^MhQWUdZddlZddlmZddlmZmZmZddlZ ddl mZ ddl m Z ddlmZmZmZmZmZmZmZmZmZgdZej !dd Z"e#e$ze%d<ej !d d Z&e"e&d Z'eZ(ee%d <e(e j)zZ)ee%d<dZ*de(deddfdZ+de(defdZ, dLdd d dde)dededdzde$dzdedzde$de$de(fdZ-ddde(dedzde(fd Z.d!d!d!d!d"d#Z/d$Z0d!d!d!d!d%dd&d'Z1ddd!d!d!d!d%dd(d)Z2d!d!d!d!d%d!dd*d+Z3dMd-Z4dNd/Z5d0ede#fd1Z6de(dede$fd2Z7dede8e#e8dzfd3Z9dededzfd4Z:ddde(d5e;dedzde(fd6Zdd d;dd<de(d=e;e?e;zdzd>e$d?e;e@zdedzde(f d@ZAddde(dedzde(fdAZBddde(dedzde(fdBZCdCddDdEe(dFe(d=e;dedzde(f dGZDd d ddHdIZEdOdEe(dedzde(fdJZFdKZGdS)Pa6Utility functions to use Python Array API compatible libraries. For the context about the Array API see: https://data-apis.org/array-api/latest/purpose_and_scope.html The SciPy use case of the Array API is described on the following page: https://data-apis.org/array-api/latest/use_cases.html#use-case-scipy N) ModuleType)AnyLiteral TypeAlias)array_api_compat) is_array_api_objsizenumpydeviceis_numpy_namespaceis_cupy_namespaceis_torch_namespaceis_jax_namespaceis_array_api_strict_namespace)_asarrayarray_namespaceassert_almost_equalassert_array_almost_equalget_xp_devicesis_array_api_strict is_complexis_cupyis_jaxis_numpyis_torchSCIPY_ARRAY_API SCIPY_DEVICEscipy_namespace_forxp_assert_closexp_assert_equalxp_assert_lessxp_copy xp_copysign xp_devicexp_moveaxis_to_endxp_ravelxp_realxp_signxp_sizexp_take_along_axisxp_unsupported_param_msgxp_vector_normrFrcpu)rrArray ArrayLikectt|D]}||}ddlm}||rd}t |t |t jjrtdt |t j rtdt |t j t j zrZ|j }t j|t js2t j|t jstd|dt#|s t j|}n#t$rtdwxYw|j }t j|t js4t j|t jsd |d}t||||<|S) aRaise exceptions on known-bad subclasses. The following subclasses are not supported and raise and error: - `numpy.ma.MaskedArray` - `numpy.matrix` - NumPy arrays which do not have a boolean or numerical dtype - Any array-like which is neither array API compatible nor coercible by NumPy - Any array-like which is coerced by NumPy to an unsupported dtype r)issparsezSparse arrays/matrices are not supported by this function. Perhaps one of the `scipy.sparse.linalg` functions would work instead.z8Inputs of type `numpy.ma.MaskedArray` are not supported.z0Inputs of type `numpy.matrix` are not supported.zAn argument has dtype `z3`; only boolean and numerical dtypes are supported.zCAn argument is neither array API compatible nor coercible by NumPy.z1An argument was coerced to an unsupported dtype `)rangelen scipy.sparser1 ValueError isinstancenpma MaskedArray TypeErrormatrixndarraygenericdtype issubdtypenumberbool_r asanyarray)arraysiarrayr1msgr>messages U/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/scipy/_lib/_array_api.py_compliance_scipyrI9s3v;;  !!q )))))) 8E?? ")CS// ! eRU. / / PVWW W ry ) ) PNOO O eRZ"*4 5 5 KEM%33 Ur}UBH7U7U U!T%!T!T!TUUU!%((  7 e,, 7 7 7!6777 7KEM%33 )r}UBH7U7U )HHHH (((F1I Ms 2EE!rExpreturncd} |||st|dS#t$rt|wxYw)zCheck for NaNs or Infs.z#array must not contain infs or NaNsN)allisfiniter5r:)rErJrFs rH _check_finiterOhsi /Cvvbkk%(()) "S// ! " " oos 7=ArCc|tdstSd|D}t|}tj|S)a1Get the array API compatible namespace for the arrays xs. Parameters ---------- *arrays : sequence of array_like Arrays used to infer the common namespace. Returns ------- namespace : module Common namespace. Notes ----- Thin wrapper around `array_api_compat.array_namespace`. 1. Check for the global switch: SCIPY_ARRAY_API. This can also be accessed dynamically through ``_GLOBAL_CONFIG['SCIPY_ARRAY_API']``. 2. `_compliance_scipy` raise exceptions on known-bad subclasses. See its definition for more details. When the global switch is False, it defaults to the `numpy` namespace. In that case, there is no compliance check. This is a convenience to ease the adoption. Otherwise, arrays must comply with the new rules. rcg|]}||SN).0rEs rH z#array_namespace..s>>>E,=u,=,=,=)_GLOBAL_CONFIG np_compatrIrr)rC_arrayss rHrrrsF4 + ,>>&>>>G((G  +W 55rV)rJ check_finitesubokr>order)KACFcopyrZr[c|t|}t|rO|durtj||||}n|rtj|||}n|tj|||}nd ||||}nJ#t $r=t|d}||||}YnwxYw|rt|||S)a`SciPy-specific replacement for `np.asarray` with `order`, `check_finite`, and `subok`. Memory layout parameter `order` is not exposed in the Array API standard. `order` is only enforced if the input array implementation is NumPy based, otherwise `order` is just silently ignored. `check_finite` is also not a keyword in the array API standard; included here for convenience rather than that having to be a separate function call inside SciPy functions. `subok` is included to allow this function to preserve the behaviour of `np.asanyarray` for NumPy based inputs. NT)r\r>r[)r\r>)r>ra)rrr7rErBasarrayr:rO)rEr>r\rarJrZr[ coerced_xps rHrrs0 z U # #|| F 4<<HU%uEJJJEE  @M%uEBBBEEJuE???EE FJJuEJ==EE F F F(A77J&&uE&EEEEE F!eR   Ls1B ACCrJxcH|t|}t|d|S)a3 Copies an array. Parameters ---------- x : array xp : array_namespace Returns ------- copy : array Copied array Notes ----- This copy function does not offer all the semantics of `np.copy`, i.e. the `subok` and `order` keywords are not used. NT)rarJ)rrrgrJs rHr"r"s+, z Q   ADR ( ( ((rVTcheck_namespace check_dtype check_shapecheck_0dcd}|rt||t|r|rdt|dt|}||r||s4||s||r J|||}||}|r,d|jd|j}|j|jks J||r,d|jd|j}|j|jks J||||j}||fS)NTz$Array-ness does not match: Actual: z Desired: zdtypes do not match. Actual: Desired: zShapes do not match. Actual: )_assert_matching_namespacertypeisscalarrdr>shape broadcast_to) actualdesiredrJrkrlrmrn__tracebackhide___msgs rH _strict_checkrzs4"67333||QQ=<<==-1']]==V$$ QW)=)= Q F++ Q46KK4H4H Q QLP Q Q QZZ  Fjj!!G3X XXXX|w},,,d,,,3X XXXX|w},,,d,,,oogv|44G 7?rVcd}t|tr|n|f}t|}|D]3}t|}d|jd|j}||ks J|4dS)NTz!Namespaces do not match. Actual: rp)r6tupler__name__)rvrwrx desired_spacearr arr_spacerys rHrqrqs!&%00 ?VVviF#G,,M00#C(( 5$-55)255M)))4)))) 00rV)rkrlrmrnerr_msgrJc jd}|t|}t|||||||\}}t|r|j|||St |r+|dkrdn|}|j||dddd|Stj|||S)NTrj)rrrFrtolatol equal_nanrlrF)rrzrtestingassert_array_equalr assert_closer7) rvrwrkrlrmrnrrJrxs rHr r s z V $ $#_[OFG r{{Gz,,VWg,NNN "G"R--$$Wz&&vwQQRV38g'GG G : ( (' ( J JJrV)rrrkrlrmrnrrJc d} | t|} t||| ||||\}}| |jd} |(| r&| |jjdzdz}n|d}t | r| j|||||St| r+|dkrdn|}| j ||||dd | Stj|||||S) NTrj) real floatingcomplex floating?gHz>)rrrrFr) rrzisdtyper>finfoepsrrassert_allcloserrr7) rvrwrrrkrlrmrnrrJrxfloatings rHrr$sP z V $ $#'[(OFG zz&,(MNNH ||xx %%)3.2 r{{Wz))&'/3W*FF F "W!R--$$Wz&&vwT155g'WW W : % %fgD+/ & B BBrV)rkrlrmrnrverboserJc d} |t|}t|||||||\}}t|r|j||||St |rH|jjdkr|}|jjdkr|}tj||||S)NTrj)rrr-) rrzrrassert_array_lessrr rrr-r7) rvrwrkrlrmrnrrrJrxs rHr!r!Fs z V $ $#_[OFG r{{$z++FG4;W,NN N "$ =  & &ZZ\\F > % ' 'kkmmG : ' '07 ( J JJrVcDddd| zz}}t||g|R||ddd|SzPBackwards compatible replacement. In new code, use xp_assert_close instead. rg? F)rrrlrmrrvrwdecimalargskwdsrrs rHrr_WCgX&$D 67 *  * * $4UPU * *$( * **rVcDddd| zz}}t||g|R||ddd|Srrrs rHrrhrrVparamcd|dS)Nz Providing z$ is only supported for numpy arrays.rS)rs rHr+r+qs E E E EErVc8||jdSNr)rr>ris rHrrus ::ag1 2 22rVcg}t|re|dgz }ddl}|j}t d|D] }|d|gz } |jjr|dgz }|St|r@ddl }|jj }t d|D] }|d|gz } |St|rddl }|d}t d|D] }|d|gz } |d}t d|D] }|d |gz } |d } t d| D] }|d |gz } |SdgS) z  * * , ,  w G  9$3355q(## % %A   } $GG   ""5"11q'"" $ $A  q | #GG""5"11q'"" $ $A  q | #GG""5"11q'"" $ $A  q | #GG 6MrVct|r ddl}|jSt|r ddl}|jSt |r|SdS)aReturn the `scipy`-like namespace of a non-NumPy backend That is, return the namespace corresponding with backend `xp` that contains `scipy` sub-namespaces like `linalg` and `special`. If no such namespace exists, return ``None``. Useful for dispatching. rN)rcupyxscipyrrr)rJrrs rHrrsZr{{ { bzz y|| 4rVsourcec|t|n|}tt|j}||}||gz}|||SrR)rlistr2ndimpop permute_dims)rgrrJaxestemps rHr%r%s_ !#    B af  D 88F  D 4&=D ??1d # ##rVx1x2c|t||n|}||}||dk|| S)Nr)rabswhere)rrrJabs_x1s rHr#r#sE$&JR BB VVBZZF 88B!GVfW - --rVc|t|n|}t|r||S||}|d|j}||dk||}||dk| |}||||j|z|}|S)Nr>r) rrsign zeros_likerdr>risnannan)rgrJrones rHr(r(s!z   rB||wwqzz ==  D **Qag* & &C 88AE3 % %D 88AEC4 & &D 88BHHQKKT 2 2D KrV)axiskeepdimsordrJrrrcd|t|n|}trtt|dr|j||||S|dkrt d||||z||dzStj ||||S)Nlinalg)rrrrzonly the Euclidean norm (`ord=2`) is currently supported in `xp_vector_norm` for backends not implementing the `linalg` extension.)rrr)rrr) rrhasattrr vector_normr5sumconjr7norm)rgrrrrJs rHr,r,s "z   rBH 2x M9((c(RR Raxx !66"''!**q.th6GGL Ly~~aSth~GGGrVcT|t|n|}||dS)N))rreshaperis rHr&r&s. "z   rB ::a  rVc|t|n|}||jdr||n|Sr)rrr>realris rHr'r'sD "z   rBAG-?@@ G2771:::aGrVr)rrJrindicesc|t|n|}t|r||||St|rt d||||S)N)dimz2Array API standard does not define take_along_axis)rrtake_along_dimrNotImplementedErrortake_along_axis)rrrrJs rHr*r*sz "$   B||6  g4 888 R 6!"VWWW!!#w555rV)ensure_writeableforce_floatingrJc` t|nd|D}d|D}dj}d|D} j|}|r,|dr||}n?#t $r2fd|D}|rjg||R}n|r|}n j|}YnwxYwd|D} t | dkrtj| n |d j } n$#t$r} d } t| | d} ~ wwxYwg} |D]}|| ||j | kr$trd d ini}j || fi|}|j|ks|r||d }| || S)Nc8g|]}|t|dn|S)NT)r[)rrTargs rHrUz(xp_broadcast_promote..s. T T T#/Xc & & & &s T T TrVcg|]}||SrRrSrs rHrUz(xp_broadcast_promote..s<<. 1 1 1Cci 1 1 1rVintegralc@g|]}|d|S)r)r)rTr>rJs rHrUz(xp_broadcast_promote..!s;>>>%!zz%<<>>>>rVch|] }|j SrS)rtrs rH z'xp_broadcast_promote..+rrVrrz/Array shapes are incompatible for broadcasting.r[T)ra)rrdr> result_typerr:r3r7broadcast_shapesrtr5appendrruastype)rrrJr args_not_none default_floatdtypesr> float_dtypesshapesrterGoutrkwargss ` rHxp_broadcast_promoters_#%:$  2B T Tt T T TD<>>>6>>>  ,"BN@L@-@@@EE  ,!EE"BNF+E,2 1= 1 1 1F)14V1A1A$f--#A&,  )))C!!q() C ; JJsOOO  9  (0 rfloat32r complex64 complex128)rrJ arr_dtypes rHxp_float_to_complexr Hs!#   B I zz)RZ((,iiR\** I / /,iiR]++ JrVcVt|r|S|jS)z@Query the namespace-dependent default floating-point dtype. )rget_default_dtypefloat64rfs rHxp_default_dtyper Vs.||##%%%zrV)NNN)r)rrR)H__doc__ostypesrtypingrrrr r7 numpy.typingnpt scipy._librscipy._lib.array_api_compatrr r)rXr r$r rr rrrrrrr__all__environgetrstrbool__annotations__rrWr.r/rIrOrrr"rzrqr rr!rrr+rrrrintr%r#r(r|floatr,r&r'r*rr r rSrVrHrs **********''''''                         !jnn->FFtFFFz~~ne44 '  ys}, 9,,,,,,^J4"6U"6z"6"6"6"6N48 , !%",,,,,)*T1,Tk ,   ,,, ,,,,^26)))u)Z$.)%)))):#'Dd< 0 0 09=$ $tRDKKKKK0.24 $$4BBBBBD8<#dBQUJJJJJ2********FCFCFFFF3%3Z3D3333!z!d3i$t*&<!!!!HJ:+<8!% $ $ $  $ $   $*/ $ $ $ $EI...E.u. T0A.U....59   u  T 1 U    48$)&'+/ HHHeHuSz)D0H!He H"D( H5: HHHH46:    d!2 e    59HHHuH T 1HUHHHH$&/3 6 6 6E 6 % 6  6&, 69> 6 6 6 6 27uQU44444n  U  T(9 U    rV