+
    NV-jè-  ã                  óØ  a € 0 t $ R t^ RIHt ^ RIHtHtHtHtH	t	 ^ RI
t^ RI
Ht ^ RIHtHt ^ RIHt ^ RIHtHtHt ]'       d   ^ RIHtHt ]! R	]R4      t ! R
 R4      tRR/t]! ]RR^R7      t]! ]RR^R7      tR R ltR R ltR R lt / t!R]"R&   RX]!R&   R]!R&   R]!R&   R]!R&   R]!R&   ]! ]!R^ RR7      t#/ t$R ]"R!&   RX]$R&   R]$R&   R]$R&   ]! ]$R^ RR7      t%R" R# lt&RR/t'R$]"R%&   ]! ]'R&R^R7      t(]	R' R( l4       t)]	R) R* l4       t)R+ R, lt)/ t*R$]"R-&   R]*R.&   R]*R&   ]! ]*R^R/7      t+]! ]*R0R^R7      t,R1 R2 lt-/ t.R3]"R4&   R].R.&   R].R&   R5].R6&   R].R&   ]! ].R7R^R7      t/]! ].R8R^R7      t0RRR6R5/t1]! ]1R9R:7      t2RRR.RRRR6R5/t3]! ]3R;R^R7      t4]! ]3R<R^R7      t5RR/t6R$]"R=&   ]! ]6R>R^R7      t7RR/t8R$]"R?&   ]! ]8R@R^R7      t9/ t:RA]"RB&   R]:R.&   R]:R&   ]:Pw                  4       t<R]<R&   R5]<R6&   R]<RC&   ]<Pw                  4       t=]<Pw                  4       t>]:Pw                  4       t?R5]?RD&   R5]?R6&   R5]:R6&   ]! ]:R9R:7      t@]! ]<RER^R7      tA]! ]=RFR^R7      tB]! ]>RGR^R7      tC]! ]?RHR^R7      tD/ tER3]"RI&   R]ER.&   R]ER&   R5]ER6&   ]! ]ER9R:7      tF/ tGRJ]"RK&   R]GR&   RL]GRM&   ]! ]GRNR9RO7      tHRPR/tI]! ]IRQR^ R7      tJRYRR RS lltKRZRT RU lltLRH]DRG]CR;]4R<]5RE]ARF]B/tMRV RW ltNR# )[a´  
For compatibility with numpy libraries, pandas functions or methods have to
accept '*args' and '**kwargs' parameters to accommodate numpy arguments that
are not actually used or respected in the pandas implementation.

To ensure that users do not abuse these parameters, validation is performed in
'validators.py' to make sure that any extra parameters passed correspond ONLY
to those in the numpy signature. Part of that validation includes whether or
not the user attempted to pass in non-default values for these extraneous
parameters. As we want to discourage users from relying on these parameters
when calling the pandas implementation, we want them only to pass in the
default values for these parameters.

This module provides a set of commonly used default arguments for functions and
methods that are spread throughout the codebase. This module will make it
easier to adjust to future upstream changes in the analogous numpy signatures.
)Úannotations)ÚTYPE_CHECKINGÚAnyÚTypeVarÚcastÚoverloadN)Úndarray)Úis_boolÚ
is_integer)ÚUnsupportedFunctionCall)Úvalidate_argsÚvalidate_args_and_kwargsÚvalidate_kwargs)ÚAxisÚAxisIntÚ	AxisNoneTc                  ó6   € ] tR t^4tRR R lltRR R lltRtR# )ÚCompatValidatorNc               ó    € V ^8„  d   QhRRRR/# ©é   Úmethodz
str | NoneÚreturnÚNone© )Úformats   "Úm/Volumes/fast/ai/experiments/ui-tars-smoke/.venv/lib/python3.14/site-packages/pandas/compat/numpy/function.pyÚ__annotate__ÚCompatValidator.__annotate__5   s    € ÷ 
7ñ 
7ð ð	
7ð 
ñ
7ó    c                	ó6   € W n         W0n        Wn        W@n        R # ©N)Úfnamer   ÚdefaultsÚmax_fname_arg_count)Úselfr#   r"   r   r$   s   &&&&&r   Ú__init__ÚCompatValidator.__init__5   s   € ð Œ
ØŒØ ŒØ#6Ö r   c               ó    € V ^8„  d   QhRRRR/# r   r   )r   s   "r   r   r   A   s$   € ÷ Fñ Fð ðFð 
ñFr   c                	ól  € V'       g   V'       g   R # Vf   V P                   MTpVf   V P                  MTpVf   V P                  MTpVR8X  d   \        W1W@P                  4       R # VR8X  d   \        W2V P                  4       R # VR8X  d   \        W1W$V P                  4       R # \        RV R24      h)NÚargsÚkwargsÚbothzinvalid validation method 'Ú')r"   r$   r   r   r#   r   r   Ú
ValueError)r%   r*   r+   r"   r$   r   s   &&&&&&r   Ú__call__ÚCompatValidator.__call__A   s¦   € ÷ ŸFÙà#šm�—
’
°ˆð #Ò*ð ×$Ò$à$ð 	ð
 !'¢�—’°Fˆà�VÔÜ˜%Ð':¿M¹MÖJØ�xÔÜ˜E¨4¯=©=Ö9Ø�vÔÜ$Ø˜V¸$¿-¹-öô Ð:¸6¸(À!ÐDÓEÐEr   )r#   r"   r$   r   )NNN)Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__r&   r/   Ú__static_attributes__r   r   r   r   r   4   s   † ÷
7÷Fó Fr   r   ÚoutÚargminr,   )r"   r   r$   Úargmaxc               ó    € V ^8„  d   QhRRRR/# )r   Úskipnaúbool | ndarray | Noner   ztuple[bool, Any]r   )r   s   "r   r   r   i   s   € ÷ ñ Ð0ð Ð;Kñ r   c                óL   € \        V \        4      '       g   V f	   V .VO5pRp W3# )NT)Ú
isinstancer   )r:   r*   s   &&r   Úprocess_skipnar>   i   s+   € Ü�&œ'×"Ò" f¢nØˆ˜‰ˆØˆàˆ<Ðr   c               ó    € V ^8„  d   QhRRRR/# ©r   r:   r;   r   Úboolr   )r   s   "r   r   r   q   ó   € ÷ 	ñ 	Ð(=ð 	ÐPTñ 	r   c                ó6   € \        W4      w  r\        W4       V # )a	  
If 'Series.argmin' is called via the 'numpy' library, the third parameter
in its signature is 'out', which takes either an ndarray or 'None', so
check if the 'skipna' parameter is either an instance of ndarray or is
None, since 'skipna' itself should be a boolean
)r>   Úvalidate_argmin©r:   r*   r+   s   &&&r   Úvalidate_argmin_with_skipnarF   q   ó   € ô " &Ó/�L€FÜ�DÔ!Ø€Mr   c               ó    € V ^8„  d   QhRRRR/# r@   r   )r   s   "r   r   r   }   rB   r   c                ó6   € \        W4      w  r\        W4       V # )a	  
If 'Series.argmax' is called via the 'numpy' library, the third parameter
in its signature is 'out', which takes either an ndarray or 'None', so
check if the 'skipna' parameter is either an instance of ndarray or is
None, since 'skipna' itself should be a boolean
)r>   Úvalidate_argmaxrE   s   &&&r   Úvalidate_argmax_with_skipnarK   }   rG   r   zdict[str, int | str | None]ÚARGSORT_DEFAULTSÚaxisÚ	quicksortÚkindÚorderÚstableÚargsort)r"   r$   r   zdict[str, int | None]ÚARGSORT_DEFAULTS_KINDc               ó    € V ^8„  d   QhRRRR/# )r   Ú	ascendingzbool | int | Noner   rA   r   )r   s   "r   r   r       s   € ÷ ñ Ð/@ð ÐSWñ r   c                óz   € \        V 4      '       g   V f	   V .VO5pRp \        W^R7       \        \        V 4      p V # )a  
If 'Categorical.argsort' is called via the 'numpy' library, the first
parameter in its signature is 'axis', which takes either an integer or
'None', so check if the 'ascending' parameter has either integer type or is
None, since 'ascending' itself should be a boolean
T)r$   )r
   Úvalidate_argsort_kindr   rA   )rU   r*   r+   s   &&&r   Úvalidate_argsort_with_ascendingrX       sB   € ô �)×Ò 	Ò 1ØÐ!˜DÑ!ˆØˆ	ä˜$¸AÕ>Ü”T˜9Ó%€IØÐr   zdict[str, Any]ÚCLIP_DEFAULTSÚclipc               ó    € V ^8„  d   QhRRRR/# )r   rM   r   r   r   r   )r   s   "r   r   r   ·   s   € × EÑ E 'Ð E¸DÑ Er   c                ó   € R # r!   r   ©rM   r*   r+   s   &&&r   Úvalidate_clip_with_axisr^   ¶   s   € ÙBEr   c               ó    € V ^8„  d   QhRRRR/# )r   rM   r   r   r   )r   s   "r   r   r   »   s   € × LÑ L )Ð L¸iÑ Lr   c                ó   € R # r!   r   r]   s   &&&r   r^   r^   º   s   € ÙILr   c               ó    € V ^8„  d   QhRRRR/# )r   rM   zndarray | AxisNoneTr   zAxisNoneT | Noner   )r   s   "r   r   r   ¾   s   € ÷ ñ Ø
ðàñr   c                óX   € \        V \        4      '       d	   V .VO5pRp \        W4       V # )zó
If 'NDFrame.clip' is called via the numpy library, the third parameter in
its signature is 'out', which can takes an ndarray, so check if the 'axis'
parameter is an instance of ndarray, since 'axis' itself should either be
an integer or None
N)r=   r   Úvalidate_clipr]   s   &&&r   r^   r^   ¾   s2   € ô �$œ× Ò Øˆ}�t‰}ˆð ˆä�$Ôð €Kr   ÚCUM_FUNC_DEFAULTSÚdtype)r   r$   Úcumsumc               ó    € V ^8„  d   QhRRRR/# )r   r:   rA   r   r   )r   s   "r   r   r   Þ   s   € ÷ ñ ¨$ð Àtñ r   c                óª   € \        V 4      '       g
   V .VO5pRp M+\        V \        P                  4      '       d   \	        V 4      p \        WVR7       V # )zË
If this function is called via the 'numpy' library, the third parameter in
its signature is 'dtype', which takes either a 'numpy' dtype or 'None', so
check if the 'skipna' parameter is a boolean or not
T©r"   )r	   r=   ÚnpÚbool_rA   Úvalidate_cum_func)r:   r*   r+   Únames   &&&&r   Úvalidate_cum_func_with_skipnarn   Þ   sF   € ô �6�?Š?Øˆ˜‰ˆØ‰Ü	�FœBŸH™H×	%Ò	%Ü�f“ˆä�d¨$Õ/Ø€Mr   zdict[str, bool | None]ÚALLANY_DEFAULTSFÚkeepdimsÚallÚanyr+   )r   ÚminÚmaxÚREPEAT_DEFAULTSÚrepeatÚROUND_DEFAULTSÚroundzdict[str, Any | None]ÚSTAT_FUNC_DEFAULTSÚinitialÚoverwrite_inputÚsumÚprodÚmeanÚmedianÚSTAT_DDOF_FUNC_DEFAULTSzdict[str, str | None]ÚTAKE_DEFAULTSÚraiseÚmodeÚtake)r"   r   ÚaxesÚ	transposec               ó    € V ^8„  d   QhRRRR/# )r   rm   Ústrr   r   r   )r   s   "r   r   r   C  s   € ÷ 
ñ 
 ð 
ÀDñ 
r   c                ó¦   € Vf   . p\        V4      \        V4      ,
          p\        V4      \        V4      ,           ^ 8”  d   \        RV  R24      hR# )zš
'args' and 'kwargs' should be empty, except for allowed kwargs because all
of their necessary parameters are explicitly listed in the function
signature
Nz?numpy operations are not valid with groupby. Use .groupby(...).z
() instead)ÚsetÚlenr   )rm   r*   r+   Úalloweds   &&&&r   Úvalidate_groupby_funcr�   C  sX   € ð ‚Øˆä�‹[œ3˜w›<Õ'€Fä
ˆ4ƒy”3�v“;Õ Ô"Ü%ð!Ø!%  jð2ó
ð 	
ñ #r   c               ó$   € V ^8„  d   QhRRRRRR/# )r   rM   zAxisInt | NoneÚndimÚintr   r   r   )r   s   "r   r   r   U  s&   € ÷ Yñ Y˜~ð Y°Sð YÀñ Yr   c                óh   € V f   R# W8¼  g   V ^ 8  d   W,           ^ 8  d   \        RV R24      hR# R# )zÝ
Ensure that the axis argument passed to min, max, argmin, or argmax is zero
or None, as otherwise it will be incorrectly ignored.

Parameters
----------
axis : int or None
ndim : int, default 1

Raises
------
ValueError
Nz4`axis` must be fewer than the number of dimensions (Ú))r.   )rM   r�   s   &&r   Úvalidate_minmax_axisr“   U  s=   € ð ‚|ÙØ„|˜˜qœ T¥[°1¤_ÜÐOÐPTÈvÐUVÐWÓXÐXñ &5™r   c               ó   € V ^8„  d   QhRR/# )r   r   r   r   )r   s   "r   r   r   s  s   € ÷ )ñ )¨$ñ )r   c                ó\   € V \         9  d   \        WV R 7      # \         V ,          pV! W4      # )ri   )Ú_validation_funcsÚvalidate_stat_func)r"   r*   r+   Úvalidation_funcs   &&& r   Úvalidate_funcr™   s  s-   € ØÔ%Ô%Ü! $°eÔ<Ð<ä'¨Õ.€OÙ˜4Ó(Ð(r   éÿÿÿÿr!   )é   )OÚ__conditional_annotations__Ú__doc__Ú
__future__r   Útypingr   r   r   r   r   Únumpyrj   r   Úpandas._libs.libr	   r
   Úpandas.errorsr   Úpandas.util._validatorsr   r   r   Úpandas._typingr   r   r   r   ÚARGMINMAX_DEFAULTSrD   rJ   r>   rF   rK   rL   Ú__annotations__Úvalidate_argsortrS   rW   rX   rY   rc   r^   rd   rl   Úvalidate_cumsumrn   ro   Úvalidate_allÚvalidate_anyÚLOGICAL_FUNC_DEFAULTSÚvalidate_logical_funcÚMINMAX_DEFAULTSÚvalidate_minÚvalidate_maxru   Úvalidate_repeatrw   Úvalidate_roundry   ÚcopyÚSUM_DEFAULTSÚPROD_DEFAULTSÚMEAN_DEFAULTSÚMEDIAN_DEFAULTSr—   Úvalidate_sumÚvalidate_prodÚvalidate_meanÚvalidate_medianr€   Úvalidate_stat_ddof_funcr�   Úvalidate_takeÚTRANSPOSE_DEFAULTSÚvalidate_transposer�   r“   r–   r™   )rœ   s   @r   Ú<module>r¿      s–  øðôõ$ #÷õ ó Ý ÷õ 2÷ñ ÷ ÷ñ
 ˜ T¨4Ó0€I÷)Fñ )FðX ˜T�]Ð Ù!Ø˜h¨vÈ1ô€ñ "Ø˜h¨vÈ1ô€õ
õ	õ	ð 13Ð Ð-Ó 2ØÐ �Ñ Ø&Ð �Ñ Ø Ð �Ñ ØÐ �Ñ Ø!Ð �Ñ ñ #Ø˜I¸1ÀVôÐ ð 02Ð Ð,Ó 1Ø "Ð �fÑ Ø!%Ð �gÑ Ø"&Ð �hÑ Ù'Ø ÀÈ&ôÐ õ
ð  "'¨ €ˆ~Ó -ÙØ˜¨ÀAô€ð
 
Ü Eó 
Ø Eð 
Ü Ló 
Ø Lõð* %'Ð �>Ó &Ø!Ð �'Ñ ØÐ �%Ñ Ù#Ø˜f¸!ôÐ ñ "Ø˜X¨fÈ!ô€õ
ð  +-€Ð'Ó ,Ø€�Ñ Ø€�Ñ Ø#€�
Ñ Ø€�Ñ ÙØ˜5¨ÀQô€ñ Ø˜5¨ÀQô€ð   j°%Ð8Ð Ù'Ð(=ÀhÔOÐ à˜4 ¨$°°t¸ZÈÐO€ÙØ˜5¨ÀQô€ñ Ø˜5¨ÀQô€ð
 $*¨4 .€�Ó 0Ù!Ø˜8¨FÈô€ð #(¨ €�Ó .Ù Ø˜'¨&Àaô€ð -/Ð Ð)Ó .Ø"Ð �7Ñ Ø Ð �5Ñ à!×&Ñ&Ó(€Ø€ˆVÑ Ø €ˆZÑ Ø€ˆYÑ à×!Ñ!Ó#€à×!Ñ!Ó#€à$×)Ñ)Ó+€Ø%*€Ð!Ñ "Ø#€�
Ñ à!&Ð �:Ñ á$Ð%7ÀÔIÐ ÙØ˜ fÀ!ô€ñ  Ø˜¨ÀAô€ñ  Ø˜¨ÀAô€ñ "Ø˜8¨FÈô€ð 35Ð Ð/Ó 4Ø#'Ð ˜Ñ  Ø!%Ð ˜Ñ Ø&+Ð ˜
Ñ #Ù)Ð*AÈ(ÔSÐ à')€Ð$Ó )Ø€ˆeÑ Ø€ˆfÑ Ù °VÀHÔM€ð ˜d�^Ð Ù$Ø˜k°&ÈaôÐ ÷

÷$Yð* ˆoØ
ˆMØ	ˆ<Ø	ˆ<Ø	ˆ<Ø
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