
    0Ph                        d dl Z d dlZd dlZd dlmZ d dlmZmZ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"m#Z#m$Z$m%Z%m&Z&m'Z'm(Z(m)Z)m*Z*m+Z+m,Z, d dl-m.Z. d dl/m0Z0m1Z1 d dl2m3Z3 ej4        5                    d e             e             e             e             e             e             e             e             e             e             e             ej6         ed	d
dd          ej4        7                    d                     ed           e             e             e             e             e             e              e$             e%             e(             ej6         e*d          ej4        7                    d                     e*d	d           e,d           gd           ej4        5                    dddg          d                         Z8ej4        9                    d          ej4        9                    d          ej4        5                    deeeeeeeeeeeeee1eee e"e$e%e(e*e+e,g          ej4        5                    d d!d"g          d#                                                 Z:ej4        5                    d$e0eee!e#e&e'e)g          ej4        5                    d%d"d&g          d'                         Z;dS )(    N)is_classifier)make_classificationmake_low_rank_matrixmake_regression)"ARDRegressionBayesianRidge
ElasticNetElasticNetCVGammaRegressorHuberRegressorLarsLarsCVLassoLassoCV	LassoLarsLassoLarsCVLassoLarsICLinearRegressionLogisticRegressionLogisticRegressionCVMultiTaskElasticNetMultiTaskElasticNetCVMultiTaskLassoMultiTaskLassoCVOrthogonalMatchingPursuitOrthogonalMatchingPursuitCVPassiveAggressiveClassifierPassiveAggressiveRegressor
PerceptronPoissonRegressorRidgeRidgeClassifierRidgeClassifierCVRidgeCVSGDClassifierSGDRegressorTheilSenRegressorTweedieRegressor)MinMaxScaler)	LinearSVC	LinearSVR)set_random_statemodel
elasticnetsaga      ?gV瞯<)penaltysolverl1_ratiotolz"Missing importance sampling scheme)reason)marksgư>)r4   zInsufficient precision.i'  )r1   max_iter)powerc                     | j         j        S )N)	__class____name__)xs    f/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/sklearn/linear_model/tests/test_common.py<lambda>r>   \   s    !+&     )idswith_sample_weightFTc                    |rFdt          j        | j                  j                                        vrt          j        d           d}t          | t                    rd}nt          | d          r| j
        dk    rd}t          j                            |          }d\  }}}t          | t          t          t           t"          f          rd	}t%          |||
          }|r<|                    dd||f          t          j        |d          d d d f         z  }	n/|                    dd|          t          j        |d          z  }	t          j        ||	z  dz             }
|                    |
          dz   }t/          |           r&||
dz   k                        t          j                  }|r$|                    dd|j        d                   }nd }|                     d           |r|                     |||           n|                     ||           t/          |           rct          j        |                     |          d d df         |          t          j        t          j        ||          |          k    sJ d S t          j        |                     |          |d          t          j        t          j        ||d          |          k    sJ d S )Nsample_weightz)Estimator does not support sample_weight.g-C6*?g?r2   r/   g{Gz?)d   
   N   )	n_samples
n_featuresrandom_state   )lowhighsizer   )axisr0   )lam   rE   T)fit_intercept)rC   )weights)rel)rS   rO   ) inspect	signaturefit
parameterskeyspytestskip
isinstancer&   hasattrr2   nprandomRandomStater   r   r   r   r   uniformmaxexppoissonr   astypefloat64shape
set_paramsaveragepredict_probaapproxpredict)r-   rA   global_random_seedrT   rngn_trainrH   	n_targetsXcoefexpectationysws                r=   test_balance_propertyrv   4   s(   r 	A7#4UY#?#?#J#O#O#Q#QQQ?@@@
C%&& 		!	! elf&<&<
)

 2
3
3C%2"GZ	3^EUV   	w:TWXXXA PKKBQj)-DKEEfQQ4() 	
 {{r
{;;bfQQ>O>O>OO&TC((K$$q(AU 5q ((44 [[QRagaj[99	4((( 		!Qb	))))		!QU 
z%--a00A6CCCv}Jq"%%%3H
 H
 H
 
 
 
 
 
 
 z%--**BQ???6=Jq"1---3D
 D
 D
 
 
 
 
 
 
r?   z!ignore:The default of 'normalize'zignore:lbfgs failed to converge	RegressorndimrQ   rK   c                    | t           u rt          j        d           t          ddd          \  }}t	                                          |                    dd                    dddf         dz   }|d	k    r|ddt          j        f         n|} |             }t          |           |
                    ||           |j        j        |j        d         fk    sJ dS )
z4Check the consistency of linear models `coef` shape.z8LinearRegression does not follow `coef_` shape contract!r         )rI   rG   rH   rQ   NrK   )r   rZ   xfailr   r)   fit_transformreshaper^   newaxisr,   rW   coef_rg   )rw   rx   rq   rt   	regressors        r=   &test_linear_model_regressor_coef_shaper      s    D $$$OPPPSRHHHDAq$$QYYr1%5%566qqq!t<q@A AII!!!RZ-1A	IYMM!Q? QWQZM111111r?   
Classifier	n_classesrF   c                 6   | t           t          fv rt          j        |  d           t	          d|d          \  }}|j        d         } |             }t          |           |                    ||           |dk    rd|fn||f}|j        j        |k    sJ d S )Nz( does not follow `coef_` shape contract!rE   r   )n_informativer   rI   rQ   rK   )	r"   r#   rZ   r}   r   rg   r,   rW   r   )r   r   rq   rt   rH   
classifierexpected_shapes          r=   'test_linear_model_classifier_coef_shaper      s     o'8999
LLLMMMR9STUUUDAqJJZ   NN1a(1Qa__Y
<SN!^333333r?   )<rU   numpyr^   rZ   sklearn.baser   sklearn.datasetsr   r   r   sklearn.linear_modelr   r   r	   r
   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r    r!   r"   r#   r$   r%   r&   r'   r(   sklearn.preprocessingr)   sklearn.svmr*   r+   sklearn.utils._testingr,   markparametrizeparamr}   rv   filterwarningsr   r    r?   r=   <module>r      sX         & & & & & & W W W W W W W W W W# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #H / . . . . . , , , , , , , , 3 3 3 3 3 3 
		 	$Vcu   +##+O#PP		
 	
 	
 	&&&!!####%%		LU###+##+D#EE	
 	
 	
 	\F;;;q!!!I%L 	'&Q  ) )T -t}==@
 @
 >=U) )V@
F ?@@=>>!#"1 : !Q((2 2 )(;  ?> A@@2 #	  q!f--4 4 .- 4 4 4r?   