
    >[g!z                     h	   d dl Z 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mZmZ d dlmZmZmZmZmZmZ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  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/m0Z0m1Z1 d dl2m3Z3m4Z4  G d de      Z5 G d de      Z6 G d de      Z7 G d de      Z8 G d de      Z9 G d de8      Z: G d de8e9      Z; G d  d!e;      Z< G d" d#e      Z= G d$ d%e      Z> G d& d'      Z? G d( d)e      Z@d* ZAd+ ZBd, ZCd- ZDd. ZEd/ ZFd0 ZGd1 ZHd2 ZId3 ZJd4 ZKd5 ZLd6 ZMej                  j                  d7 e&       d8f e  e&       d9d:d;gi      d8f e"d< e&       fg      d8f e"d= e  e&       d9d:d;gi      fg      d8f e'       d>f e  e'       d9d:d;gi      d>f e"d? e'       fg      d>f e"d@ e  e'       d9d:d;gi      fg      d>fg      dA        ZPej                  j                  d7 e'       d8f e  e'       d9d:d;gi      d8f e"d? e'       fg      d8f e"d@ e  e'       d9d:d;gi      fg      d8f e&       d>f e  e&       d9d:d;gi      d>f e"d< e&       fg      d>f e"d= e  e&       d9d:d;gi      fg      d>fg      dB        ZQej                  j                  d7 e       d8f e  e       dCdDdEgi      d8f e"dF e       fg      d8f e"dG e  e       dCdDdEgi      fg      d8f e&       d>f e  e&       d9d:d;gi      d>f e"d< e&       fg      d>f e"d= e  e&       d9d:d;gi      fg      d>fg      dH        ZRdI ZSdJ ZTdK ZUej                  j                  dL e)dMd N       ej                  d O      f e*dMd N       ej                  d O      fg      dP        ZXdQ ZYdR ZZdS Z[ G dT dUe)      Z\dVZ]dW Z^ G dX dYe)      Z_dZ Z`d[ Za G d\ d]      Zb G d^ d_ebe      Zcd` Zdda Ze G db dce      Zfdd Zgde Zhdf Zidg Zjdh Zkdi Zldj Zmdk Zndl Zodm Zp G dn do      Zq G dp dqeqe      Zrej                  j                  dr e        er       g      ds        Zsdt Ztej                  j                  dug dv      dw        Zu ed8x      dy        Zv ed8x      dz        Zwy){    N)assert_allclose)config_contextdatasets)BaseEstimatorOutlierMixinTransformerMixincloneis_classifieris_clustereris_outlier_detectoris_regressor)KMeans)PCA)IsolationForest)InconsistentVersionWarning)GridSearchCV)Pipeline)StandardScaler)SVCSVR)DecisionTreeClassifierDecisionTreeRegressor)MockDataFrame)_get_output_config)_convert_containerassert_array_equal)_check_n_featuresvalidate_datac                       e Zd ZddZy)MyEstimatorNc                      || _         || _        y N)l1empty)selfr#   r$   s      R/var/www/html/bid-api/venv/lib/python3.12/site-packages/sklearn/tests/test_base.py__init__zMyEstimator.__init__.   s    
    )r   N__name__
__module____qualname__r'    r(   r&   r    r    -   s    r(   r    c                       e Zd ZddZy)KNc                      || _         || _        y r"   )cd)r%   r1   r2   s      r&   r'   z
K.__init__4       r(   NNr)   r-   r(   r&   r/   r/   3       r(   r/   c                       e Zd ZddZy)TNc                      || _         || _        y r"   )ab)r%   r9   r:   s      r&   r'   z
T.__init__:   r3   r(   r4   r)   r-   r(   r&   r7   r7   9   r5   r(   r7   c                        e Zd Z fdZ xZS )NaNTagc                 F    t         |          }d|j                  _        |S )NTsuper__sklearn_tags__
input_tags	allow_nanr%   tags	__class__s     r&   r@   zNaNTag.__sklearn_tags__@   s!    w')$(!r(   r*   r+   r,   r@   __classcell__rE   s   @r&   r<   r<   ?        r(   r<   c                        e Zd Z fdZ xZS )NoNaNTagc                 F    t         |          }d|j                  _        |S NFr>   rC   s     r&   r@   zNoNaNTag.__sklearn_tags__G   !    w')$)!r(   rF   rH   s   @r&   rK   rK   F   rI   r(   rK   c                        e Zd Z fdZ xZS )OverrideTagc                 F    t         |          }d|j                  _        |S rM   r>   rC   s     r&   r@   zOverrideTag.__sklearn_tags__N   rN   r(   rF   rH   s   @r&   rP   rP   M   rI   r(   rP   c                       e Zd Zy)DiamondOverwriteTagNr*   r+   r,   r-   r(   r&   rS   rS   T       r(   rS   c                       e Zd Zy)InheritDiamondOverwriteTagNrT   r-   r(   r&   rW   rW   X   rU   r(   rW   c                   <    e Zd ZdZ ej
                  dg      fdZy)ModifyInitParamsz_Deprecated behavior.
    Equal parameters but with a type cast.
    Doesn't fulfill a is a
    r   c                 .    |j                         | _        y r"   )copyr9   r%   r9   s     r&   r'   zModifyInitParams.__init__b   s    r(   N)r*   r+   r,   __doc__nparrayr'   r-   r(   r&   rY   rY   \   s    
 "1# r(   rY   c                       e Zd ZdZddZy)Buggyz9A buggy estimator that does not set its parameters right.Nc                     d| _         y N   r9   r\   s     r&   r'   zBuggy.__init__i   s	    r(   r"   r*   r+   r,   r]   r'   r-   r(   r&   ra   ra   f   s
    ?r(   ra   c                   "    e Zd Zd ZddZddZy)NoEstimatorc                      y r"   r-   r%   s    r&   r'   zNoEstimator.__init__n       r(   Nc                     | S r"   r-   r%   Xys      r&   fitzNoEstimator.fitq   s    r(   c                      y r"   r-   r%   rn   s     r&   predictzNoEstimator.predictt   s    r(   r4   r"   )r*   r+   r,   r'   rp   rs   r-   r(   r&   rh   rh   m   s    r(   rh   c                       e Zd ZdZd Zy)VargEstimatorz-scikit-learn estimators shouldn't have vargs.c                      y r"   r-   )r%   vargss     r&   r'   zVargEstimator.__init__{   rk   r(   Nrf   r-   r(   r&   ru   ru   x   s
    7r(   ru   c                      ddl m} m}  | |d      }t        |      }||usJ |j	                         |j	                         k(  sJ  | |t        j                  d            }t        |      }||usJ y )Nr   	SelectFpr	f_classif皙?alpha)
      )sklearn.feature_selectionrz   r{   r	   
get_paramsr^   zerosrz   r{   selectornew_selectors       r&   
test_cloner      sv     ?#.H?L<''' L$;$;$===="((7*;<H?L<'''r(   c                  h    ddl m} m}  | |d      }d|_        t	        |      }t        |d      rJ y )Nr   ry   r|   r}   testown_attribute)r   rz   r{   r   r	   hasattrr   s       r&   test_clone_2r      s7     ?#.H#H?L|_5555r(   c                  *   t               } d| _        t        j                  t              5  t        |        d d d        t               }t        j                  t              5  t        |       d d d        t               }t        j                  t              5  t        |       d d d        t               }t        j                  t              5  t        |       d d d        y # 1 sw Y   xY w# 1 sw Y   xY w# 1 sw Y   YxY w# 1 sw Y   y xY w)Nr   )
ra   r9   pytestraisesRuntimeErrorr	   rh   	TypeErrorru   rY   )buggyno_estimatorvarg_estests       r&   test_clone_buggyr      s    GEEG	|	$e 
% =L	y	!l 
" H	|	$h 
% 
C	|	$c
 
%	$ 
%	$ 
"	! 
%	$ 
%	$s/   C%"C1C=D	%C.1C:=D	Dc                  ~   t        t        j                  g             } t        |       }t	        | j
                  |j
                         t        t        j                  t        j                  dgg                  } t        |       }t	        | j
                  j                  |j
                  j                         y )Nr$   r   )	r    r^   r_   r	   r   r$   sp
csr_matrixdataclfclf2s     r&   test_clone_empty_arrayr      sq    
BHHRL
)C:Dsyy$**-
BMM"((QC5/:
;C:Dsyy~~tzz7r(   c                      t        t        j                        } t        |       }| j                  |j                  u sJ y Nr   )r    r^   nanr	   r$   r   s     r&   test_clone_nanr      s/    
BFF
#C:D99

"""r(   c                  J    dt               i} t        |       }| d   |d   usJ y )Nr9   )r    r	   )origcloneds     r&   test_clone_dictr      s-    D4[F9F3K'''r(   c            	         t        t              D  cg c]6  } | j                  d      r#t        t	        t        |       x}      t        u r|8 }} |D ]  } |t        j                  d            }t        |      }t        |      }|j                  j                  |j                  j                  u sJ t        |j                  j                         |j                  j                                 y c c} w )N_matrix   r   )dirr   endswithtypegetattrr^   eyer    r	   r$   rE   r   toarray)nameclssparse_matrix_classessparse_matrixr   
clf_cloneds         r&   test_clone_sparse_matricesr      s     GD==#GB4E-ES(F$(N 	   %BFF1I.3Z
yy""j&6&6&@&@@@@399,,.
0@0@0H0H0JK %s   ;C3c                  n    t        t               } t        |       }| j                  |j                  u sJ y r   )r    r	   r$   r   s     r&   test_clone_estimator_typesr      s-     K
(C:D99

"""r(   c                      d} t        j                  t        |       5  t        t               d d d        y # 1 sw Y   y xY w)Nz8You should provide an instance of scikit-learn estimatormatch)r   r   r   r	   r    )msgs    r&   %test_clone_class_rather_than_instancer      s,     EC	y	,k 
-	,	,s	   7A c                      t               } t        |        t        t               t                     }t        |      dk(  sJ t        dgdz        }t	        t        |            dk(  sJ y )NzT(a=K(), b=K())long_paramsi  re   i  )r    reprr7   r/   len)my_estimatorr   some_ests      r&   	test_reprr      s[    =LQS!#;D:****M?T)*HtH~#%%%r(   c                  .    t               } t        |        y r"   )r    str)r   s    r&   test_strr      s    =Lr(   c                  f   t        t               t              } d| j                  d      v sJ d| j                  d      vsJ | j                  d       | j                  j
                  dk(  sJ t        j                  t              5  | j                  d       d d d        y # 1 sw Y   y xY w)Na__dT)deepFr   )r   )a__a)	r7   r/   r   
set_paramsr9   r2   r   r   
ValueError)r   s    r&   test_get_paramsr     s    QS!9DT__$_////e4444OOO6688q==	z	"Q 
#	"	"s   B''B0c                     t        j                  t        d      5  t        t              sJ 	 d d d        t        j                  t        d      5  t        t              sJ 	 d d d        t        j                  t        d      5  t        t              sJ 	 d d d        t        j                  t        d      5  t        t              sJ 	 d d d        y # 1 sw Y   xY w# 1 sw Y   xY w# 1 sw Y   XxY w# 1 sw Y   y xY w)Nz!passing a class to.*is deprecatedr   )r   warnsFutureWarningr
   r   r   r   r   r   r   r   r-   r(   r&   test_is_estimator_type_classr     s    	m+N	OS!!! 
P 
m+N	OC    
P 
m+N	OF### 
P 
m+N	O"?333 
P	O 
P	O 
P	O 
P	O 
P	Os/   CC&C2>C>C#&C/2C;>Dzestimator, expected_resultTCr|   rd   svcsvc_cvFsvrsvr_cvc                 $    t        |       |k(  sJ y r"   )r
   	estimatorexpected_results     r&   test_is_classifierr     s     #666r(   c                 $    t        |       |k(  sJ y r"   )r   r   s     r&   test_is_regressorr   /       	"o555r(   
n_clusters      kmkm_cvc                 $    t        |       |k(  sJ y r"   )r   r   s     r&   test_is_clustererr   @  r   r(   c                  0   t        dt               fg      } t        j                  t              5  | j                  d       d d d        t        j                  t              5  | j                  d       d d d        y # 1 sw Y   >xY w# 1 sw Y   y xY w)Nr   T)svc__stupid_param)svm__stupid_param)r   r   r   r   r   r   )r   s    r&   test_set_paramsr   Q  sl    
UCEN#
$C 
z	". 
# 
z	". 
#	"	 
#	" 
#	"s   B $B B	Bc                       G fddt               } dddt        d |        fg      t         |        i       fD ]  }|j                  dd        y )Nc                   "     e Zd Z fdZ xZS )?test_set_params_passes_all_parameters.<locals>.TestDecisionTreec                 4    t        |   di | |k(  sJ | S )Nr-   )r?   r   )r%   kwargsrE   expected_kwargss     r&   r   zJtest_set_params_passes_all_parameters.<locals>.TestDecisionTree.set_paramsh  s&    G((_,,,Kr(   )r*   r+   r,   r   rG   )rE   r   s   @r&   TestDecisionTreer   g  s    	 	r(   r   r   r   )	max_depthmin_samples_leafr   )estimator__max_depthestimator__min_samples_leaf)r   r   r   r   )r   r   r   s     @r&   %test_set_params_passes_all_parametersr   c  s\    1  %&1=O; 0 2345%', 	A1M	r(   c                      t        t               i       } | j                  t               d       | j                  j
                  dk(  sJ y )Ng      E@)r   estimator__C)r   r   r   r   r   r   )gscvs    r&   $test_set_params_updates_valid_paramsr   v  s>     .0"5DOOce$O7>>t###r(   ztree,datasetr   )r   random_state)r   c                    t         j                  j                  d      }|\  }}| j                  ||       |j	                  ddt        |            }| j                  ||      }| j                  |||      }d}||k7  sJ |       y )Nr   rd   r   )size)sample_weightz5Unweighted and weighted scores are unexpectedly equal)r^   randomRandomStaterp   randintr   score)	treedatasetrngrn   ro   r   score_unweightedscore_weightedr   s	            r&   test_score_sample_weightr  ~  s     ))


"CDAqHHQNKK2CFK3Mzz!Q'ZZ1MZBN
AC~-2s2-r(   c                  2    G d dt         t              } t        j                  d      }t	        |      } | |d      }t        |      }|j                  |j                  k(  j                  j                         sJ |j                  |j                  k(  sJ y )Nc                   &    e Zd ZdZddZddZd Zy)3test_clone_pandas_dataframe.<locals>.DummyEstimatora,  This is a dummy class for generating numerical features

        This feature extractor extracts numerical features from pandas data
        frame.

        Parameters
        ----------

        df: pandas data frame
            The pandas data frame parameter.

        Notes
        -----
        Nc                      || _         || _        y r"   )dfscalar_param)r%   r  r  s      r&   r'   z<test_clone_pandas_dataframe.<locals>.DummyEstimator.__init__  s    DG ,Dr(   c                      y r"   r-   rm   s      r&   rp   z7test_clone_pandas_dataframe.<locals>.DummyEstimator.fit      r(   c                      y r"   r-   rr   s     r&   	transformz=test_clone_pandas_dataframe.<locals>.DummyEstimator.transform  r  r(   rc   r"   )r*   r+   r,   r]   r'   rp   r  r-   r(   r&   DummyEstimatorr    s    		-		r(   r  r   rd   )r  )
r   r   r^   aranger   r	   r  valuesallr  )r  r2   r  ecloned_es        r&   test_clone_pandas_dataframer    s~    )= 6 			"A	q	Br*AQxH DDHKK''++--->>X22222r(   c                  Z    G d dt               } t        j                  ddgddgddgg      }t               j	                  |      }|j
                  } | |      }t        |j
                  |       t        |j                         |j                                t        j                  ddgddgd	dgg      }|j	                  |       t        |j
                  |       |j                  |       t        |j
                  |       t        |      }||u sJ t        |j
                  |       y
)z:Checks that clone works with `__sklearn_clone__` protocol.c                   *    e Zd Zd Zd Zd Zd Zd Zy),test_clone_protocol.<locals>.FrozenEstimatorc                     || _         y r"   )fitted_estimator)r%   r  s     r&   r'   z5test_clone_protocol.<locals>.FrozenEstimator.__init__  s
    $4D!r(   c                 .    t        | j                  |      S r"   )r   r  )r%   r   s     r&   __getattr__z8test_clone_protocol.<locals>.FrozenEstimator.__getattr__  s    400$77r(   c                     | S r"   r-   rj   s    r&   __sklearn_clone__z>test_clone_protocol.<locals>.FrozenEstimator.__sklearn_clone__      Kr(   c                     | S r"   r-   r%   argsr   s      r&   rp   z0test_clone_protocol.<locals>.FrozenEstimator.fit  r#  r(   c                 :     | j                   j                  |i |S r"   )r  r  r%  s      r&   fit_transformz:test_clone_protocol.<locals>.FrozenEstimator.fit_transform  s     24((22DCFCCr(   N)r*   r+   r,   r'   r   r"  rp   r(  r-   r(   r&   FrozenEstimatorr    s    	5	8			Dr(   r)  r   r      rd   N)r   r^   r_   r   rp   components_r   r   get_feature_names_outasarrayr(  r	   )r)  rn   pca
components
frozen_pcaX_newclone_frozen_pcas          r&   test_clone_protocolr6    s   D- D  	2r(RHr2h/0A
%))A,CJ %JJ**J7 z7793;T;T;VW JJQ!Q!Q01ENN5J**J7 U#J**J7 Z(z)))$00*=r(   c                  
   t        j                         } t               j                  | j                  | j
                        }t        j                  |      }d|v sJ t        j                         5  t        j                  d       t        j                  |      }d d d        |j                  | j                  | j
                        }j                  | j                  | j
                        }||k(  sJ y # 1 sw Y   ]xY w)N   _sklearn_versionerror)r   	load_irisr   rp   r   targetpickledumpswarningscatch_warningssimplefilterloadsr  )irisr  tree_pickletree_restoredscore_of_originalscore_of_restoreds         r&   ?test_pickle_version_warning_is_not_raised_with_matching_versionrG    s    D!#''		4;;?D,,t$K+---		 	 	"g&[1 
#
 

499dkk:%++DIIt{{C 1111 
#	"s   2+C99Dc                       e Zd Zd Zy)TreeBadVersionc                 L    t        | j                  j                         d      S )N	something)_sklearn_version)dict__dict__itemsrj   s    r&   __getstate__zTreeBadVersion.__getstate__  s    DMM'')KHHr(   Nr*   r+   r,   rP  r-   r(   r&   rI  rI    s    Ir(   rI  zTrying to unpickle estimator {estimator} from version {old_version} when using version {current_version}. This might lead to breaking code or invalid results. Use at your own risk.c                  `   t        j                         } t               j                  | j                  | j
                        }t        j                  |      }t        j                  ddt        j                        }t        j                  t        |      5 }t        j                  |       d d d        j                   d   j"                  }t%        |t&              sJ |j(                  dk(  sJ |j*                  dk(  sJ |j,                  t        j                  k(  sJ y # 1 sw Y   vxY w)NrI  rK  r   old_versioncurrent_versionr   r   )r   r:  rI  rp   r   r;  r<  r=  pickle_error_messageformatsklearn__version__r   r   UserWarningrA  listmessage
isinstancer   estimator_nameoriginal_sklearn_versioncurrent_sklearn_version)rB  r  tree_pickle_otherr\  warning_records        r&   <test_pickle_version_warning_is_issued_upon_different_versionrc  	  s    D		4;;7DT*"))"++ * G
 
k	1^&' 
2 !!!$,,Gg9:::!!%5555++{:::**g.A.AAAA 
2	1s   D$$D-c                       e Zd Zd Zy)TreeNoVersionc                     | j                   S r"   )rN  rj   s    r&   rP  zTreeNoVersion.__getstate__  s    }}r(   NrQ  r-   r(   r&   re  re    s    r(   re  c                     t        j                         } t               j                  | j                  | j
                        }t        j                  |      }d|vsJ t        j                  ddt        j                        }t        j                  t        |      5  t        j                  |       d d d        y # 1 sw Y   y xY w)Nr8  re  zpre-0.18rS  r   )r   r:  re  rp   r   r;  r<  r=  rV  rW  rX  rY  r   r   rZ  rA  )rB  r  tree_pickle_noversionr\  s       r&   Dtest_pickle_version_warning_is_issued_when_no_version_info_in_pickleri  !  s    D?tyy$++6D"LL.&;;;;"))!++ * G 
k	1*+ 
2	1	1s   B>>Cc                     t        j                         } t               j                  | j                  | j
                        }t        j                  |      }	 t        j                  }dt        _        t        j                         5  t        j                  d       t        j                  |       d d d        |t        _        y # 1 sw Y   xY w# t        _        w xY w)N
notsklearnr9  )r   r:  re  rp   r   r;  r<  r=  r+   r>  r?  r@  rA  )rB  r  rh  module_backups       r&   Ctest_pickle_version_no_warning_is_issued_with_non_sklearn_estimatorrm  2  s    D?tyy$++6D"LL.	1%00#/ $$&!!'*LL./ '
 $1  '&
 $1 s$   /C +C3C CC C c                       e Zd Zd Zd Zy)DontPickleAttributeMixinc                 D    | j                   j                         }d |d<   |S N_attribute_not_pickled)rN  r[   )r%   r   s     r&   rP  z%DontPickleAttributeMixin.__getstate__C  s$    }}!!#)-%&r(   c                 D    d|d<   | j                   j                  |       y )NT	_restored)rN  update)r%   states     r&   __setstate__z%DontPickleAttributeMixin.__setstate__H  s    !kU#r(   N)r*   r+   r,   rP  rw  r-   r(   r&   ro  ro  B  s    
$r(   ro  c                       e Zd ZddZy)MultiInheritanceEstimatorc                      || _         d | _        y r"   attribute_pickledrr  r%   r|  s     r&   r'   z"MultiInheritanceEstimator.__init__N      !2&*#r(   Nr   r)   r-   r(   r&   ry  ry  M  s    +r(   ry  c                      t               } d| _        t        j                  |       }t        j                  |      }|j
                  dk(  sJ |j                  J |j                  sJ y N$this attribute should not be pickledr   )ry  rr  r<  r=  rA  r|  rt  r   
serializedestimator_restoreds      r&   3test_pickling_when_getstate_is_overwritten_by_mixinr  S  sd    )+I'MI$i(Jj1//144444<<<''''r(   c                  `   	 t               } d}|| _        t        |       j                  }dt        |       _        | j	                         }|d ddk(  sJ d|d<   | j                  |       | j                  dk(  sJ | j                  sJ 	 |t        |       _        y # t               _        w xY w)Nr  rk  r   )rr  r|  r-  r|  )ry  rr  r   r+   rP  rw  r|  rt  )r   textold_modr  s       r&   Ftest_pickling_when_getstate_is_overwritten_by_mixin_outside_of_sklearnr  ^  s    --/	5+/	(y/,,%1Y"++-
STUUUU*+
&'z***a///""""%,Y"WY"s   BB B-c                   &     e Zd ZddZ fdZ xZS )SingleInheritanceEstimatorc                      || _         d | _        y r"   r{  r}  s     r&   r'   z#SingleInheritanceEstimator.__init__r  r~  r(   c                 .    t         |          }d |d<   |S rq  )r?   rP  )r%   rv  rE   s     r&   rP  z'SingleInheritanceEstimator.__getstate__v  s     $&*.&'r(   r  )r*   r+   r,   r'   rP  rG   rH   s   @r&   r  r  q  s    + r(   r  c                      t               } d| _        t        j                  |       }t        j                  |      }|j
                  dk(  sJ |j                  J y r  )r  rr  r<  r=  rA  r|  r  s      r&   Ctest_pickling_works_when_getstate_is_overwritten_in_the_child_classr  |  sU    *,I'MI$i(Jj1//144444<<<r(   c                     t               } t               }| j                         j                  j                  sJ |j                         j                  j                  rJ t               }|j                         j                  j                  rJ t               }|j                         j                  j                  sJ t               }|j                         j                  j                  sJ y r"   )r<   rK   r@   rA   rB   rP   rS   rW   )nan_tag_estno_nan_tag_estredefine_tags_estdiamond_tag_estinherit_diamond_tag_ests        r&   test_tag_inheritancer    s     (KZN'')44>>>>..0;;EEEE# 113>>HHHH)+O++-88BBBB8:"335@@JJJJr(   c                       G d dt               }  |        }d}t        j                  t        |      5  |j	                          d d d        y # 1 sw Y   y xY w)Nc                       e Zd ZddZddZy)<test_raises_on_get_params_non_attribute.<locals>.MyEstimatorc                      y r"   r-   )r%   params     r&   r'   zEtest_raises_on_get_params_non_attribute.<locals>.MyEstimator.__init__  r  r(   Nc                     | S r"   r-   rm   s      r&   rp   z@test_raises_on_get_params_non_attribute.<locals>.MyEstimator.fit  r#  r(   r  r"   )r*   r+   r,   r'   rp   r-   r(   r&   r    r    s    		r(   r    z-'MyEstimator' object has no attribute 'param'r   )r   r   r   AttributeErrorr   )r    r   r   s      r&   'test_raises_on_get_params_non_attributer    s@    m  -C
9C	~S	1 
2	1	1s   AAc                      t               } | j                         }d|v sJ d|v sJ t        d      5  | j                         }d|v sJ d|vsJ 	 d d d        y # 1 sw Y   y xY w)Nz
text/plainz	text/htmlr  display)r   _repr_mimebundle_r   )r  outputs     r&   test_repr_mimebundle_r    sr    !#D##%F6!!!&   		''')v%%%&((( 
(	'	's   AA#c                  
   t               } | j                         }d|v sJ t        d      5  d}t        j                  t
        |      5  | j                         }d d d        d d d        y # 1 sw Y   xY w# 1 sw Y   y xY w)Nz<style>r  r  z _repr_html_ is only defined whenr   )r   _repr_html_r   r   r   r  )r  r  r   s      r&   test_repr_html_wrapsr    sl    !#DF		'0]]>5%%'F 6 
(	'55 
(	's#   A9A-A9-A6	2A99Bc                      t               } g dg dg}t        | |d       | j                  dk(  sJ d}t        j                  t
        |      5  t        | dd	       d
d
d
       y
# 1 sw Y   y
xY w)z>Check that `_check_n_features` validates data when reset=False)rd   r   r   )r-  r      Tresetr   zHX does not contain any features, but MyEstimator is expecting 3 featuresr   	invalid XFN)r    r   n_features_in_r   r   r   )r   X_trainr   s      r&   test_n_features_in_validationr    s^    
-C)$Gc7$/"""
TC	z	-#{%8 
.	-	-s   A''A0c                  l    t               } t        | dd       t        | d      rJ t        | dd       y)z]Check that `_check_n_features` does not validate data when
    n_features_in_ is not defined.r  Tr  r  FN)r    r   r   )r   s    r&    test_n_features_in_no_validationr    s6     -Cc;d3s,--- c;e4r(   c                     t        j                  d      } t        j                         }|j                  }| j                  ||j                        } G d dt        t              } |       j                  |      }t        |j                  |j                         |j                  |       t        |d      rJ |j                  |       d}| j                  ||j                  ddd         }t        j                  t        |	      5  |j!                  |       ddd       d
}t        j"                  t$        |	      5  |j!                  |       ddd       d} |       j                  |      }t        j"                  t$        |	      5  |j!                  |       ddd       | j                  |      } |       }t'        j(                         5  t'        j*                  dt$               |j                  |       ddd       ||g}	|	D ]J  }
t'        j(                         5  t'        j*                  dt$               |j!                  |
       ddd       L | j                  |g d      } |       }t-        j.                  d      }t        j                  t0        |	      5  |j                  |       ddd       t        j                  t0        |	      5  |j!                  |       ddd       y# 1 sw Y   xY w# 1 sw Y   xY w# 1 sw Y   sxY w# 1 sw Y    xY w# 1 sw Y   'xY w# 1 sw Y   xY w# 1 sw Y   yxY w)z;Check that feature_name_in are recorded by `_validate_data`pandascolumnsc                       e Zd ZddZd Zy).test_feature_names_in.<locals>.NoOpTransformerNc                     t        | |       | S r"   r   rm   s      r&   rp   z2test_feature_names_in.<locals>.NoOpTransformer.fit      $"Kr(   c                 "    t        | |d       |S NFr  r  rr   s     r&   r  z8test_feature_names_in.<locals>.NoOpTransformer.transform  s    $/Hr(   r"   r*   r+   r,   rp   r  r-   r(   r&   NoOpTransformerr    s    		r(   r  feature_names_in_z5The feature names should match those that were passedNr*  r   zVX does not have valid feature names, but NoOpTransformer was fitted with feature nameszIX has feature names, but NoOpTransformer was fitted without feature namesr9  )r9   r:   rd   r   a  Feature names are only supported if all input features have string names, but your input has ['int', 'str'] as feature name / column name types. If you want feature names to be stored and validated, you must convert them all to strings, by using X.columns = X.columns.astype(str) for example. Otherwise you can remove feature / column names from your input data, or convert them all to a non-string data type.)r   importorskipr   r:  r   	DataFramefeature_namesr   r   rp   r   r  r  r   r   r   r  r   rZ  r>  r?  r@  reescaper   )pdrB  X_npr  r  transr   df_baddf_int_namesXsrn   df_mixeds               r&   test_feature_names_inr    s   			X	&BD99D	dD$6$6	7B*M  !!"%Eu..

; 
IIdOu1222	IIbM
AC\\$(:(:4R4(@\AF	z	- 
.
	$  
k	- 
. VC!!$'E	k	- 
. <<%LE		 	 	"g{3		, 
# 	B$$&!!';7OOA '&  ||D*:|;HE
))	?C 
y	,		( 
- 
y	,! 
-	,_ 
.	- 
.	- 
.	- 
#	" '& 
-	, 
-	,sT   K:LL,L!(,L.*L;M:LLL!L+.L8	;MMc                  "   t        j                  d      } t        j                         }| j	                  |j
                  |j                        }| j                  |j                        } G d dt        t              } |       }t        ||d      }t        |t        j                        sJ t        ||j!                                t        ||d      }||u sJ t        ||d      }t        |t        j                        sJ t        ||j!                                t        ||d      }	|	|u sJ t        |||d      \  }}t        |t        j                        sJ t        ||j!                                t        |t        j                        sJ t        ||j!                                t        |||d      \  }}	||u sJ |	|u sJ d	}
t        j"                  t$        |

      5  t        |       ddd       y# 1 sw Y   yxY w)z0Check skip_check_array option of _validate_data.r  r  c                       e Zd Zy)<test_validate_data_skip_check_array.<locals>.NoOpTransformerNrT   r-   r(   r&   r  r  0      r(   r  F)skip_check_arrayT)ro   r  z*Validation should be done on X, y or both.r   N)r   r  r   r:  r  r   r  Seriesr;  r   r   r   r]  r^   ndarrayr   to_numpyr   r   )r  rB  r  ro   r  no_opX_np_outX_df_outy_np_outy_series_outr   s              r&   #test_validate_data_skip_check_arrayr  (  s    
		X	&BD	dii););	<B
		$++A*M  EUB?Hh

+++Hbkkm,UB>Hr>>Ua%@Hh

+++Hajjl+ !dCL1&ub!eLHhh

+++Hbkkm,h

+++Hajjl+*5"a$OHlr>>1
6C	z	-e 
.	-	-s   0HHc                      t               j                  d      } t        d|       }t        |       }t        d|      }||k(  sJ y)z-Check that clone keeps the set_output config.r  )r  r  N)r   
set_outputr   r	   )ssconfigss_cloneconfig_clones       r&   test_clone_keeps_output_configr  Q  sI     
		$	$x	$	8BR0FRyH%k8<L\!!!r(   c                       e Zd Zy)_EmptyNrT   r-   r(   r&   r  r  \  rU   r(   r  c                       e Zd Zy)EmptyEstimatorNrT   r-   r(   r&   r  r  `  rU   r(   r  r   c                     | j                         }dt        j                  i}||k(  sJ t        j                  t        j
                  t                            y)zCheck that ``__getstate__`` returns an empty ``dict`` with an empty
    instance.

    Python 3.11+ changed behaviour by returning ``None`` instead of raising an
    ``AttributeError``. Non-regression test for gh-25188.
    rL  N)rP  rX  rY  r<  rA  r=  r   )r   rv  expecteds      r&   "test_estimator_empty_instance_dictr  d  sI     ""$E"G$7$78HH LLmo./r(   c                  Z    G d d      }  G d dt         |       }d}t        j                  t        |      5   |       j	                          ddd       t        j                  t        |      5  t        j                   |              ddd       y# 1 sw Y   HxY w# 1 sw Y   yxY w)z:Using a `BaseEstimator` with `__slots__` is not supported.c                       e Zd ZdZy)Dtest_estimator_getstate_using_slots_error_message.<locals>.WithSlots)xN)r*   r+   r,   	__slots__r-   r(   r&   	WithSlotsr  w  s    	r(   r  c                       e Zd Zy)Dtest_estimator_getstate_using_slots_error_message.<locals>.EstimatorNrT   r-   r(   r&   	Estimatorr  z  r  r(   r  zRYou cannot use `__slots__` in objects inheriting from `sklearn.base.BaseEstimator`r   N)r   r   r   r   rP  r<  r=  )r  r  r   s      r&   1test_estimator_getstate_using_slots_error_messager  t  s     M9 	' 
 
y	,  " 
- 
y	,Y[! 
-	, 
-	, 
-	,s   B1B!B!B*zconstructor_name, minversion))	dataframez1.5.0)pyarrowz12.0.0)polarsz0.20.23c                    g dg dg}g d}t        || ||      } G d dt        t              } |       }|j                  |       t	        |j
                  |       |j                  |      }| dk7  rt        ||       g d}t        || |	      }	t        j                  t        d
      5  |j                  |	       ddd       y# 1 sw Y   yxY w)z:Uses the dataframe exchange protocol to get feature names.)rd   r-  r   )r   r   r  )col_0col_1col_2)columns_name
minversionc                       e Zd ZddZd Zy)0test_dataframe_protocol.<locals>.NoOpTransformerNc                     t        | |       | S r"   r  rm   s      r&   rp   z4test_dataframe_protocol.<locals>.NoOpTransformer.fit  r  r(   c                     t        | |d      S r  r  rr   s     r&   r  z:test_dataframe_protocol.<locals>.NoOpTransformer.transform  s     q66r(   r"   r  r-   r(   r&   r  r    s    		7r(   r  r  )r9   r:   r1   )r  zThe feature names should matchr   N)r   r   r   rp   r   r  r  r   r   r   r   )
constructor_namer  r   r  r  r  r  X_out	bad_namesr  s
             r&   test_dataframe_protocolr    s     y!D)G	W
B7*M 7 E	IIbMu..8OOBE9$ 	E"I&6YOF	z)I	J 
K	J	Js   -CC)enable_metadata_routingc                      G d dt         t              } t        j                  t        d      5   |        j                  d      j                  dggdgd       ddd       t        j                  d	      5 } |        j                  d      j                  dggdg       t        |      d
k(  sJ 	 ddd       y# 1 sw Y   dxY w# 1 sw Y   yxY w)zkTest that having a transformer with metadata for transform raises a
    warning when calling fit_transform.c                       e Zd ZddZddZy)Ttest_transformer_fit_transform_with_metadata_in_transform.<locals>.CustomTransformerNc                     | S r"   r-   r%   rn   ro   props       r&   rp   zXtest_transformer_fit_transform_with_metadata_in_transform.<locals>.CustomTransformer.fit  r#  r(   c                     |S r"   r-   r%   rn   r  s      r&   r  z^test_transformer_fit_transform_with_metadata_in_transform.<locals>.CustomTransformer.transform      Hr(   r4   r"   r  r-   r(   r&   CustomTransformerr        		r(   r  z*`transform` method which consumes metadatar   Tr  rd   Nrecordr   )
r   r   r   r   rZ  set_transform_requestr(  r>  r?  r   )r  r  s     r&   9test_transformer_fit_transform_with_metadata_in_transformr    s    
M+;  
k)U	V11t1<JJSEA3Q 	K 	
 
W 
	 	 	-11t1<JJQC5STRUV6{a 
.	- 
W	V 
.	-   -C ;;C C	Cc                      G d dt         t              } t        j                  t        d      5   |        j                  d      j                  dggdgd       ddd       t        j                  d	      5 } |        j                  d      j                  dggdg       t        |      d
k(  sJ 	 ddd       y# 1 sw Y   dxY w# 1 sw Y   yxY w)ziTest that having an OutlierMixin with metadata for predict raises a
    warning when calling fit_predict.c                       e Zd ZddZddZy)Vtest_outlier_mixin_fit_predict_with_metadata_in_predict.<locals>.CustomOutlierDetectorNc                     | S r"   r-   r
  s       r&   rp   zZtest_outlier_mixin_fit_predict_with_metadata_in_predict.<locals>.CustomOutlierDetector.fit  r#  r(   c                     |S r"   r-   r  s      r&   rs   z^test_outlier_mixin_fit_predict_with_metadata_in_predict.<locals>.CustomOutlierDetector.predict  r  r(   r4   r"   )r*   r+   r,   rp   rs   r-   r(   r&   CustomOutlierDetectorr    r  r(   r  z(`predict` method which consumes metadatar   Tr  rd   Nr  r   )
r   r   r   r   rZ  set_predict_requestfit_predictr>  r?  r   )r  r  s     r&   7test_outlier_mixin_fit_predict_with_metadata_in_predictr    s    
|  
k)S	T333>JJSEA3Q 	K 	
 
U 
	 	 	-333>JJQC5STRUV6{a 
.	- 
U	T 
.	-r  )xr<  r  r>  numpyr^   r   scipy.sparsesparser   numpy.testingr   rX  r   r   sklearn.baser   r   r   r	   r
   r   r   r   sklearn.clusterr   sklearn.decompositionr   sklearn.ensembler   sklearn.exceptionsr   sklearn.model_selectionr   sklearn.pipeliner   sklearn.preprocessingr   sklearn.svmr   r   sklearn.treer   r   sklearn.utils._mockingr   sklearn.utils._set_outputr   sklearn.utils._testingr   r   sklearn.utils.validationr   r   r    r/   r7   r<   rK   rP   rS   rW   rY   ra   rh   ru   r   r   r   r   r   r   r   r   r   r   r   r   r   markparametrizer   r   r   r   r   r   make_classificationmake_regressionr  r  r6  rG  rI  rV  rc  re  ri  rm  ro  ry  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r-   r(   r&   <module>r6     s    	     )  ,	 	 	 # % , 9 0 % 0   F 0 8 F
-   ] } & 	&( 		!4 	} M  M ($6(8#(L#&
 4  		cecC8_	-t4	E35>"	#T*	Hl353a/BCD	EtL		cecC8_	-u5	E35>"	#U+	Hl353a/BCD	EuM	77  		cecC8_	-t4	E35>"	#T*	Hl353a/BCD	EtL		cecC8_	-u5	E35>"	#U+	Hl353a/BCD	EuM	66  	4	fh1v 6	7>	D&(#$	%t,	G\&(\Aq64JKLM	NPTU		cecC8_	-u5	E35>"	#U+	Hl353a/BCD	EuM	66
/$N&$  #QQ?(H((a8	

 "AA>$H$$!4	
	33#3L)>X2 I+ I B&* 
,"1 $ $+ 8- +(-& =K$
)
(
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