
    {KgO                         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
mZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZm Z  ejB                  jE                  d e	        e
        e        e        e        e        e        e        e        e        e        ejF                   edddd	
      ejB                  jI                  d             ed       e        e        e        e        e        e        e        e        e        ejF                   ed	      ejB                  jI                  d             edd       e d       gd       ejB                  jE                  dddg      d               Z%y)    N)is_classifier)make_low_rank_matrix)ARDRegressionBayesianRidge
ElasticNetElasticNetCVLarsLarsCVLassoLassoCVLassoLarsCVLassoLarsICLinearRegressionLogisticRegressionLogisticRegressionCVMultiTaskElasticNetMultiTaskElasticNetCVMultiTaskLassoMultiTaskLassoCVOrthogonalMatchingPursuitOrthogonalMatchingPursuitCVPoissonRegressorRidgeRidgeCVSGDRegressorTweedieRegressormodel
elasticnetsaga      ?gV瞯<)penaltysolverl1_ratiotolz"Missing importance sampling scheme)reason)marksgư>)r$   zInsufficient precision.i'  )r!   max_iter)powerc                 .    | j                   j                  S )N)	__class____name__)xs    j/home/alanp/www/video.onchill/myenv/lib/python3.12/site-packages/sklearn/linear_model/tests/test_common.py<lambda>r.   O   s    !++&&    )idswith_sample_weightFTc                 z   |rNdt        j                  | j                        j                  j	                         vrt        j                  d       d}t        | t              rd}nt        | d      r| j                  dk(  rd}t        j                  j                  |      }d\  }}}t        | t        t        t         t"        f      rd	}t%        |||
      }|r6|j'                  dd||f      t        j(                  |d      d d d f   z  }	n,|j'                  dd|      t        j(                  |d      z  }	t        j*                  ||	z  dz         }
|j-                  |
      dz   }t/        |       r%||
dz   kD  j1                  t        j2                        }|r"|j'                  dd|j4                  d         }nd }| j7                  d       |r| j                  |||       n| j                  ||       t/        |       r]t        j8                  | j;                  |      d d df   |      t        j<                  t        j8                  ||      |      k(  sJ y t        j8                  | j?                  |      |d      t        j<                  t        j8                  ||d      |      k(  sJ y )Nsample_weightz)Estimator does not support sample_weight.g-C6*?g?r"   r   g{Gz?)d   
   N   )	n_samples
n_featuresrandom_state   )lowhighsizer   )axisr    )lam   r5   T)fit_intercept)r3   )weights)rel)rC   r?   ) inspect	signaturefit
parameterskeyspytestskip
isinstancer   hasattrr"   nprandomRandomStater   r   r   r   r   uniformmaxexppoissonr   astypefloat64shape
set_paramsaveragepredict_probaapproxpredict)r   r1   global_random_seedrD   rngn_trainr8   	n_targetsXcoefexpectationysws                r-   test_balance_propertyrf   '   s`   r 	7#4#4UYY#?#J#J#O#O#QQ?@
C%&		!ellf&<
))

 2
3C%2"GZ	3^EUV 	w:TWXAKKBQj)-DKEffQQ4() 	
 {{r
{;bffQQ>OO&&TC(K$q(AUq ((4[[QRaggaj[9	4(		!Qb	)		!Q Uzz%--a0A6Cv}}JJq"%3H
 
 	
 
 zz%--*BQ?6==JJq"1-3D
 
 	
 
r/   )&rE   numpyrN   rJ   sklearn.baser   sklearn.datasetsr   sklearn.linear_modelr   r   r   r   r	   r
   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   markparametrizeparamxfailrf    r/   r-   <module>rp      s      & 1      : 	 	$Vcu ++##+O#P		
 	&!##%	U#++##+D#E	
 	\F;q!I%L 	'Q  )T -t}=A
 >U)VA
r/   