Ë
    ÷Q(h¶6  ã            	       óò  — d dl Z d dlZd dlZd dlZd dlmZ d dlmZ d dlZd dl	Z	d dl
Z
d dl
mZ d dlmZ d dlmZmZ d dlmZmZ d dlmZ d d	lmZ d d
lmZ d dlmZ d dlmZmZmZm Z m!Z! d dl"m#Z# d dl$m%Z%m&Z&  ejN                  «       5   ejP                  de)«       ejT                  jW                  e
jX                  «      gZ- e. ede-¬«      D � cg c]  } d| d   v sd| d   v s| d   ‘Œ c} «      Z/ddd«       g d¢Z0g d¢Z1d„ Z2d„ Z3d„ Z4d„ Z5e	jl                  jo                  d«      e	jl                  jq                  d e«       «      d„ «       «       Z9d„ Z:e!d„ «       Z;e!d „ «       Z<yc c} w # 1 sw Y   Œ{xY w)!é    N)Ú	signature)Úwalk_packages)Úmetrics)Úmake_classification)ÚStackingClassifierÚStackingRegressor)Úenable_halving_search_cvÚenable_iterative_imputer©ÚLogisticRegression)ÚFunctionTransformer)Úall_estimators)Ú_construct_instances)Ú_get_func_nameÚassert_docstring_consistencyÚcheck_docstring_parametersÚignore_warningsÚskip_if_no_numpydoc)Ú_is_deprecated)Ú_enforce_estimator_tags_XÚ_enforce_estimator_tags_yÚignorezsklearn.)ÚprefixÚpathz._é   z.tests.)z%sklearn.utils.deprecation.load_mlcompzsklearn.pipeline.make_pipelinezsklearn.pipeline.make_unionz%sklearn.utils.extmath.safe_sparse_dotzsklearn.utils._joblibÚHalfBinomialLoss)ÚfitÚscoreÚfit_predictÚfit_transformÚpartial_fitÚpredictc                  ó&  ‡— t        j                  dd¬«       ddlm}  g }t        D �]–  }|j                  d«      rŒ|dk(  rŒt        j                  d¬	«      5  t        j                  |«      }d d d «       t        j                  t        j                  «      }|D �cg c]#  }|d
   j                  j                  d«      sŒ"|‘Œ% }}|D �]8  \  }}g }|t        v s|j                  d«      rŒ#t        j                   |«      rŒ9t        j                  d¬	«      5 }| j#                  |«      }	d d d «       t%        «      rt'        d|›d|›d|d   ›�«      ‚t)        |j*                  «      rŒ¡|t-        |j.                  	«      z  }|	j0                  D ]k  }
t3        ||
«      }t)        |«      rŒd }|
t4        v r5t7        |«      }d|j8                  v r|j8                  d   j:                  €dg}t-        ||¬«      }||z  }Œm ||z  }�Œ; t        j                  |t        j<                  «      }|D �cg c]  }|d
   j                  |k(  sŒ|‘Œ }}|D ]l  \  }}|j                  d«      rŒ|dk(  r|j                  d«      rŒ/t?        |«      ŠtA        ˆfd„t        D «       «      rŒSt)        |«      rŒ_|t-        |«      z  }Œn �Œ™ djC                  |«      }t%        |«      dkD  rtE        d|z   «      ‚y # 1 sw Y   �Œ‚xY wc c}w # 1 sw Y   �Œ×xY wc c}w )NÚnumpydocz+numpydoc is required to test the docstrings)Úreasonr   ©Ú	docscrapez	.conftestzsklearn.utils.fixesT)Úrecordr   ÚsklearnÚ_zError for __init__ of z in z:
Úy)r   ÚconfigurationÚsetupc              3   ó&   •K  — | ]  }|‰v –— Œ
 y ­w)N© )Ú.0ÚdÚname_s     €úe/var/www/skyplay_api_hub/venv/lib/python3.12/site-packages/sklearn/tests/test_docstring_parameters.pyú	<genexpr>z,test_docstring_parameters.<locals>.<genexpr>’   s   øè ø€ Ò> a�q˜E”zÑ>ùs   ƒú
zDocstring Error:
)#ÚpytestÚimportorskipr$   r'   ÚPUBLIC_MODULESÚendswithÚwarningsÚcatch_warningsÚ	importlibÚimport_moduleÚinspectÚ
getmembersÚisclassÚ
__module__Ú
startswithÚ_DOCSTRING_IGNORESÚ
isabstractÚClassDocÚlenÚRuntimeErrorr   Ú__new__r   Ú__init__ÚmethodsÚgetattrÚ_METHODS_IGNORE_NONE_Yr   Ú
parametersÚdefaultÚ
isfunctionr   ÚanyÚjoinÚAssertionError)r'   Ú	incorrectÚnameÚmoduleÚclassesÚclsÚcnameÚthis_incorrectÚwÚcdocÚmethod_nameÚmethodÚparam_ignoreÚsigÚresultÚ	functionsÚfnÚfnameÚfuncÚmsgr2   s                       @r3   Útest_docstring_parametersrf   M   sü  ø€ ô ×ÑØÐHõõ
 #à€IÜó <>ˆØ�=‰=˜Ô%àØÐ(Ò(àÜ×$Ñ$¨DÔ1ñ 	3Ü×,Ñ,¨TÓ2ˆF÷	3ä×$Ñ$ V¬W¯_©_Ó=ˆà")ÖU˜3¨S°©V×->Ñ->×-IÑ-IÈ)Õ-T’3ÐUˆÐUØ!ó !	(‰JˆE�3ØˆNØÔ*Ñ*¨e×.>Ñ.>¸sÔ.CØÜ×!Ñ! #Ô&ØÜ×(Ñ(°Ô5ð /¸Ø ×)Ñ)¨#Ó.�÷/ä�1ŒvÝ"Ú=@Â$ÈÈ!ÊÐMóð ô
 ˜cŸk™kÔ*ØàÔ8¸¿¹ÀtÓLÑLˆNà#Ÿ|™|ò )�Ü   kÓ2�Ü! &Ô)ØØ#�ð Ô"8Ñ8Ü# FÓ+�CØ˜cŸn™nÑ,°·±ÀÑ1D×1LÑ1LÐ1TØ(+ u˜Ü3°FÀ<ÔP�Ø &Ñ(‘ð)ð ˜Ñ'ŠIðC!	(ôF ×&Ñ& v¬w×/AÑ/AÓBˆ	à"+ÖH˜B¨r°!©u×/?Ñ/?À4Ó/G’RÐHˆ	ÐHØ$ò 
	>‰KˆE�4à×Ñ Ô$ØØ˜Ò'¨D¯M©M¸'Ô,BØÜ" 4Ó(ˆEÜÓ>Ô+=Ô>Õ>Ä~ØõHð Ô7¸Ó=Ñ=‘	ò
	>ðe<>ð| �)‰)�IÓ
€CÜ
ˆ9ƒ~˜ÒÜÐ1°CÑ7Ó8Ð8ð ÷q	3ñ 	3üò V÷/ñ /üò> Is0   ÁK/Â#K<ÃK<ÄLÈ/LÉLË/K9	ÌLc                 ó,   —  | t        «       dddgi«      S )NÚCgš™™™™™¹?r   r   )ÚSearchCVs    r3   Ú_construct_searchcv_instancerj   œ   s   € ÙÔ&Ó(¨3°°a°¨/Ó:Ð:ó    c                 óÌ   — | j                   dk(  r | ddddgfg¬«      S | j                   dk(  r | dt        «       fg¬	«      S | j                   d
k(  r | dt        «       fg¬«      S y )NÚColumnTransformerÚtransformerÚpassthroughr   r   )ÚtransformersÚPipelineÚclf)ÚstepsÚFeatureUnion)Útransformer_list)Ú__name__r   r   )Ú	Estimators    r3   Ú$_construct_compose_pipeline_instancerx       sy   € à×ÑÐ0Ò0Ù¨°}ÀqÈ!ÀfÐ'MÐ&NÔOÐOØ	×	Ñ	˜zÒ	)Ù Ô(:Ó(<Ð =Ð>Ô?Ð?Ø	×	Ñ	˜~Ò	-Ù¨MÔ;NÓ;PÐ+QÐ*RÔSÐSð 
.rk   c                 ó|   — t        j                  g d¢g d¢g d¢g d¢g d¢gt         j                  ¬«      } | |¬«      S )N)r   r   r   )éÿÿÿÿrz   é   )r   r   r   )r   r   r   )r   r{   r   )Údtype)Ú
dictionary)ÚnpÚarrayÚfloat64)rw   r}   s     r3   Ú_construct_sparse_coderr�   ª   s2   € ä—‘Ú	’K¢ªI²yÐAÜ�j‰jô€Jñ  
Ô+Ð+rk   z-ignore::sklearn.exceptions.ConvergenceWarningzname, Estimatorc                 ó¢  — t        j                  d«       ddlm} |j	                  |«      }|d   }|j
                  dv rt        |«      }nŠ|j
                  dv rt        |«      }np|j
                  dk(  rt        |«      }nU|j
                  dk(  r2t        d	d
d¬«      \  }} |t        «       j                  ||«      «      }nt        t        |«      «      }|j
                  dk(  r|j                  d¬«       n¡|j
                  dk(  r|j                  d¬«       n|j
                  dk(  s|j
                  j                  d«      r|j                  d¬«       nB|j
                  dv r|j                  d¬«       n!|j
                  dk(  r|j                  d¬«       d|j!                  «       v r3|j                  d¬«       |j
                  dk(  r|j                  d¬«       d|j!                  «       v r|j                  d¬«       i }|j
                  j#                  d«      r/|j
                  dv rg d ¢}n|j
                  d!k(  r
ddd"œd#dd$œg}d }n+t        d	d#ddd¬%«      \  }}t%        ||«      }t'        ||«      }|j)                  «       j*                  j,                  r|j                  |«       n¥|j)                  «       j*                  j.                  r%|j                  t0        j2                  ||f   «       n\|j)                  «       j4                  j6                  r&|j                  t0        j8                  d&f   |«       n|j                  |«       |D ]q  }	|	j:                  |v rŒd'j=                  |	j>                  «      jA                  «       }
d(|
v rŒ@tC        tD        ¬)«      5  tG        ||	j:                  «      sJ ‚	 d d d «       Œs tI        |«      }|D �	cg c]  }	|	j:                  ‘Œ }}	tK        |«      jM                  |«      }tK        |«      jM                  |«      }|rtO        d*|j
                  › d+|› �«      ‚y # 1 sw Y   ŒóxY wc c}	w ),Nr$   r   r&   Ú
Attributes)ÚHalvingRandomSearchCVÚRandomizedSearchCVÚHalvingGridSearchCVÚGridSearchCV)rm   rq   rt   ÚSparseCoderÚFrozenEstimatoré   é   )Ú	n_samplesÚ
n_featuresÚrandom_stateÚSelectKBestr{   )ÚkÚDummyClassifierÚ
stratified)ÚstrategyÚCCAÚPLSr   )Ún_components)ÚGaussianRandomProjectionÚSparseRandomProjectionÚTSNE)Ú
perplexityÚmax_iter)r›   éú   rŽ   )rŽ   Ú
Vectorizer)ÚCountVectorizerÚHashingVectorizerÚTfidfVectorizer)zThis is the first document.z%This document is the second document.zAnd this is the third one.zIs this the first document?ÚDictVectorizer)ÚfooÚbaré   )r¢   Úbaz)rŒ   r�   Ún_redundantÚ	n_classesrŽ   .ú zonly ©ÚcategoryzUndocumented attributes for z: )(r6   r7   r$   r'   rE   rv   rj   rx   r�   r   r   r   Únextr   Ú
set_paramsrB   Ú
get_paramsr9   r   r   Ú__sklearn_tags__Útarget_tagsÚone_d_labelsÚtwo_d_labelsr~   Úc_Ú
input_tagsÚthree_d_arrayÚnewaxisrT   rQ   ÚdescÚlowerr   ÚFutureWarningÚhasattrÚ_get_all_fitted_attributesÚsetÚ
differencerR   )rT   rw   r'   ÚdocÚ
attributesÚestÚXr+   Úskipped_attributesÚattrr¶   Úfit_attrÚfit_attr_namesÚundocumented_attrss                 r3   Útest_fit_docstring_attributesrÆ   ³   sú  € ô ×Ñ˜
Ô#Ý"à
×
Ñ
˜YÓ
'€CØ�\Ñ"€Jà×Ñð ñ ô +¨9Ó5‰Ø	×	Ñ	ð  ñ 
ô
 3°9Ó=‰Ø	×	Ñ	˜}Ò	,Ü% iÓ0‰Ø	×	Ñ	Ð0Ò	0Ü"¨R¸AÈAÔN‰ˆˆ1ÙÔ*Ó,×0Ñ0°°AÓ6Ó7‰ô Ô'¨	Ó2Ó3ˆà×Ñ˜]Ò*Ø�‰˜ˆÕØ	×	Ñ	Ð0Ò	0Ø�‰ ˆÕ-Ø	×	Ñ	˜uÒ	$¨	×(:Ñ(:×(EÑ(EÀeÔ(Là�‰ AˆÕ&Ø	×	Ñ	ð  ñ 
ð
 	�‰ AˆÕ&Ø	×	Ñ	˜vÒ	%à�‰ !ˆÔ$ð �S—^‘^Ó%Ñ%Ø�‰ ˆÔ"à×Ñ Ò'Ø�N‰N CˆNÔ(à˜Ÿ™Ó)Ñ)Ø�‰ AˆÔ&ð Ðà×Ñ×"Ñ" <Ô0à×Ñð "
ñ 
ò
‰Að ×ÑÐ#3Ò3Ø 1Ñ%¨q¸Ñ';Ð<ˆAØ‰ä"ØØØØØô
‰ˆˆ1ô & c¨1Ó-ˆÜ% c¨1Ó-ˆà
×ÑÓ×)Ñ)×6Ò6Ø�‰��
Ø	×	Ñ	Ó	×	+Ñ	+×	8Ò	8Ø�‰”—‘�a˜�d‘ÕØ	×	Ñ	Ó	×	*Ñ	*×	8Ò	8Ø�‰�”"—*‘*˜c�/Ñ" AÕ&à�‰��1Œàò +ˆØ�9‰9Ð*Ñ*ØØ�x‰x˜Ÿ	™	Ó"×(Ñ(Ó*ˆð �d‰?Øä¤mÔ4ñ 	+Ü˜3 §	¡	Ô*Ð*Ñ*÷	+ð 	+ð+ô *¨#Ó.€HØ,6Ö7 D�d—i“iÐ7€NÐ7Ü˜X›×1Ñ1°.ÓAÐÜÐ/Ó0×;Ñ;Ð<NÓOÐÙÜØ*¨9×+=Ñ+=Ð*>¸bÐASÐ@TÐUó
ð 	
ð ÷	+ð 	+üò 8s   Î&Q ÏQÑ Q		c                 ó,  — t        | j                  j                  «       «      }t        j                  «       5  t        j
                  dt        ¬«       t        | j                  «      D ]G  }t        | j                  |«      }t        |t        «      sŒ*	 t        | |«       |j                  |«       ŒI 	 ddd«       |D �cg c](  }|j                  d«      sŒ|j                  d«      rŒ'|‘Œ* c}S # t        t        f$ r Y Œ˜w xY w# 1 sw Y   ŒRxY wc c}w )zBGet all the fitted attributes of an estimator including propertiesÚerrorr©   Nr*   )ÚlistÚ__dict__Úkeysr:   r;   Úfilterwarningsr¸   ÚdirÚ	__class__rK   Ú
isinstanceÚpropertyÚAttributeErrorÚappendr9   rB   )Ú	estimatorrÃ   rT   Úobjr�   s        r3   rº   rº   .  sì   € ô �I×&Ñ&×+Ñ+Ó-Ó.€Hô 
×	 Ñ	 Ó	"ñ "Ü×Ñ ´-Õ@ä˜	×+Ñ+Ó,ò 	"ˆDÜ˜)×-Ñ-¨tÓ4ˆCÜ˜c¤8Ô,ØðÜ˜	 4Ô(ð �O‰O˜DÕ!ñ	"÷"ð   ÖM�! 1§:¡:¨c¥?¸1¿<¹<ÈÕ;LŠAÒMÐMøô	 #¤MÐ2ò Ùðú÷"ð "üò  NsB   ¸ADÂC0Â DÃ DÃDÃ)DÃ0DÃ?DÄDÄDÄDc                  ó  — t         j                  t         j                  t         j                  t         j                  t         j
                  g} t        | dddg¬«       d}t        | dgdj                  |j                  «       «      ¬«       y)	z>Check docstrings parameters of related metrics are consistent.TÚaverageÚzero_division)Úinclude_paramsÚexclude_paramsaß  This parameter is required for multiclass/multilabel targets\.
        If ``None``, the metrics for each class are returned\. Otherwise, this
        determines the type of averaging performed on the data:
        ``'binary'``:
            Only report results for the class specified by ``pos_label``\.
            This is applicable only if targets \(``y_\{true,pred\}``\) are binary\.
        ``'micro'``:
            Calculate metrics globally by counting the total true positives,
            false negatives and false positives\.
        ``'macro'``:
            Calculate metrics for each label, and find their unweighted
            mean\.  This does not take label imbalance into account\.
        ``'weighted'``:
            Calculate metrics for each label, and find their average weighted
            by support \(the number of true instances for each label\)\. This
            alters 'macro' to account for label imbalance; it can result in an
            F-score that is not between precision and recall\.[\s\w]*\.*
        ``'samples'``:
            Calculate metrics for each instance, and find their average \(only
            meaningful for multilabel classification where this differs from
            :func:`accuracy_score`\)\.r¨   )rØ   Údescr_regex_patternN)	r   Úprecision_recall_fscore_supportÚf1_scoreÚfbeta_scoreÚprecision_scoreÚrecall_scorer   rQ   Úsplit)Úmetrics_to_checkÚdescription_regexs     r3   Ú3test_precision_recall_f_score_docstring_consistencyrã   G  s…   € ô 	×/Ñ/Ü×ÑÜ×ÑÜ×ÑÜ×ÑðÐô !ØØð " ?Ð3õð	*ð ô2 !ØØ!�{ØŸH™HÐ%6×%<Ñ%<Ó%>Ó?örk   c                  ó<   — t        t        t        gg d¢ddg¬«       y)z?Check docstrings parameters stacking estimators are consistent.)ÚcvÚn_jobsro   ÚverboseTÚfinal_estimator_)rØ   Úinclude_attrsÚexclude_attrsN)r   r   r   r/   rk   r3   Ú8test_stacking_classifier_regressor_docstring_consistencyrë   x  s!   € ô !Ü	Ô.Ð/ÚAØØ)Ð*ö	rk   )=r<   r>   Úosr:   r   Úpkgutilr   Únumpyr~   r6   r)   r   Úsklearn.datasetsr   Úsklearn.ensembler   r   Úsklearn.experimentalr	   r
   Úsklearn.linear_modelr   Úsklearn.preprocessingr   Úsklearn.utilsr   Ú-sklearn.utils._test_common.instance_generatorr   Úsklearn.utils._testingr   r   r   r   r   Úsklearn.utils.deprecationr   Úsklearn.utils.estimator_checksr   r   r;   Úsimplefilterr¸   r   ÚdirnameÚ__file__Úsklearn_pathr»   r8   rC   rL   rf   rj   rx   r�   ÚmarkrÌ   ÚparametrizerÆ   rº   rã   rë   )Úpckgs   0r3   ú<module>r      sˆ  ðó Û Û 	Û Ý Ý !ã Û ã Ý Ý 0ß B÷õ 4Ý 5Ý (Ý N÷õ õ 5÷ð €X×ÑÓñ 
Ø€H×Ñ˜( MÔ2à—G‘G—O‘O G×$4Ñ$4Ó5Ð6€LÙñ &¨Z¸lÔKö	
àØ˜D ™G‘O y°D¸±GÑ';ð �‹Gò	
ó€N÷	
òÐ òÐ òL9ò^;òTò,ð ‡�×ÑÐKÓLØ‡�×ÑÐ*©NÓ,<Ó=ñv
ó >ó Mðv
òrNð2 ñ-ó ð-ð` ñó ñùòS
	
÷
ð 
ús   Â
AE-ÃE(
Ã,E-Å(E-Å-E6