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Convert one of the arguments to a NumPy array (eg 'ufunc(df1, np.asarray(df2)') to keep the current behaviour, or align manually (eg 'df1, df2 = df1.align(df2)') before passing to the ufunc to obtain the future behaviour and silence this warning. stacklevel)rdrcpandas.core.genericrsrnextwarningswarn FutureWarningrappendrenpasarraygetattrr) rlrnrprq n_alignablen_frames non_aligned new_inputsrxr)rcrsr}r_maybe_fallbacks0    rcsTddlmddlmt}tdi|}tg|Ri|}|tur)|Stg|Ri|}|tur<|St j j |j f}|D](}t |doQ|j j k} t |dodt|j |vodt|j } | si| rmtSqEtdd|D} fdd t|| Dtd krtt| d krtd j} d d D]} tt| | jD] \}\}}||| |<qqttj| tfd dt|| D}n ttjjjd krdd |D}tt|d kr|dnd }d|inifdd}fddd|vr%tg|Ri|}||Sdkr>tg|Ri|}|tur>|Sjd kret|d ksQjd kretdd|D}t|i|}n?jd krtdd|D}t|i|}n%dkr|s|dj }|!t}nt"|dg|Ri|}||}|S)z Compatibility with numpy ufuncs. See also -------- numpy.org/doc/stable/reference/arrays.classes.html#numpy.class.__array_ufunc__ rrr) BlockManager__array_priority____array_ufunc__css|]}t|VqdSr)typervrrrry!zarray_ufunc..csg|] \}}t|r|qSr) issubclassrwrxtrrrr "szarray_ufunc..r|z;Cannot apply ufunc {} to mixed DataFrame and Series inputs.Nc3s2|]\}}t|r|jdin|VqdS)Nr)rreindexr)rsreconstruct_axesrrry:s  cSs g|] }t|drt|dqS)name)hasattrrrvrrrrBs rcs(jdkrtfdd|DS|S)Nr|c3s|]}|VqdSrrrv) _reconstructrrryKrz3array_ufunc..reconstruct..)nouttuple)result)rrlrr reconstructHs z array_ufunc..reconstructcst|r|S|jjkr*dkr(jdkr&d}tj|ttd|St|St |r=j |fiddi}nj |fiddi}t dkrW| }|S)Nouterr{zouter method for ufunc {} is not implemented on pandas objects. Returning an ndarray, but in the future this will raise a 'NotImplementedError'. Consider explicitly converting the DataFrame to an array with '.to_numpy()' first.r~copyFr|) r is_scalarndimrrformatrrNotImplementedErrorre _constructorlen __finalize__)rmsg)r alignablernrreconstruct_kwargsrrlrrrOs6      z!array_ufunc.._reconstructoutreducecss|]}t|VqdSrrrrvrrrryrzcss|] }t|ddVqdS)T) extract_numpyNr rvrrrrys__call__r)#rrspandas.core.internalsrr_standardize_out_kwargrrrrndarrayrrrre_HANDLED_TYPESrziprsetrraxes enumerateuniondict _AXIS_ORDERSrdispatch_ufunc_with_outdispatch_reduction_ufuncrr_mgrapplydefault_array_ufunc)rrlrnrprqclsrno_deferitemhigher_priorityhas_array_ufunctypesrobjiax1ax2namesrrmgrr) rrsrrrnrrrrlr array_ufuncs            %  &   rreturnrcKs@d|vrd|vrd|vr|d}|d}||f}||d<|S)z If kwargs contain "out1" and "out2", replace that with a tuple "out" np.divmod, np.modf, np.frexp can have either `out=(out1, out2)` or `out1=out1, out2=out2)` rout1out2)pop)rqrrrrrrrs   rc Os|d}|dd}t|||i|}|turtSt|trAt|tr-t|t|kr/tt||D] \}} t|| |q4|St|trSt|dkrQ|d}ntt||||S)zz If we have an `out` keyword, then call the ufunc without `out` and then set the result into the given `out`. rwhereNr|r) rrrrerrrr _assign_where) rrlrnrprqrrrarrresrrrrs"       rNonecCs*|dur ||dd<dSt|||dS)zV Set a ufunc result into 'out', masking with a 'where' argument if necessary. N)rputmask)rrrrrrrsrcs@tfdd|Ds tfdd|D}t|||i|S)z Fallback to the behavior we would get if we did not define __array_ufunc__. Notes ----- We are assuming that `self` is among `inputs`. c3s|]}|uVqdSrrrvrrrryrz&default_array_ufunc..cs"g|] }|ur |nt|qSrrrvrrrrs"z'default_array_ufunc..)anyrr)rrlrnrprqrrrrrsrcOs|dksJt|dks|d|urtS|jtvrtSt|j}t||s'tS|jdkr=t|tr5d|d<d|vr=d|d<t||d ddi|S) z@ Dispatch ufunc reductions to self's reduction methods. rr|rF numeric_onlyaxisskipnaNr) rrr_REDUCTION_ALIASESrrrerr)rrlrnrprq method_namerrrrs      r)rlrmrnrorprrqr)rr)rlrmrnro)rr)!__doc__ __future__rr#typingrrnumpyr pandas._libsrpandas._libs.ops_dispatchrpandas.util._exceptionsrpandas.core.dtypes.genericr pandas.corerpandas.core.constructionr pandas.core.ops.commonr rrrkrrrrrrrrrrrs:          > 2  #