֮M7uIqG 1==tLtR,ƜSrHYt&QP윯Lg' I,3@P'}'R˪e/%-Auv·ñ\> vDJzlӾNv5:|K/Jb6KI9)Zh*ZAi`?S {aiVDԲuy5W7pWeQJk֤#5&V<̺@/GH?^τZL|IJNvI:'P=Ϛt"¨=cud S Q.Ki0 !cJy;LJR;G{BJy޺[^8fK6)=yʊ+(k|&xQ2`L?Ȓ2@Mf 0C`6-%pKpm')c$׻K5[J*U[/#hH!6acB JA _|uMvDyk y)6OPYjœ50VT K}cǻP[ $:]4MEA.y)|B)cf-A?(e|lɉ#P9V)[9t.EiQPDѠ3ϴ;E:+Օ t ȥ~|_N2,ZJLt4! %ա]u {+=p.GhNcŞQI?Nd'yeh n7zi1DB)1S | S#ًZs2|Ɛy$F SxeX{7Vl.Src3E℃Q>b6G ўYCmtկ~=K0f(=LrAS GN'ɹ9<\!a`)֕y[uՍ[09` 9 +57ts6}b4{oqd+J5fa/,97J#6yν99mRWxJyѡyu_TJc`~W>l^q#Ts#2"nD1%fS)FU w{ܯ R{ ˎ󅃏џDsZSQS;LV;7 Od1&1n$ N /.q3~eNɪ]E#oM~}v֯FڦwyZ=<<>Xo稯lfMFV6p02|*=tV!c~]fa5Y^Q_WN|Vs 0ҘދU97OI'N2'8N֭fgg-}V%y]U4 峧p*91#9U kCac_AFңĪy뚇Y_AiuYyTTYЗ-(!JFLt›17uTozc. S;7A&&<ԋ5y;Ro+:' *eYJkWR[@F %SHWP 72k4 qLd'J "zB6{AC0ƁA6U.'F3:Ȅ(9ΜL;D]m8ڥ9}dU "v!;*13Rg^fJyShyy5auA?ɩGHRjo^]׽S)Fm\toy 4WQS@mE#%5ʈfFYDX ~D5Ϡ9tE9So_aU4?Ѽm%&c{n>.KW1Tlb}:j uGi(JgcYj0qn+>) %\!4{LaJso d||u//P_y7iRJ߬nHOy) l+@$($VFIQ9%EeKʈU. ia&FY̒mZ=)+qqoQn >L!qCiDB;Y<%} OgBxB!ØuG)WG9y(Ą{_yesuZmZZey'Wg#C~1Cev@0D $a@˲(.._GimA:uyw֬%;@!JkQVM_Ow:P.s\)ot- ˹"`B,e CRtaEUP<0'}r3[>?G8xU~Nqu;Wm8\RIkբ^5@k+5(By'L&'gBJ3ݶ!/㮻w҅ yqPWUg<e"Qy*167΃sJ\oz]T*UQ<\FԎ`HaNmڜ6DysCask8wP8y9``GJ9lF\G g's Nn͵MLN֪u$| /|7=]O)6s !ĴAKh]q_ap $HH'\1jB^s\|- W1:=6lJBqjY^LsPk""`]w)󭃈,(HC ?䔨Y$Sʣ{4Z+0NvQkhol6C.婧/u]FwiVjZka&%6\F*Ny#8O,22+|Db~d ~Çwc N:FuuCe&oZ(l;@ee-+Wn`44AMK➝2BRՈt7g*1gph9N) *"TF*R(#'88pm=}X]u[i7bEc|\~EMn}P瘊J)K.0i1M6=7'_\kaZ(Th{K*GJyytw"IO-PWJk)..axӝ47"89Cc7ĐBiZx 7m!fy|ϿF9CbȩV 9V-՛^pV̌ɄS#Bv4-@]Vxt-Z, &ֺ*diؠ2^VXbs֔Ìl.jQ]Y[47gj=幽ex)A0ip׳ W2[ᎇhuE^~q흙L} #-b۸oFJ_QP3r6jr+"nfzRJTUqoaۍ /$d8Mx'ݓ= OՃ| )$2mcM*cЙj}f };n YG w0Ia!1Q.oYfr]DyISaP}"dIӗթO67jqR ҊƐƈaɤGG|h;t]䗖oSv|iZqX)oalv;۩meEJ\!8=$4QU4Xo&VEĊ YS^E#d,yX_> ۘ-e\ "Wa6uLĜZi`aD9.% w~mB(02G[6y.773a7 /=o7D)$Z 66 $bY^\CuP. (x'"J60׿Y:Oi;F{w佩b+\Yi`TDWa~|VH)8q/=9!g߆2Y)?ND)%?Ǐ`k/sn:;O299yB=a[Ng 3˲N}vLNy;*?x?~L&=xyӴ~}q{qE*IQ^^ͧvü{Huu=R|>JyUlZV, B~/YF!Y\u_ݼF{_C)LD]m {H 0ihhadd nUkf3oٺCvE\)QJi+֥@tDJkB$1!Đr0XQ|q?d2) Ӣ_}qv-< FŊ߫%roppVBwü~JidY4:}L6M7f٬F "?71<2#?Jyy4뷢<_a7_=Q E=S1И/9{+93֮E{ǂw{))?maÆm(uLE#lïZ  ~d];+]h j?!|$F}*"4(v'8s<ŏUkm7^7no1w2ؗ}TrͿEk>p'8OB7d7R(A 9.*Mi^ͳ; eeUwS+C)uO@ =Sy]` }l8^ZzRXj[^iUɺ$tj))<sbDJfg=Pk_{xaKo1:-uyG0M ԃ\0Lvuy'ȱc2Ji AdyVgVh!{]/&}}ċJ#%d !+87<;qN޼Nفl|1N:8ya  8}k¾+-$4FiZYÔXk*I&'@iI99)HSh4+2G:tGhS^繿 Kتm0 вDk}֚+QT4;sC}rՅE,8CX-e~>G&'9xpW,%Fh,Ry56Y–hW-(v_,? ; qrBk4-V7HQ;ˇ^Gv1JVV%,ik;D_W!))+BoS4QsTM;gt+ndS-~:11Sgv!0qRVh!"Ȋ(̦Yl.]PQWgٳE'`%W1{ndΗBk|Ž7ʒR~,lnoa&:ü$ 3<a[CBݮwt"o\ePJ=Hz"_c^Z.#ˆ*x z̝grY]tdkP*:97YľXyBkD4N.C_[;F9`8& !AMO c `@BA& Ost\-\NX+Xp < !bj3C&QL+*&kAQ=04}cC!9~820G'PC9xa!w&bo_1 Sw"ܱ V )Yl3+ס2KoXOx]"`^WOy :3GO0g;%Yv㐫(R/r (s } u B &FeYZh0y> =2<Ϟc/ -u= c&׭,.0"g"7 6T!vl#sc>{u/Oh Bᾈ)۴74]x7 gMӒ"d]U)}" v4co[ ɡs 5Gg=XR14?5A}D "b{0$L .\4y{_fe:kVS\\O]c^W52LSBDM! C3Dhr̦RtArx4&agaN3Cf<Ԉp4~ B'"1@.b_/xQ} _߃҉/gٓ2Qkqp0շpZ2fԫYz< 4L.Cyυι1t@鎫Fe sYfsF}^ V}N<_`p)alٶ "(XEAVZ<)2},:Ir*#m_YӼ R%a||EƼIJ,,+f"96r/}0jE/)s)cjW#w'Sʯ5<66lj$a~3Kʛy 2:cZ:Yh))+a߭K::N,Q F'qB]={.]h85C9cr=}*rk?vwV렵ٸW Rs%}rNAkDv|uFLBkWY YkX מ|)1!$#3%y?pF<@<Rr0}: }\J [5FRxY<9"SQdE(Q*Qʻ)q1E0B_O24[U'],lOb ]~WjHޏTQ5Syu wq)xnw8~)c 쫬gٲߠ H% k5dƝk> kEj,0% b"vi2Wس_CuK)K{n|>t{P1򨾜j>'kEkƗBg*H%'_aY6Bn!TL&ɌOb{c`'d^{t\i^[uɐ[}q0lM˕G:‚4kb祔c^:?bpg… +37stH:0}en6x˟%/<]BL&* 5&fK9Mq)/iyqtA%kUe[ڛKN]Ě^,"`/ s[EQQm?|XJ߅92m]G.E΃ח U*Cn.j_)Tѧj̿30ڇ!A0=͜ar I3$C^-9#|pk!)?7.x9 @OO;WƝZBFU keZ75F6Tc6"ZȚs2y/1 ʵ:u4xa`C>6Rb/Yм)^=+~uRd`/|_8xbB0?Ft||Z\##|K 0>>zxv8۴吅q 8ĥ)"6>~\8:qM}#͚'ĉ#p\׶ l#bA?)|g g9|8jP(cr,BwV (WliVxxᡁ@0Okn;ɥh$_ckCgriv}>=wGzβ KkBɛ[˪ !J)h&k2%07δt}!d<9;I&0wV/ v 0<H}L&8ob%Hi|޶o&h1L|u֦y~󛱢8fٲUsւ)0oiFx2}X[zVYr_;N(w]_4B@OanC?gĦx>мgx>ΛToZoOMp>40>V Oy V9iq!4 LN,ˢu{jsz]|"R޻&'ƚ{53ўFu(<٪9:΋]B;)B>1::8;~)Yt|0(pw2N%&X,URBK)3\zz&}ax4;ǟ(tLNg{N|Ǽ\G#C9g$^\}p?556]/RP.90 k,U8/u776s ʪ_01چ|\N 0VV*3H鴃J7iI!wG_^ypl}r*jɤSR 5QN@ iZ#1ٰy;_\3\BQQ x:WJv츟ٯ$"@6 S#qe딇(/P( Dy~TOϻ<4:-+F`0||;Xl-"uw$Цi󼕝mKʩorz"mϺ$F:~E'ҐvD\y?Rr8_He@ e~O,T.(ފR*cY^m|cVR[8 JҡSm!ΆԨb)RHG{?MpqrmN>߶Y)\p,d#xۆWY*,l6]v0h15M˙MS8+EdI='LBJIH7_9{Caз*Lq,dt >+~ّeʏ?xԕ4bBAŚjﵫ!'\Ը$WNvKO}ӽmSşذqsOy?\[,d@'73'j%kOe`1.g2"e =YIzS2|zŐƄa\U,dP;jhhhaxǶ?КZ՚.q SE+XrbOu%\GتX(H,N^~]JyEZQKceTQ]VGYqnah;y$cQahT&QPZ*iZ8UQQM.qo/T\7X"u?Mttl2Xq(IoW{R^ ux*SYJ! 4S.Jy~ BROS[V|žKNɛP(L6V^|cR7i7nZW1Fd@ Ara{詑|(T*dN]Ko?s=@ |_EvF]׍kR)eBJc" MUUbY6`~V޴dJKß&~'d3i WWWWWW
Current Directory: /opt/cloudlinux/venv/lib/python3.11/site-packages/numpy
Viewing File: /opt/cloudlinux/venv/lib/python3.11/site-packages/numpy/__init__.pxd
# NumPy static imports for Cython < 3.0 # # If any of the PyArray_* functions are called, import_array must be # called first. # # Author: Dag Sverre Seljebotn # DEF _buffer_format_string_len = 255 cimport cpython.buffer as pybuf from cpython.ref cimport Py_INCREF from cpython.mem cimport PyObject_Malloc, PyObject_Free from cpython.object cimport PyObject, PyTypeObject from cpython.buffer cimport PyObject_GetBuffer from cpython.type cimport type cimport libc.stdio as stdio cdef extern from "Python.h": ctypedef int Py_intptr_t bint PyObject_TypeCheck(object obj, PyTypeObject* type) cdef extern from "numpy/arrayobject.h": ctypedef Py_intptr_t npy_intp ctypedef size_t npy_uintp cdef enum NPY_TYPES: NPY_BOOL NPY_BYTE NPY_UBYTE NPY_SHORT NPY_USHORT NPY_INT NPY_UINT NPY_LONG NPY_ULONG NPY_LONGLONG NPY_ULONGLONG NPY_FLOAT NPY_DOUBLE NPY_LONGDOUBLE NPY_CFLOAT NPY_CDOUBLE NPY_CLONGDOUBLE NPY_OBJECT NPY_STRING NPY_UNICODE NPY_VOID NPY_DATETIME NPY_TIMEDELTA NPY_NTYPES NPY_NOTYPE NPY_INT8 NPY_INT16 NPY_INT32 NPY_INT64 NPY_INT128 NPY_INT256 NPY_UINT8 NPY_UINT16 NPY_UINT32 NPY_UINT64 NPY_UINT128 NPY_UINT256 NPY_FLOAT16 NPY_FLOAT32 NPY_FLOAT64 NPY_FLOAT80 NPY_FLOAT96 NPY_FLOAT128 NPY_FLOAT256 NPY_COMPLEX32 NPY_COMPLEX64 NPY_COMPLEX128 NPY_COMPLEX160 NPY_COMPLEX192 NPY_COMPLEX256 NPY_COMPLEX512 NPY_INTP ctypedef enum NPY_ORDER: NPY_ANYORDER NPY_CORDER NPY_FORTRANORDER NPY_KEEPORDER ctypedef enum NPY_CASTING: NPY_NO_CASTING NPY_EQUIV_CASTING NPY_SAFE_CASTING NPY_SAME_KIND_CASTING NPY_UNSAFE_CASTING ctypedef enum NPY_CLIPMODE: NPY_CLIP NPY_WRAP NPY_RAISE ctypedef enum NPY_SCALARKIND: NPY_NOSCALAR, NPY_BOOL_SCALAR, NPY_INTPOS_SCALAR, NPY_INTNEG_SCALAR, NPY_FLOAT_SCALAR, NPY_COMPLEX_SCALAR, NPY_OBJECT_SCALAR ctypedef enum NPY_SORTKIND: NPY_QUICKSORT NPY_HEAPSORT NPY_MERGESORT ctypedef enum NPY_SEARCHSIDE: NPY_SEARCHLEFT NPY_SEARCHRIGHT enum: # DEPRECATED since NumPy 1.7 ! Do not use in new code! NPY_C_CONTIGUOUS NPY_F_CONTIGUOUS NPY_CONTIGUOUS NPY_FORTRAN NPY_OWNDATA NPY_FORCECAST NPY_ENSURECOPY NPY_ENSUREARRAY NPY_ELEMENTSTRIDES NPY_ALIGNED NPY_NOTSWAPPED NPY_WRITEABLE NPY_ARR_HAS_DESCR NPY_BEHAVED NPY_BEHAVED_NS NPY_CARRAY NPY_CARRAY_RO NPY_FARRAY NPY_FARRAY_RO NPY_DEFAULT NPY_IN_ARRAY NPY_OUT_ARRAY NPY_INOUT_ARRAY NPY_IN_FARRAY NPY_OUT_FARRAY NPY_INOUT_FARRAY NPY_UPDATE_ALL enum: # Added in NumPy 1.7 to replace the deprecated enums above. NPY_ARRAY_C_CONTIGUOUS NPY_ARRAY_F_CONTIGUOUS NPY_ARRAY_OWNDATA NPY_ARRAY_FORCECAST NPY_ARRAY_ENSURECOPY NPY_ARRAY_ENSUREARRAY NPY_ARRAY_ELEMENTSTRIDES NPY_ARRAY_ALIGNED NPY_ARRAY_NOTSWAPPED NPY_ARRAY_WRITEABLE NPY_ARRAY_WRITEBACKIFCOPY NPY_ARRAY_BEHAVED NPY_ARRAY_BEHAVED_NS NPY_ARRAY_CARRAY NPY_ARRAY_CARRAY_RO NPY_ARRAY_FARRAY NPY_ARRAY_FARRAY_RO NPY_ARRAY_DEFAULT NPY_ARRAY_IN_ARRAY NPY_ARRAY_OUT_ARRAY NPY_ARRAY_INOUT_ARRAY NPY_ARRAY_IN_FARRAY NPY_ARRAY_OUT_FARRAY NPY_ARRAY_INOUT_FARRAY NPY_ARRAY_UPDATE_ALL cdef enum: NPY_MAXDIMS npy_intp NPY_MAX_ELSIZE ctypedef void (*PyArray_VectorUnaryFunc)(void *, void *, npy_intp, void *, void *) ctypedef struct PyArray_ArrayDescr: # shape is a tuple, but Cython doesn't support "tuple shape" # inside a non-PyObject declaration, so we have to declare it # as just a PyObject*. PyObject* shape ctypedef struct PyArray_Descr: pass ctypedef class numpy.dtype [object PyArray_Descr, check_size ignore]: # Use PyDataType_* macros when possible, however there are no macros # for accessing some of the fields, so some are defined. cdef PyTypeObject* typeobj cdef char kind cdef char type # Numpy sometimes mutates this without warning (e.g. it'll # sometimes change "|" to "<" in shared dtype objects on # little-endian machines). If this matters to you, use # PyArray_IsNativeByteOrder(dtype.byteorder) instead of # directly accessing this field. cdef char byteorder cdef char flags cdef int type_num cdef int itemsize "elsize" cdef int alignment cdef object fields cdef tuple names # Use PyDataType_HASSUBARRAY to test whether this field is # valid (the pointer can be NULL). Most users should access # this field via the inline helper method PyDataType_SHAPE. cdef PyArray_ArrayDescr* subarray ctypedef class numpy.flatiter [object PyArrayIterObject, check_size ignore]: # Use through macros pass ctypedef class numpy.broadcast [object PyArrayMultiIterObject, check_size ignore]: cdef int numiter cdef npy_intp size, index cdef int nd cdef npy_intp *dimensions cdef void **iters ctypedef struct PyArrayObject: # For use in situations where ndarray can't replace PyArrayObject*, # like PyArrayObject**. pass ctypedef class numpy.ndarray [object PyArrayObject, check_size ignore]: cdef __cythonbufferdefaults__ = {"mode": "strided"} cdef: # Only taking a few of the most commonly used and stable fields. # One should use PyArray_* macros instead to access the C fields. char *data int ndim "nd" npy_intp *shape "dimensions" npy_intp *strides dtype descr # deprecated since NumPy 1.7 ! PyObject* base # NOT PUBLIC, DO NOT USE ! ctypedef unsigned char npy_bool ctypedef signed char npy_byte ctypedef signed short npy_short ctypedef signed int npy_int ctypedef signed long npy_long ctypedef signed long long npy_longlong ctypedef unsigned char npy_ubyte ctypedef unsigned short npy_ushort ctypedef unsigned int npy_uint ctypedef unsigned long npy_ulong ctypedef unsigned long long npy_ulonglong ctypedef float npy_float ctypedef double npy_double ctypedef long double npy_longdouble ctypedef signed char npy_int8 ctypedef signed short npy_int16 ctypedef signed int npy_int32 ctypedef signed long long npy_int64 ctypedef signed long long npy_int96 ctypedef signed long long npy_int128 ctypedef unsigned char npy_uint8 ctypedef unsigned short npy_uint16 ctypedef unsigned int npy_uint32 ctypedef unsigned long long npy_uint64 ctypedef unsigned long long npy_uint96 ctypedef unsigned long long npy_uint128 ctypedef float npy_float32 ctypedef double npy_float64 ctypedef long double npy_float80 ctypedef long double npy_float96 ctypedef long double npy_float128 ctypedef struct npy_cfloat: float real float imag ctypedef struct npy_cdouble: double real double imag ctypedef struct npy_clongdouble: long double real long double imag ctypedef struct npy_complex64: float real float imag ctypedef struct npy_complex128: double real double imag ctypedef struct npy_complex160: long double real long double imag ctypedef struct npy_complex192: long double real long double imag ctypedef struct npy_complex256: long double real long double imag ctypedef struct PyArray_Dims: npy_intp *ptr int len int _import_array() except -1 # A second definition so _import_array isn't marked as used when we use it here. # Do not use - subject to change any time. int __pyx_import_array "_import_array"() except -1 # # Macros from ndarrayobject.h # bint PyArray_CHKFLAGS(ndarray m, int flags) nogil bint PyArray_IS_C_CONTIGUOUS(ndarray arr) nogil bint PyArray_IS_F_CONTIGUOUS(ndarray arr) nogil bint PyArray_ISCONTIGUOUS(ndarray m) nogil bint PyArray_ISWRITEABLE(ndarray m) nogil bint PyArray_ISALIGNED(ndarray m) nogil int PyArray_NDIM(ndarray) nogil bint PyArray_ISONESEGMENT(ndarray) nogil bint PyArray_ISFORTRAN(ndarray) nogil int PyArray_FORTRANIF(ndarray) nogil void* PyArray_DATA(ndarray) nogil char* PyArray_BYTES(ndarray) nogil npy_intp* PyArray_DIMS(ndarray) nogil npy_intp* PyArray_STRIDES(ndarray) nogil npy_intp PyArray_DIM(ndarray, size_t) nogil npy_intp PyArray_STRIDE(ndarray, size_t) nogil PyObject *PyArray_BASE(ndarray) nogil # returns borrowed reference! PyArray_Descr *PyArray_DESCR(ndarray) nogil # returns borrowed reference to dtype! int PyArray_FLAGS(ndarray) nogil npy_intp PyArray_ITEMSIZE(ndarray) nogil int PyArray_TYPE(ndarray arr) nogil object PyArray_GETITEM(ndarray arr, void *itemptr) int PyArray_SETITEM(ndarray arr, void *itemptr, object obj) except -1 bint PyTypeNum_ISBOOL(int) nogil bint PyTypeNum_ISUNSIGNED(int) nogil bint PyTypeNum_ISSIGNED(int) nogil bint PyTypeNum_ISINTEGER(int) nogil bint PyTypeNum_ISFLOAT(int) nogil bint PyTypeNum_ISNUMBER(int) nogil bint PyTypeNum_ISSTRING(int) nogil bint PyTypeNum_ISCOMPLEX(int) nogil bint PyTypeNum_ISPYTHON(int) nogil bint PyTypeNum_ISFLEXIBLE(int) nogil bint PyTypeNum_ISUSERDEF(int) nogil bint PyTypeNum_ISEXTENDED(int) nogil bint PyTypeNum_ISOBJECT(int) nogil bint PyDataType_ISBOOL(dtype) nogil bint PyDataType_ISUNSIGNED(dtype) nogil bint PyDataType_ISSIGNED(dtype) nogil bint PyDataType_ISINTEGER(dtype) nogil bint PyDataType_ISFLOAT(dtype) nogil bint PyDataType_ISNUMBER(dtype) nogil bint PyDataType_ISSTRING(dtype) nogil bint PyDataType_ISCOMPLEX(dtype) nogil bint PyDataType_ISPYTHON(dtype) nogil bint PyDataType_ISFLEXIBLE(dtype) nogil bint PyDataType_ISUSERDEF(dtype) nogil bint PyDataType_ISEXTENDED(dtype) nogil bint PyDataType_ISOBJECT(dtype) nogil bint PyDataType_HASFIELDS(dtype) nogil bint PyDataType_HASSUBARRAY(dtype) nogil bint PyArray_ISBOOL(ndarray) nogil bint PyArray_ISUNSIGNED(ndarray) nogil bint PyArray_ISSIGNED(ndarray) nogil bint PyArray_ISINTEGER(ndarray) nogil bint PyArray_ISFLOAT(ndarray) nogil bint PyArray_ISNUMBER(ndarray) nogil bint PyArray_ISSTRING(ndarray) nogil bint PyArray_ISCOMPLEX(ndarray) nogil bint PyArray_ISPYTHON(ndarray) nogil bint PyArray_ISFLEXIBLE(ndarray) nogil bint PyArray_ISUSERDEF(ndarray) nogil bint PyArray_ISEXTENDED(ndarray) nogil bint PyArray_ISOBJECT(ndarray) nogil bint PyArray_HASFIELDS(ndarray) nogil bint PyArray_ISVARIABLE(ndarray) nogil bint PyArray_SAFEALIGNEDCOPY(ndarray) nogil bint PyArray_ISNBO(char) nogil # works on ndarray.byteorder bint PyArray_IsNativeByteOrder(char) nogil # works on ndarray.byteorder bint PyArray_ISNOTSWAPPED(ndarray) nogil bint PyArray_ISBYTESWAPPED(ndarray) nogil bint PyArray_FLAGSWAP(ndarray, int) nogil bint PyArray_ISCARRAY(ndarray) nogil bint PyArray_ISCARRAY_RO(ndarray) nogil bint PyArray_ISFARRAY(ndarray) nogil bint PyArray_ISFARRAY_RO(ndarray) nogil bint PyArray_ISBEHAVED(ndarray) nogil bint PyArray_ISBEHAVED_RO(ndarray) nogil bint PyDataType_ISNOTSWAPPED(dtype) nogil bint PyDataType_ISBYTESWAPPED(dtype) nogil bint PyArray_DescrCheck(object) bint PyArray_Check(object) bint PyArray_CheckExact(object) # Cannot be supported due to out arg: # bint PyArray_HasArrayInterfaceType(object, dtype, object, object&) # bint PyArray_HasArrayInterface(op, out) bint PyArray_IsZeroDim(object) # Cannot be supported due to ## ## in macro: # bint PyArray_IsScalar(object, verbatim work) bint PyArray_CheckScalar(object) bint PyArray_IsPythonNumber(object) bint PyArray_IsPythonScalar(object) bint PyArray_IsAnyScalar(object) bint PyArray_CheckAnyScalar(object) ndarray PyArray_GETCONTIGUOUS(ndarray) bint PyArray_SAMESHAPE(ndarray, ndarray) nogil npy_intp PyArray_SIZE(ndarray) nogil npy_intp PyArray_NBYTES(ndarray) nogil object PyArray_FROM_O(object) object PyArray_FROM_OF(object m, int flags) object PyArray_FROM_OT(object m, int type) object PyArray_FROM_OTF(object m, int type, int flags) object PyArray_FROMANY(object m, int type, int min, int max, int flags) object PyArray_ZEROS(int nd, npy_intp* dims, int type, int fortran) object PyArray_EMPTY(int nd, npy_intp* dims, int type, int fortran) void PyArray_FILLWBYTE(object, int val) npy_intp PyArray_REFCOUNT(object) object PyArray_ContiguousFromAny(op, int, int min_depth, int max_depth) unsigned char PyArray_EquivArrTypes(ndarray a1, ndarray a2) bint PyArray_EquivByteorders(int b1, int b2) nogil object PyArray_SimpleNew(int nd, npy_intp* dims, int typenum) object PyArray_SimpleNewFromData(int nd, npy_intp* dims, int typenum, void* data) #object PyArray_SimpleNewFromDescr(int nd, npy_intp* dims, dtype descr) object PyArray_ToScalar(void* data, ndarray arr) void* PyArray_GETPTR1(ndarray m, npy_intp i) nogil void* PyArray_GETPTR2(ndarray m, npy_intp i, npy_intp j) nogil void* PyArray_GETPTR3(ndarray m, npy_intp i, npy_intp j, npy_intp k) nogil void* PyArray_GETPTR4(ndarray m, npy_intp i, npy_intp j, npy_intp k, npy_intp l) nogil # Cannot be supported due to out arg # void PyArray_DESCR_REPLACE(descr) object PyArray_Copy(ndarray) object PyArray_FromObject(object op, int type, int min_depth, int max_depth) object PyArray_ContiguousFromObject(object op, int type, int min_depth, int max_depth) object PyArray_CopyFromObject(object op, int type, int min_depth, int max_depth) object PyArray_Cast(ndarray mp, int type_num) object PyArray_Take(ndarray ap, object items, int axis) object PyArray_Put(ndarray ap, object items, object values) void PyArray_ITER_RESET(flatiter it) nogil void PyArray_ITER_NEXT(flatiter it) nogil void PyArray_ITER_GOTO(flatiter it, npy_intp* destination) nogil void PyArray_ITER_GOTO1D(flatiter it, npy_intp ind) nogil void* PyArray_ITER_DATA(flatiter it) nogil bint PyArray_ITER_NOTDONE(flatiter it) nogil void PyArray_MultiIter_RESET(broadcast multi) nogil void PyArray_MultiIter_NEXT(broadcast multi) nogil void PyArray_MultiIter_GOTO(broadcast multi, npy_intp dest) nogil void PyArray_MultiIter_GOTO1D(broadcast multi, npy_intp ind) nogil void* PyArray_MultiIter_DATA(broadcast multi, npy_intp i) nogil void PyArray_MultiIter_NEXTi(broadcast multi, npy_intp i) nogil bint PyArray_MultiIter_NOTDONE(broadcast multi) nogil # Functions from __multiarray_api.h # Functions taking dtype and returning object/ndarray are disabled # for now as they steal dtype references. I'm conservative and disable # more than is probably needed until it can be checked further. int PyArray_SetNumericOps (object) except -1 object PyArray_GetNumericOps () int PyArray_INCREF (ndarray) except * # uses PyArray_Item_INCREF... int PyArray_XDECREF (ndarray) except * # uses PyArray_Item_DECREF... void PyArray_SetStringFunction (object, int) dtype PyArray_DescrFromType (int) object PyArray_TypeObjectFromType (int) char * PyArray_Zero (ndarray) char * PyArray_One (ndarray) #object PyArray_CastToType (ndarray, dtype, int) int PyArray_CastTo (ndarray, ndarray) except -1 int PyArray_CastAnyTo (ndarray, ndarray) except -1 int PyArray_CanCastSafely (int, int) # writes errors npy_bool PyArray_CanCastTo (dtype, dtype) # writes errors int PyArray_ObjectType (object, int) except 0 dtype PyArray_DescrFromObject (object, dtype) #ndarray* PyArray_ConvertToCommonType (object, int *) dtype PyArray_DescrFromScalar (object) dtype PyArray_DescrFromTypeObject (object) npy_intp PyArray_Size (object) #object PyArray_Scalar (void *, dtype, object) #object PyArray_FromScalar (object, dtype) void PyArray_ScalarAsCtype (object, void *) #int PyArray_CastScalarToCtype (object, void *, dtype) #int PyArray_CastScalarDirect (object, dtype, void *, int) object PyArray_ScalarFromObject (object) #PyArray_VectorUnaryFunc * PyArray_GetCastFunc (dtype, int) object PyArray_FromDims (int, int *, int) #object PyArray_FromDimsAndDataAndDescr (int, int *, dtype, char *) #object PyArray_FromAny (object, dtype, int, int, int, object) object PyArray_EnsureArray (object) object PyArray_EnsureAnyArray (object) #object PyArray_FromFile (stdio.FILE *, dtype, npy_intp, char *) #object PyArray_FromString (char *, npy_intp, dtype, npy_intp, char *) #object PyArray_FromBuffer (object, dtype, npy_intp, npy_intp) #object PyArray_FromIter (object, dtype, npy_intp) object PyArray_Return (ndarray) #object PyArray_GetField (ndarray, dtype, int) #int PyArray_SetField (ndarray, dtype, int, object) except -1 object PyArray_Byteswap (ndarray, npy_bool) object PyArray_Resize (ndarray, PyArray_Dims *, int, NPY_ORDER) int PyArray_MoveInto (ndarray, ndarray) except -1 int PyArray_CopyInto (ndarray, ndarray) except -1 int PyArray_CopyAnyInto (ndarray, ndarray) except -1 int PyArray_CopyObject (ndarray, object) except -1 object PyArray_NewCopy (ndarray, NPY_ORDER) object PyArray_ToList (ndarray) object PyArray_ToString (ndarray, NPY_ORDER) int PyArray_ToFile (ndarray, stdio.FILE *, char *, char *) except -1 int PyArray_Dump (object, object, int) except -1 object PyArray_Dumps (object, int) int PyArray_ValidType (int) # Cannot error void PyArray_UpdateFlags (ndarray, int) object PyArray_New (type, int, npy_intp *, int, npy_intp *, void *, int, int, object) #object PyArray_NewFromDescr (type, dtype, int, npy_intp *, npy_intp *, void *, int, object) #dtype PyArray_DescrNew (dtype) dtype PyArray_DescrNewFromType (int) double PyArray_GetPriority (object, double) # clears errors as of 1.25 object PyArray_IterNew (object) object PyArray_MultiIterNew (int, ...) int PyArray_PyIntAsInt (object) except? -1 npy_intp PyArray_PyIntAsIntp (object) int PyArray_Broadcast (broadcast) except -1 void PyArray_FillObjectArray (ndarray, object) except * int PyArray_FillWithScalar (ndarray, object) except -1 npy_bool PyArray_CheckStrides (int, int, npy_intp, npy_intp, npy_intp *, npy_intp *) dtype PyArray_DescrNewByteorder (dtype, char) object PyArray_IterAllButAxis (object, int *) #object PyArray_CheckFromAny (object, dtype, int, int, int, object) #object PyArray_FromArray (ndarray, dtype, int) object PyArray_FromInterface (object) object PyArray_FromStructInterface (object) #object PyArray_FromArrayAttr (object, dtype, object) #NPY_SCALARKIND PyArray_ScalarKind (int, ndarray*) int PyArray_CanCoerceScalar (int, int, NPY_SCALARKIND) object PyArray_NewFlagsObject (object) npy_bool PyArray_CanCastScalar (type, type) #int PyArray_CompareUCS4 (npy_ucs4 *, npy_ucs4 *, register size_t) int PyArray_RemoveSmallest (broadcast) except -1 int PyArray_ElementStrides (object) void PyArray_Item_INCREF (char *, dtype) except * void PyArray_Item_XDECREF (char *, dtype) except * object PyArray_FieldNames (object) object PyArray_Transpose (ndarray, PyArray_Dims *) object PyArray_TakeFrom (ndarray, object, int, ndarray, NPY_CLIPMODE) object PyArray_PutTo (ndarray, object, object, NPY_CLIPMODE) object PyArray_PutMask (ndarray, object, object) object PyArray_Repeat (ndarray, object, int) object PyArray_Choose (ndarray, object, ndarray, NPY_CLIPMODE) int PyArray_Sort (ndarray, int, NPY_SORTKIND) except -1 object PyArray_ArgSort (ndarray, int, NPY_SORTKIND) object PyArray_SearchSorted (ndarray, object, NPY_SEARCHSIDE, PyObject *) object PyArray_ArgMax (ndarray, int, ndarray) object PyArray_ArgMin (ndarray, int, ndarray) object PyArray_Reshape (ndarray, object) object PyArray_Newshape (ndarray, PyArray_Dims *, NPY_ORDER) object PyArray_Squeeze (ndarray) #object PyArray_View (ndarray, dtype, type) object PyArray_SwapAxes (ndarray, int, int) object PyArray_Max (ndarray, int, ndarray) object PyArray_Min (ndarray, int, ndarray) object PyArray_Ptp (ndarray, int, ndarray) object PyArray_Mean (ndarray, int, int, ndarray) object PyArray_Trace (ndarray, int, int, int, int, ndarray) object PyArray_Diagonal (ndarray, int, int, int) object PyArray_Clip (ndarray, object, object, ndarray) object PyArray_Conjugate (ndarray, ndarray) object PyArray_Nonzero (ndarray) object PyArray_Std (ndarray, int, int, ndarray, int) object PyArray_Sum (ndarray, int, int, ndarray) object PyArray_CumSum (ndarray, int, int, ndarray) object PyArray_Prod (ndarray, int, int, ndarray) object PyArray_CumProd (ndarray, int, int, ndarray) object PyArray_All (ndarray, int, ndarray) object PyArray_Any (ndarray, int, ndarray) object PyArray_Compress (ndarray, object, int, ndarray) object PyArray_Flatten (ndarray, NPY_ORDER) object PyArray_Ravel (ndarray, NPY_ORDER) npy_intp PyArray_MultiplyList (npy_intp *, int) int PyArray_MultiplyIntList (int *, int) void * PyArray_GetPtr (ndarray, npy_intp*) int PyArray_CompareLists (npy_intp *, npy_intp *, int) #int PyArray_AsCArray (object*, void *, npy_intp *, int, dtype) #int PyArray_As1D (object*, char **, int *, int) #int PyArray_As2D (object*, char ***, int *, int *, int) int PyArray_Free (object, void *) #int PyArray_Converter (object, object*) int PyArray_IntpFromSequence (object, npy_intp *, int) except -1 object PyArray_Concatenate (object, int) object PyArray_InnerProduct (object, object) object PyArray_MatrixProduct (object, object) object PyArray_CopyAndTranspose (object) object PyArray_Correlate (object, object, int) int PyArray_TypestrConvert (int, int) #int PyArray_DescrConverter (object, dtype*) except 0 #int PyArray_DescrConverter2 (object, dtype*) except 0 int PyArray_IntpConverter (object, PyArray_Dims *) except 0 #int PyArray_BufferConverter (object, chunk) except 0 int PyArray_AxisConverter (object, int *) except 0 int PyArray_BoolConverter (object, npy_bool *) except 0 int PyArray_ByteorderConverter (object, char *) except 0 int PyArray_OrderConverter (object, NPY_ORDER *) except 0 unsigned char PyArray_EquivTypes (dtype, dtype) # clears errors #object PyArray_Zeros (int, npy_intp *, dtype, int) #object PyArray_Empty (int, npy_intp *, dtype, int) object PyArray_Where (object, object, object) object PyArray_Arange (double, double, double, int) #object PyArray_ArangeObj (object, object, object, dtype) int PyArray_SortkindConverter (object, NPY_SORTKIND *) except 0 object PyArray_LexSort (object, int) object PyArray_Round (ndarray, int, ndarray) unsigned char PyArray_EquivTypenums (int, int) int PyArray_RegisterDataType (dtype) except -1 int PyArray_RegisterCastFunc (dtype, int, PyArray_VectorUnaryFunc *) except -1 int PyArray_RegisterCanCast (dtype, int, NPY_SCALARKIND) except -1 #void PyArray_InitArrFuncs (PyArray_ArrFuncs *) object PyArray_IntTupleFromIntp (int, npy_intp *) int PyArray_TypeNumFromName (char *) int PyArray_ClipmodeConverter (object, NPY_CLIPMODE *) except 0 #int PyArray_OutputConverter (object, ndarray*) except 0 object PyArray_BroadcastToShape (object, npy_intp *, int) void _PyArray_SigintHandler (int) void* _PyArray_GetSigintBuf () #int PyArray_DescrAlignConverter (object, dtype*) except 0 #int PyArray_DescrAlignConverter2 (object, dtype*) except 0 int PyArray_SearchsideConverter (object, void *) except 0 object PyArray_CheckAxis (ndarray, int *, int) npy_intp PyArray_OverflowMultiplyList (npy_intp *, int) int PyArray_CompareString (char *, char *, size_t) int PyArray_SetBaseObject(ndarray, base) except -1 # NOTE: steals a reference to base! Use "set_array_base()" instead. # Typedefs that matches the runtime dtype objects in # the numpy module. # The ones that are commented out needs an IFDEF function # in Cython to enable them only on the right systems. ctypedef npy_int8 int8_t ctypedef npy_int16 int16_t ctypedef npy_int32 int32_t ctypedef npy_int64 int64_t #ctypedef npy_int96 int96_t #ctypedef npy_int128 int128_t ctypedef npy_uint8 uint8_t ctypedef npy_uint16 uint16_t ctypedef npy_uint32 uint32_t ctypedef npy_uint64 uint64_t #ctypedef npy_uint96 uint96_t #ctypedef npy_uint128 uint128_t ctypedef npy_float32 float32_t ctypedef npy_float64 float64_t #ctypedef npy_float80 float80_t #ctypedef npy_float128 float128_t ctypedef float complex complex64_t ctypedef double complex complex128_t # The int types are mapped a bit surprising -- # numpy.int corresponds to 'l' and numpy.long to 'q' ctypedef npy_long int_t ctypedef npy_longlong longlong_t ctypedef npy_ulong uint_t ctypedef npy_ulonglong ulonglong_t ctypedef npy_intp intp_t ctypedef npy_uintp uintp_t ctypedef npy_double float_t ctypedef npy_double double_t ctypedef npy_longdouble longdouble_t ctypedef npy_cfloat cfloat_t ctypedef npy_cdouble cdouble_t ctypedef npy_clongdouble clongdouble_t ctypedef npy_cdouble complex_t cdef inline object PyArray_MultiIterNew1(a): return PyArray_MultiIterNew(1, <void*>a) cdef inline object PyArray_MultiIterNew2(a, b): return PyArray_MultiIterNew(2, <void*>a, <void*>b) cdef inline object PyArray_MultiIterNew3(a, b, c): return PyArray_MultiIterNew(3, <void*>a, <void*>b, <void*> c) cdef inline object PyArray_MultiIterNew4(a, b, c, d): return PyArray_MultiIterNew(4, <void*>a, <void*>b, <void*>c, <void*> d) cdef inline object PyArray_MultiIterNew5(a, b, c, d, e): return PyArray_MultiIterNew(5, <void*>a, <void*>b, <void*>c, <void*> d, <void*> e) cdef inline tuple PyDataType_SHAPE(dtype d): if PyDataType_HASSUBARRAY(d): return <tuple>d.subarray.shape else: return () cdef extern from "numpy/ndarrayobject.h": PyTypeObject PyTimedeltaArrType_Type PyTypeObject PyDatetimeArrType_Type ctypedef int64_t npy_timedelta ctypedef int64_t npy_datetime cdef extern from "numpy/ndarraytypes.h": ctypedef struct PyArray_DatetimeMetaData: NPY_DATETIMEUNIT base int64_t num cdef extern from "numpy/arrayscalars.h": # abstract types ctypedef class numpy.generic [object PyObject]: pass ctypedef class numpy.number [object PyObject]: pass ctypedef class numpy.integer [object PyObject]: pass ctypedef class numpy.signedinteger [object PyObject]: pass ctypedef class numpy.unsignedinteger [object PyObject]: pass ctypedef class numpy.inexact [object PyObject]: pass ctypedef class numpy.floating [object PyObject]: pass ctypedef class numpy.complexfloating [object PyObject]: pass ctypedef class numpy.flexible [object PyObject]: pass ctypedef class numpy.character [object PyObject]: pass ctypedef struct PyDatetimeScalarObject: # PyObject_HEAD npy_datetime obval PyArray_DatetimeMetaData obmeta ctypedef struct PyTimedeltaScalarObject: # PyObject_HEAD npy_timedelta obval PyArray_DatetimeMetaData obmeta ctypedef enum NPY_DATETIMEUNIT: NPY_FR_Y NPY_FR_M NPY_FR_W NPY_FR_D NPY_FR_B NPY_FR_h NPY_FR_m NPY_FR_s NPY_FR_ms NPY_FR_us NPY_FR_ns NPY_FR_ps NPY_FR_fs NPY_FR_as # # ufunc API # cdef extern from "numpy/ufuncobject.h": ctypedef void (*PyUFuncGenericFunction) (char **, npy_intp *, npy_intp *, void *) ctypedef class numpy.ufunc [object PyUFuncObject, check_size ignore]: cdef: int nin, nout, nargs int identity PyUFuncGenericFunction *functions void **data int ntypes int check_return char *name char *types char *doc void *ptr PyObject *obj PyObject *userloops cdef enum: PyUFunc_Zero PyUFunc_One PyUFunc_None UFUNC_ERR_IGNORE UFUNC_ERR_WARN UFUNC_ERR_RAISE UFUNC_ERR_CALL UFUNC_ERR_PRINT UFUNC_ERR_LOG UFUNC_MASK_DIVIDEBYZERO UFUNC_MASK_OVERFLOW UFUNC_MASK_UNDERFLOW UFUNC_MASK_INVALID UFUNC_SHIFT_DIVIDEBYZERO UFUNC_SHIFT_OVERFLOW UFUNC_SHIFT_UNDERFLOW UFUNC_SHIFT_INVALID UFUNC_FPE_DIVIDEBYZERO UFUNC_FPE_OVERFLOW UFUNC_FPE_UNDERFLOW UFUNC_FPE_INVALID UFUNC_ERR_DEFAULT UFUNC_ERR_DEFAULT2 object PyUFunc_FromFuncAndData(PyUFuncGenericFunction *, void **, char *, int, int, int, int, char *, char *, int) int PyUFunc_RegisterLoopForType(ufunc, int, PyUFuncGenericFunction, int *, void *) except -1 void PyUFunc_f_f_As_d_d \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_d_d \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_f_f \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_g_g \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_F_F_As_D_D \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_F_F \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_D_D \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_G_G \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_O_O \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_ff_f_As_dd_d \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_ff_f \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_dd_d \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_gg_g \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_FF_F_As_DD_D \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_DD_D \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_FF_F \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_GG_G \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_OO_O \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_O_O_method \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_OO_O_method \ (char **, npy_intp *, npy_intp *, void *) void PyUFunc_On_Om \ (char **, npy_intp *, npy_intp *, void *) int PyUFunc_GetPyValues \ (char *, int *, int *, PyObject **) int PyUFunc_checkfperr \ (int, PyObject *, int *) void PyUFunc_clearfperr() int PyUFunc_getfperr() int PyUFunc_handlefperr \ (int, PyObject *, int, int *) except -1 int PyUFunc_ReplaceLoopBySignature \ (ufunc, PyUFuncGenericFunction, int *, PyUFuncGenericFunction *) object PyUFunc_FromFuncAndDataAndSignature \ (PyUFuncGenericFunction *, void **, char *, int, int, int, int, char *, char *, int, char *) int _import_umath() except -1 cdef inline void set_array_base(ndarray arr, object base): Py_INCREF(base) # important to do this before stealing the reference below! PyArray_SetBaseObject(arr, base) cdef inline object get_array_base(ndarray arr): base = PyArray_BASE(arr) if base is NULL: return None return <object>base # Versions of the import_* functions which are more suitable for # Cython code. cdef inline int import_array() except -1: try: __pyx_import_array() except Exception: raise ImportError("numpy.core.multiarray failed to import") cdef inline int import_umath() except -1: try: _import_umath() except Exception: raise ImportError("numpy.core.umath failed to import") cdef inline int import_ufunc() except -1: try: _import_umath() except Exception: raise ImportError("numpy.core.umath failed to import") cdef extern from *: # Leave a marker that the NumPy declarations came from this file # See https://github.com/cython/cython/issues/3573 """ /* NumPy API declarations from "numpy/__init__.pxd" */ """ cdef inline bint is_timedelta64_object(object obj): """ Cython equivalent of `isinstance(obj, np.timedelta64)` Parameters ---------- obj : object Returns ------- bool """ return PyObject_TypeCheck(obj, &PyTimedeltaArrType_Type) cdef inline bint is_datetime64_object(object obj): """ Cython equivalent of `isinstance(obj, np.datetime64)` Parameters ---------- obj : object Returns ------- bool """ return PyObject_TypeCheck(obj, &PyDatetimeArrType_Type) cdef inline npy_datetime get_datetime64_value(object obj) nogil: """ returns the int64 value underlying scalar numpy datetime64 object Note that to interpret this as a datetime, the corresponding unit is also needed. That can be found using `get_datetime64_unit`. """ return (<PyDatetimeScalarObject*>obj).obval cdef inline npy_timedelta get_timedelta64_value(object obj) nogil: """ returns the int64 value underlying scalar numpy timedelta64 object """ return (<PyTimedeltaScalarObject*>obj).obval cdef inline NPY_DATETIMEUNIT get_datetime64_unit(object obj) nogil: """ returns the unit part of the dtype for a numpy datetime64 object. """ return <NPY_DATETIMEUNIT>(<PyDatetimeScalarObject*>obj).obmeta.base