o
    \i-                    @   s  d dl Z d dlmZ d dlmZ d dlmZmZmZ d dl	Z
d dl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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/m0Z0m1Z1m2Z2m3Z3m4Z4m5Z5m6Z6m7Z7m8Z8m9Z9m:Z:m;Z;m<Z<m=Z=m>Z> d d	l?m@Z@ d d
lAmBZBmCZCmDZDmEZEmFZFmGZGmHZHmIZImJZJmKZKmLZL d dlMmNZN d dlOmPZP d dlQmRZRmSZSmTZTmUZU d dlVmWZWmXZXmYZYmZZZm[Z[m\Z\ d dl]m^Z^m_Z_m`Z` d dlambZb d dlcmdZdmeZe i de)de*de/de0de-de2de+dedee7ddde;de<dee1d d d!e.d"e,d#ee1d$d d%eed$d d&ed'eiZfi d(ed)ed*eed+d,d-eed.d/d0ed1d2d3 d4e3d5ee3d+d6d7e"d8e>d9ee>d.d/d:e$d;e6d<e8d=e d>ee!d?d@dAee!dBd@i dCe(dDee!dEdBdFdGee dEdHdIee!dEd?dFdJee6dEdHdKee8dEdHdLee$dEdHdMee!dNdBdFdOee dNdHdPee!dNd?dFdQee6dNdHdRee8dNdHdSee$dNdHdTee!dUdBdFdVee dUdHdWee!dUd?dFdXee6dUdHee8dUdHee$dUdHee!dYdBdFee dYdHee!dYd?dFee6dYdHee8dYdHee$dYdHedZ	Zgd[d\ Zhe:ehed]Zii d^ed_e&d`e'daee'd.d/dbe#dcedde9deee9dEdHdfee9dYdHdgee9dNdHdhee9dUdidjdkee9dEdidjdlee9dUdmdjdnee9dEdmdjdoee9dBdpdqedreedEdHeedYdHeedNdHe%e4ee=dsZjek Zlelmej elmeg elmef elmei h dtZnh duZoenpeoZqh dvZrh dwZsh dxZth dyZuh dzZvh d{Zwh d|Zxh d}Zyh d~Zzh dZ{h dZ|h dZ}ddhZ~dd Zdd Zdd Zejdeezdd Zejdee{dd Zdd Zejdeeeleq dd Zdd Zejdeeeleq dd Zejdeeegeq dd Zejdejdd Zd dge
je
jgfd dge
je
jgfd dge
je
jgfd dge
jdgfd dge
jdgfgZejdeej ef ejdedd Zejdeg ejdee
jdd?gg dfe
jdd?gg dfg dd Zejdeg dd Zdd Zdd Zejdejdeeeleq eej dd ZejdejdeeyexB dd Zejdeeydd Zejdeeydd Zejdejde^dd Zejdeexdd Zejdeevdd Zejdeevdd Zejdeevexdd Zdd Zdd Zejdeerdd ZejdeeresB ddÄ Zejdeerddń ZddǄ ZejdeerddɄ Zdd˄ Zejdeeeleefe| dd̈́ Zejdeeeleefe| ddτ Zejdeeeleef e| en ddф Zejdeeeleef e| eq ddӄ ZejdeexewB e| ddՄ Zejdeeye| ddׄ Zddل Zejdeexd4h ddۄ ZejdeeweyB dd݄ Zejdeeejeq dd߄ Zejdegdd Zejded+fed+fe d.fee!dd@d.fe$d.fe5d+fe6d.fe8d.fe:d+fg	ejdeegdd Zdd Zdd Zdd Zdd Zdd Zdd Zdd Zi eeeege eeege!eege$eeege3eeege6eeege8eeege>eeege"eeege1egee1dd egee1dd ege7eegeEegeeege*eege-eegi e/eege0eegeegeHege.egeBege,ege)ege+eegeCegeIegeDegeFegeGegeJegeKege;eege<eegeLegiZefddZejjdeU eTdejde dd Zejddd gejdeeldd Zdd Zejdeeldd ZdS (      N)partial)	signature)chainpermutationsproduct)config_context)make_multilabel_classification)UndefinedMetricWarning),accuracy_scoreaverage_precision_scorebalanced_accuracy_scorebrier_score_losscohen_kappa_scoreconfusion_matrixcoverage_errord2_absolute_error_scored2_pinball_scored2_tweedie_score	dcg_score	det_curveexplained_variance_scoref1_scorefbeta_scorehamming_loss
hinge_lossjaccard_score%label_ranking_average_precision_scorelabel_ranking_losslog_lossmatthews_corrcoef	max_errormean_absolute_errormean_absolute_percentage_errormean_gamma_deviancemean_pinball_lossmean_poisson_deviancemean_squared_errormean_squared_log_errormean_tweedie_deviancemedian_absolute_errormultilabel_confusion_matrix
ndcg_scoreprecision_recall_curveprecision_scorer2_scorerecall_scoreroc_auc_score	roc_curveroot_mean_squared_errorroot_mean_squared_log_errortop_k_accuracy_scorezero_one_loss)_average_binary_score)additive_chi2_kernelchi2_kernelcosine_distancescosine_similarityeuclidean_distanceslinear_kernelpaired_cosine_distancespaired_euclidean_distancespolynomial_kernel
rbf_kernelsigmoid_kernel)LabelBinarizer)shuffle)_atol_for_type_convert_to_numpy_get_namespace_device_dtype_ids)yield_namespace_device_dtype_combinations)_array_api_for_testsassert_allcloseassert_almost_equalassert_array_equalassert_array_lessignore_warnings)COO_CONTAINERSparse_version
sp_version)type_of_target)_num_samplescheck_random_stater    r!   r&   r'   r$   r)   r"   r   r.   variance_weighted)multioutputr2   r3   mean_normal_deviance)powerr%   r#   mean_compound_poisson_deviancegffffff?r   r   r   r
   r    adjusted_balanced_accuracy_scoreT)adjustedunnormalized_accuracy_scoreF	normalizeunnormalized_confusion_matrixnormalized_confusion_matrixc                  O   s8   t | i |dt | i |jddd d tjf  S )Nfloat   axis)r   astypesumnpnewaxis)argskwargs rj   /var/www/www-root/data/www/176.119.141.140/sports-predictor/venv/lib/python3.10/site-packages/sklearn/metrics/tests/test_common.py<lambda>   s   "rl   (unnormalized_multilabel_confusion_matrix/unnormalized_multilabel_confusion_matrix_sample)
samplewiser   r5   unnormalized_zero_one_lossr   r-   r/   r   f2_score   )beta
f0.5_score      ?matthews_corrcoef_scoreweighted_f0.5_scoreweightedaveragers   weighted_f1_scorerz   weighted_f2_scoreweighted_precision_scoreweighted_recall_scoreweighted_jaccard_scoremicro_f0.5_scoremicromicro_f1_scoremicro_f2_scoremicro_precision_scoremicro_recall_scoremicro_jaccard_scoremacro_f0.5_scoremacromacro_f1_scoremacro_f2_scoremacro_precision_scoresamples)	macro_recall_scoremacro_jaccard_scoresamples_f0.5_scoresamples_f1_scoresamples_f2_scoresamples_precision_scoresamples_recall_scoresamples_jaccard_scorer   c               
   O   sR   t | i |\}}}t|t| }t||tj|tjd|fdtjgdgS )a'  
    The dimensions of precision-recall pairs and the threshold array as
    returned by the precision_recall_curve do not match. See
    func:`sklearn.metrics.precision_recall_curve`

    This prevents implicit conversion of return value triple to an higher
    dimensional np.array of dtype('float64') (it will be of dtype('object)
    instead). This again is needed for assert_array_equal to work correctly.

    As a workaround we pad the threshold array with NaN values to match
    the dimension of precision and recall arrays respectively.
    r   constant)	pad_widthmodeconstant_values)r,   lenrf   arraypadrd   float64nan)rh   ri   	precisionrecall
thresholdspad_threshholdsrj   rj   rk   (precision_recall_curve_padded_thresholds   s   
r   )r1   r,   r   r   r   r   unnormalized_log_lossr   r   r0   weighted_roc_aucsamples_roc_aucmicro_roc_aucovr_roc_aucovr)rz   multi_classweighted_ovr_roc_aucovo_roc_aucovoweighted_ovo_roc_aucpartial_roc_auc)max_fprr    weighted_average_precision_score)samples_average_precision_scoremicro_average_precision_scorer   r+   r   r4   >   r   r+   r   r   r   r   r   r   r   r   rn   r   >   r   rq   r   r1   r/   r   r   r0   r   r-   r   r   r,   rt   >   r   rq   r/   r   r-   rt   >   r0   r   r   >   r   rq   r   r1   r/   r   r-   r   r,   r   r   r   r   rt   >"   r   rq   r   r   r1   r/   r   r   r   r   r   r-   r   r   r{   r}   r   r   r   r   r   r   r   r,   r   r~   r_   r^   rm   rn   rt   r   r   rw   >   r5   r
   r4   >   r   r   r+   r   r0   r   r   r   r   r   r   r   r   r   r   r   r   >   r   r5   r
   r   r   r   r   r   r   r{   r}   r   r   r   r   r   r   r   r   r   r   r   r~   rp   r[   rm   r   r   r   rw   >   r.   r   r$   r&   r!   r)   r'   r   r2   r   r3   r"   >   r   r    r   r   r5   r
   r   r   r   r   r$   r&   r   r   r!   r   rV   r)   r   r   r   r'   rv   r2   rp   r3   r[   r   >   rq   r.   r   r1   r   r/   r   r-   r   r   r{   r}   r   r#   r   r%   r,   r   r   r   r   r~   r_   r^   r"   rX   rY   rm   rt   r   rw   >   r    r   r   r)   >   r   r#   r%   rX   c                 C   s2   t t|  | d }| |7 } ||7 }| |fS )zMake targets strictly positivera   )absminy1y2offsetrj   rj   rk   _require_positive_targetsB  s   r   c                 C   sJ   t t|  | d }| tj} |tj}| |7 } ||7 }| |fS )z$Make targets strictly larger than -1gGz?)r   r   rd   rf   r   r   rj   rj   rk   _require_log1p_targetsJ  s   r   c                   C   s6   t tB ttB tB ttksJ t t@ t ksJ d S N)SYMMETRIC_METRICSNOT_SYMMETRIC_METRICSsetTHRESHOLDED_METRICS"METRIC_UNDEFINED_BINARY_MULTICLASSALL_METRICSrj   rj   rj   rk   test_symmetry_consistencyT  s   r   namec                 C   s   t d}|jdddd}|jdddd}| tv r t||\}}n| tv r+t||\}}|jdddd}|jdddd}t|  }| tv r\| tv rXt	||||||d|  d d S J d	t	||||||d|  d d S )
Nr   rr      sizer      z%s is not symmetricerr_msgFz This case is currently unhandled)
rS   randintMETRICS_REQUIRE_POSITIVE_Yr   METRICS_WITH_LOG1P_Yr   r   METRIC_UNDEFINED_BINARYMULTILABELS_METRICSrI   )r   random_statey_truey_pred
y_true_bin
y_pred_binmetricrj   rj   rk   test_symmetric_metric`  s.   

r   c           	      C   s   t d}t|  }d}tdD ]1}|jdddd}|jdddd}| tv r+t||\}}|||}|||}t||s?d} nq|rIt|  dd S )	Nr   T   rr   r   r   F seems to be symmetric)	rS   r   ranger   r   r   rf   allclose
ValueError)	r   r   r   always_symmetric_r   r   nominalswappedrj   rj   rk   test_not_symmetric_metric  s"   

r   c                  C   s   d} d}t |  tjt| dd t | W d    n1 s!w   Y  t| tjt|  dd t|  W d    d S 1 sDw   Y  d S )Nr
   r/   z is not symmetricmatchr   )r   pytestraisesAssertionErrorr   r   )symnot_symrj   rj   rk   test_symmetry_tests  s   

"r   c                 C   s   t d}|jdddd}|jdddd}| tv r t||\}}n| tv r+t||\}}t||dd\}}t  t|  }t	||||||d|  d W d    d S 1 sVw   Y  d S )Nr   rr   r   r   r    %s is not sample order invariantr   )
rS   r   r   r   r   r   rC   rM   r   rI   )r   r   r   r   y_true_shuffley_pred_shuffler   rj   rj   rk   test_sample_order_invariance  s    "r   c            	      C   s  t d} | jdddd}| jdddd}| j|jd}||jddd }t|||dd\}}}tD ]}t| }t||||||d	| d
 q1t	D ]}t| }t||||||d	| d
 qIt
D ]$}t| }t||||||d	| d
 t||||||d	| d
 qad S )Nr   rr   r   r   ra   Trc   keepdimsr   r   r   )rS   r   uniformshapere   rC   r   r   rI   THRESHOLDED_MULTILABEL_METRICSMULTIOUTPUT_METRICS)	r   r   r   y_scorer   r   y_score_shuffler   r   rj   rj   rk   7test_sample_order_invariance_multilabel_and_multioutput  sF   r   c              	   C   s  t d}|jdddd}|jdddd}| tv r t||\}}n| tv r+t||\}}t|}t|}t|t|}}t	|j
d t	|j
d t|d}t|d}	t|d}
t|d}t  t|  }|||}t||||d|  d	 t||||d
|  d	 t|||	|d|  d	 t||||d|  d	 t||||d|  d	 t|||	|d|  d	 t||||d|  d	 t|||	|d|  d	 t||||d|  d	 tt ||| W d    n1 sw   Y  tt ||
| W d    n	1 sw   Y  tt ||| W d    n	1 s'w   Y  tt ||
| W d    n	1 sBw   Y  tt ||| W d    n	1 s]w   Y  tt ||
|	 W d    n	1 sxw   Y  | ttB tB vrd| v rtt t||
|sJ W d    n	1 sw   Y  n+tt ||
| W d    n!1 sw   Y  W d    d S W d    d S W d    d S W d    d S 1 sw   Y  d S )Nr   rr   r   r   ra   )ra   )ra   r   z,%s is not representation invariant with listr   z3%s is not representation invariant with np-array-1dz7%s is not representation invariant with np-array-columnz@%s is not representation invariant with mix np-array-1d and listzK%s is not representation invariant with mix np-array-1d and np-array-columnzD%s is not representation invariant with mix list and np-array-columnroc_auc)rS   r   r   r   r   r   listrf   r   rK   ndimreshaperM   r   rI   r   r   r   r   r   r   warnsr	   mathisnan)r   r   r   r   y1_listy2_listy1_1dy2_1d	y1_column	y2_columny1_rowy2_rowr   measurerj   rj   rk   &test_format_invariance_with_1d_vectors  s   



	


 \ e$r
  c                 C   sb  t d}|jdddd}|jdddd}tddg| }tddg| }d}ddg}t x t|  }|||}	|}
| tv rEt|
|d}
|
||}t|	|d	| d	 |
|
d
|
d
}t|	|d	| d	 | tv rt|
|d}
|
||}t|	|d	| d	 |
|
d
|
d
}t|	|d	| d	 W d    d S W d    d S 1 sw   Y  d S )Nr   rr   r   r   eggsspam	pos_label+{0} failed string vs number invariance testr   O2{0} failed string object vs number invariance test)labelsz,{0} failed string vs number  invariance test)rS   r   rf   r   rM   CLASSIFICATION_METRICSMETRICS_WITH_POS_LABELr   rK   formatrd   METRICS_WITH_LABELS)r   r   r   r   y1_stry2_strpos_label_str
labels_strr   measure_with_number
metric_strmeasure_with_strmeasure_with_strobjrj   rj   rk   7test_classification_invariance_string_vs_numbers_labelss  sT   


"r  c              	   C   sn  t d}|jdddd}|jdddd}tddg| }d}t  t|  }| tvr^|}| tv r7t||d}|||}|||}	t	||	d
| d	 ||d
|}
t	||
d
| d	 n?tt ||| W d    n1 ssw   Y  tt ||d
| W d    n1 sw   Y  W d    d S W d    d S W d    d S 1 sw   Y  d S )Nr   rr   r   r   r  r  r  r  r   r  r  )rS   r   rf   r   rM   r   r   r  r   rK   r  rd   r   r   r   )r   r   r   r   r  r  r   r  r  r  r  rj   rj   rk   4test_thresholded_invariance_string_vs_numbers_labels  sJ   

	"r   ra   r   zy_true, y_scorec                 C   sR   | t kr
|g}|g}tjtdd | || W d    d S 1 s"w   Y  d S )Nzcontains (NaN|infinity)r   )r   r   r   r   )r   r   r   rj   rj   rk   )test_regression_thresholded_inf_nan_input  s   "r!  )ra   rr      c                 C   s   t | sd}t | rd}nd}nd}t | r"d}nd}d| d| }tjt|d | || W d   dS 1 sDw   Y  dS )	z{check that classification metrics raise a message mentioning the
    occurrence of non-finite values in the target vectors.r   NaNzinfinity or a value too larger   zInput z
 contains r   N)rf   isfiniteallr   anyr   r   r   )r   r   r   
input_nameunexpected_valuer   rj   rj   rk   !test_classification_inf_nan_input  s   "r)  c                 C   sT   g dg d}}d}t jt|d | || W d   dS 1 s#w   Y  dS )zocheck that classification metrics raise a message of mixed type data
    with continuous/binary target vectors.)abr*  皙?皙?333333?zJClassification metrics can't handle a mix of binary and continuous targetsr   N)r   r   r   )r   r   r   r   rj   rj   rk   +test_classification_binary_continuous_input  s   "r0  c                 C   s\   t |  }| tv rddg}n| tv rddg}nddg}t|ddD ]\}}||g|g q d S )Nra   rr   gffffffr   repeat)r   r   r   r   )r   r   valuesijrj   rj   rk   check_single_sample  s   

r6  c                 C   sL   t |  }tddgddD ]\}}}}|t||ggt||gg qd S )Nr   ra      r1  )r   r   rf   r   )r   r   r4  r5  klrj   rj   rk   check_single_sample_multioutput-  s   $r:  ignorec                 C      t |  d S r   )r6  r   rj   rj   rk   test_single_sample4  s   r>  c                 C   r<  r   )r:  r=  rj   rj   rk   test_single_sample_multioutputD  s   r?  c                 C   sz   t g dg dg dg}t ddgddgddgg}t|  }tt ||| W d    d S 1 s6w   Y  d S )N)ra   r   r   ra   )r   ra   ra   ra   )ra   ra   r   ra   r   ra   rf   r   r   r   r   r   )r   r   r   r   rj   rj   rk   (test_multioutput_number_of_output_differJ  s   "rA  c                 C   s   t d}|jdddd}|jdddd}t|  }|||}tdD ]"}||jd }t||d d |f |d d |f |d|  d q!d S )	Nr   rr   r   r   r   r"  ra   z'%s is not dimension shuffling invariantr   )rS   r   r   r   permutationr   rI   )r   r   r   r   r   errorr   permrj   rj   rk   =test_multioutput_regression_invariance_to_dimension_shufflingT  s   
 rF  z1ignore::sklearn.exceptions.UndefinedMetricWarningcoo_containerc                 C   s  d}d}t d|d|dd\}}t d|d|dd\}}t|dg| gg}t|dg| gg}| |}| |}t|}t|}	dd |D }
d	d |	D }tD ]:}t| }t|trad
|_||_	|||}t
||||d| d t||
||d| d t|||	|d| d qPd S )Nr7  2   ra   r   T
n_features	n_classesr   	n_samplesallow_unlabeledc                 S      g | ]}t |qS rj   r   .0r*  rj   rj   rk   
<listcomp>      z=test_multilabel_representation_invariance.<locals>.<listcomp>c                 S   rN  rj   rO  rP  rj   rj   rk   rR    rS  tmpzO%s failed representation invariance between dense and sparse indicator formats.r   z\%s failed representation invariance  between dense array and list of list indicator formats.zW%s failed representation invariance  between dense and list of array indicator formats.)r   rf   vstackr   r   r   
isinstancer   
__module____name__rI   rJ   )rG  rK  rL  r   r   r   y1_sparse_indicatory2_sparse_indicatory1_list_array_indicatory2_list_array_indicatory1_list_list_indicatory2_list_list_indicatorr   r   r	  rj   rj   rk   )test_multilabel_representation_invarianceg  sh   

	

	
r_  c              	   C   s   dgdgddggg dg gdgt jg ddggddg}t|  }|D ]}tt ||| W d    n1 s8w   Y  q!d S )Nra   rr   r   )rj   rr   )r   ra   rj   objectdtyper@  )r   multilabel_sequencesr   seqrj   rj   rk   +test_raise_value_error_multilabel_sequences  s   re  c                 C   s   d}d}t d}|jd||fd}|jd||fd}|j|jd}t|  }| tv r+|n|}|||dd}	|||dd}
td|	 dd	d
 t|	|
| d|  d
 d S )Nrr   r   r   r   Tr\   F      0We failed to test correctly the normalize optionr   Failed with )rS   r   normalr   r   r   rL   rI   r   rK  rL  r   r   r   r   metricspredmeasure_normalizedmeasure_not_normalizedrj   rj   rk   +test_normalize_option_binary_classification  s(   
ro  c                 C   s   d}d}t d}|jd||fd}|jd||fd}|j||fd}t|  }| tv r,|n|}|||dd}	|||dd}
td|	 dd	d
 t|	|
| d|  d
 d S )Nr7  r   r   r   Tr\   Frf  rg  r   rh  )rS   r   r   r   r   rL   rI   rj  rj   rj   rk   /test_normalize_option_multiclass_classification  s(   
rp  c                 C   s   d}d}t d}td|dd|d\}}td|dd|d\}}|j|jd}|dg| 7 }|dg| 7 }t|  }| tv r=|n|}	|||	dd}
|||	d	d}td
|
 ddd t|
|| d|  d d S )Nr7  d   r   ra   T)rJ  rK  r   rM  rL  r   r\   Frf  rg  r   rh  )rS   r   r   r   r   r   rL   rI   )r   rK  rL  r   r   r   r   r   rk  rl  rm  rn  rj   rj   rk   /test_normalize_option_multilabel_classification  sD   


rr  c                    s  j \}} ||d d}t| fddt|D   ||dd}	t|	     ||dd}
t|
t| tjdtd}t|dkr_ ||dd}t|tj||d	 n ||dd}t|d |r ||d
d}t|t fddt|D  t	
t  ||dd W d    n1 sw   Y  t	
t  ||dd W d    d S 1 sw   Y  d S )Nr|   c                    s.   g | ]} d d |f d d |f qS r   rj   rQ  r4  r   y_pred_binarizey_true_binarizerj   rk   rR  :  s     z$_check_averaging.<locals>.<listcomp>r   r   r   )rc   rb  rx   )weightsr   c                    s   g | ]} | | qS rj   rj   rs  rt  rj   rk   rR  Z  s    unknowngarbage)r   rI   r   ravelrf   meanre   intrz   r   r   r   )r   r   r   rv  ru  is_multilabelrL  rK  label_measuremicro_measuremacro_measurerw  weighted_measuresample_measurerj   rt  rk   _check_averaging1  sH   
	

"r  c                 C   sZ   t |d}t|  }| tv rt|||||| d S | tv r)t|||||| d S td)N
multilabelz2Metric is not recorded as having an average option)rQ   
startswithr   METRICS_WITH_AVERAGINGr  "THRESHOLDED_METRICS_WITH_AVERAGINGr   )r   r   rv  r   ru  r   r}  r   rj   rj   rk   check_averagingg  s   r  c           
      C   sz   d\}}t d}|jd||fd}|jd||fd}|j||fd}t |}||}||}	t| ||||	| d S )N)rH  r"  r   r   )rS   r   r   rB   fit	transformr  )
r   rL  rK  r   r   r   r   lbrv  ru  rj   rj   rk   test_averaging_multiclassx  s   

r  c           
      C   sh   d\}}t d|d|dd\}}|d d }|dd  }tdjd|fd}|}|}	t| ||||	| d S )	N)(   r   ra   r   FrI  r   r   r   )r   rS   ri  r  )
r   rL  rK  r   yr   r   r   rv  ru  rj   rj   rk   test_averaging_multilabel  s   
r  c                 C   <   t d}t d}t d}|}|}t| ||||| d S Nr   r"  )rf   zerosr  r   r   r   r   rv  ru  rj   rj   rk   $test_averaging_multilabel_all_zeroes     


r  c                  C   s>   t d} t d}| }|}ddd}t|| |||dd d S )Nr  r   c                 S   s   t t| ||S r   )r6   r-   )r   r   rz   rj   rj   rk   rl     s    z=test_averaging_binary_multilabel_all_zeroes.<locals>.<lambda>T)r}  )r   )rf   r  r  )r   r   rv  ru  binary_metricrj   rj   rk   +test_averaging_binary_multilabel_all_zeroes  s   



r  c                 C   r  r  )rf   onesr  r  rj   rj   rk   "test_averaging_multilabel_all_ones  r  r  c                 C   s,  t jd}|jddt|d}| dkrt|ddn|}|||d d}t||||t jt|ddd	|  d
 ||||d}t	t
 t|| td||| f 1 sUw   Y  |||| d}t||d||| f d
 |t j||ddt j||ddd d}	t||	d|  d
 |dd d }
t |}d|d d d< |dd d }|dd d }||||
d}||||d}t||d||| f d
 | dsdD ]}t|||||| dd|  d
 qdt|t|t|d }tj	t|d |||t ||gd W d    d S 1 sw   Y  d S )Nr   ra   
   r   r4   )r8  sample_weight)r   zAFor %s sample_weight=None is not equivalent to sample_weight=onesr   zQUnweighted and weighted scores are unexpectedly almost equal (%s) and (%s) for %szVWeighted scores for array and list sample_weight input are not equal (%s != %s) for %srb   z.Weighting %s is not equal to repeating samplesrr   zeZeroing weights does not give the same result as removing the corresponding samples (%s != %s) for %sunnormalized)rr   r/  z/%s sample_weight is not invariant under scalingzJFound input variables with inconsistent numbers of samples: \[{}, {}, {}\]r   )rf   randomRandomStater   r   r   rI   r  r   r   r   r   tolistr2  copyr  r  rR   hstack)r   r   r   r   rngr  unweighted_scoreweighted_scoreweighted_score_listrepeat_weighted_scoresample_weight_subsetsample_weight_zeroed	y1_subset	y2_subsetweighted_score_subsetweighted_score_zeroedscalingerror_messagerj   rj   rk   check_sample_weight_invariance  s   
	


	$r  c                 C   sB   d}t d}|j|fd}|j|fd}t|  }t| ||| d S )NrH  r   r   )rS   random_sampler   r  )r   rL  r   r   r   r   rj   rj   rk   (test_regression_sample_weight_invariance&  s   r  c                 C   s   d}t d}|j|fd}|j|fd}t|  }|j|d fd}tjtdd ||||d W d    n1 s:w   Y  |j|d fd|df}tjtd	d ||||d W d    d S 1 sgw   Y  d S )
NrH  r   r   ra   z'Found input variables with inconsistentr   r  rr   z)Sample weights must be 1D array or scalar)rS   r  r   r   r   r   r   )r   rL  r   r   r   r   r  rj   rj   rk   *test_regression_with_invalid_sample_weight7  s   	"r  c                 C   sr   d}t d}|jdd|fd}|jdd|fd}|j|fd}t|  }| tv r0t| ||| d S t| ||| d S )NrH  r   rr   r   )rS   r   r  r   r   r  )r   rL  r   r   r   r   r   rj   rj   rk   $test_binary_sample_weight_invarianceQ  s   r  c           	      C   s   d}t d}|jdd|fd}|jdd|fd}|j|dfd}t|  }| tv rCt| }||jdddd }t	| ||| d S t	| ||| d S )NrH  r   r   r   r   rb   ra   )
rS   r   r  r   r   rf   expre   r   r  )	r   rL  r   r   r   r   r   tempy_score_normrj   rj   rk   (test_multiclass_sample_weight_invarianceh  s   r  c           	      C   s   t d}tdddddd\}}tdddddd\}}t||g}t||g}|j|jd}||jddd	 }t|  }| tv rIt	| ||| d S t	| ||| d S )
Nr   ra   r  rH  FrI  r   Tr   )
rS   r   rf   rU  r   r   re   r   r   r  )	r   r   r   yaybr   r   r   r   rj   rj   rk   (test_multilabel_sample_weight_invariance  s   	



r  c                 C   sB   t d}|jdddd}|jdddd}t|  }t| ||| d S )Nr   rr   rB  r   )rS   r   r   r  )r   r   r   r   r   rj   rj   rk   )test_multioutput_sample_weight_invariance  s
   r  c                  C   s   t g dg dg} t g dg dg}t g d}t g d}t g d}t j|dd\}}tD ]3}||g| |gfD ](\}}	|tvrN|	jd	krNq@t| }
|
||	|d d
}|
||	d d}t|||  q@q6d S )N)ra   ra   r   r   r   r   ra   ra   )r   ra   ra   r   )r   ra   rr   )r   rr   r"  )r"  r   ra   rr   T)return_inversera   )r  rz   r|   )rf   r   uniquer  r   r   r   rK   )y_true_multilabely_pred_multilabely_true_multiclassy_pred_multiclassr  r   inverse_labelsr   r   r   r   score_labelsscorerj   rj   rk   test_no_averaging_labels  s$   r  c                 C   s   t d}d\}}|jdd||fd}|jdd||fd}t|  }|||}tt||D ]}|d d |f }	|d d |f }
||
|	}t|| q,d S )Nr   r   r7  rr   r   )rS   r   r   r   r   rJ   r   r   rL  rK  r   r   r   r  rE  y_score_permy_true_permcurrent_scorerj   rj   rk   -test_multilabel_label_permutations_invariance  s   

r  c                 C   s   t d}d\}}|jdd||fd}|j|jd}||jddd }d||ddkdf< d||ddkdf< t|  }|||}tt||D ].}|d d |f }	|d d |f }
||
|	}|tkrqt	
|sjJ |d	kspJ qHt|| qHd S )
Nr   r  rr   r   ra   Tr   r7  g    .A)rS   r   r   r   re   r   r   r   r"   rf   r$  rJ   r  rj   rj   rk   ?test_thresholded_multilabel_multioutput_permutations_invariance  s$   

r  c                 C   s   d\}}t d}|||}t| }||jdddd }|jd||d}t|  }|||}tt	||D ]*}	tj
|td}
t||
t|	< |d d |
f }t|	|}|||}t|| q8d S )N)rq  r"  r   r   rb   ra   r   ra  )rS   randrf   r  re   r   r   r   r   r   r  r|  aranger   takerJ   )r   rL  rK  r   r   r  r   r   r  rE  inverse_permr  r  r  rj   rj   rk   .test_thresholded_metric_permutation_invariance  s    

r  metric_namec                 C   s   t jd}t jdgd dgd  td}|jdd|jd}d	}tjt	|d
 t
|  || W d    d S 1 s:w   Y  d S )N*   r  r"  r  rr   ra  r   r   z7Labels in y_true and y_pred should be of the same type.r   )rf   r  r  r   r`  r   r   r   r   	TypeErrorr  )r  r  r   r   r   rj   rj   rk   "test_metrics_consistent_type_error  s   "r  zmetric, y_pred_thresholddtype_y_strc           
      C   s   t jd}t jdgd dgd  |d}|jdd|jd}|s+t jddg|d| }d	}d
}t| jd j}|dkr=|n|}	t	j
t|	d | || W d    d S 1 sWw   Y  d S )Nr  r  r"  r  rr   ra  r   r   zy_true takes value in {'eggs', 'spam'} and pos_label is not specified: either make y_true take value in {0, 1} or {-1, 1} or pass pos_label explicitzHpos_label=1 is not a valid label. It should be one of \['eggs', 'spam'\]r  ra   r   )rf   r  r  r   r   r   r   
parametersdefaultr   r   r   )
r   y_pred_thresholdr  r  r   r   err_msg_pos_label_Noneerr_msg_pos_label_1pos_label_defaultr   rj   rj   rk    test_metrics_pos_label_error_str$  s   "r  c              
   K   s  t ||}|j||d}|j||d}	| ||fi |}
|dd ur.|j|d |d|d< |d}t|tjrB|j||d|d< zt| t|	 d}W n tttfy^   d}Y nw |r| ||	fi |}t	||
t
|d | ||	fi |}t	||
t
|d | ||fi |}t	||
t
|d tdd! | ||	fi |}t	t||||
t
|d W d    d S 1 sw   Y  d S )N)devicer  rU   TF)atol)array_api_dispatch)rH   asarraygetrV  rf   ndarrayr  RuntimeErrorr   rI   rD   r   rE   )r   array_namespacer  
dtype_namea_npb_npmetric_kwargsxpa_xpb_xp	metric_nprU   numpy_as_array_works	metric_xpmetric_xp_mixed_1metric_xp_mixed_2rj   rj   rk   check_array_api_metricM  sZ   




"r  c              	   C   s^   t g d}t g d}t| |||||d d t jg d|d}t| ||||||d d S )Nr  )r   ra   r   ra   r  r  r          r-         @      ?ra  rf   r   r  r   r  r  r  	y_true_np	y_pred_npr  rj   rj   rk   ,check_array_api_binary_classification_metric  s*   

r  c           
      C   s   t g d}t g d}ddd}t| |d}|D ])}t| |||f||d d| t jg d|d	}	t| |||f|||	d| qd S )
N)r   ra   rr   r"  )r   ra   r   rr   r   r   rx   r.  ru   g?ry   r   paramsr  r  ra  rf   r   (_get_metric_kwargs_for_array_api_testingr  
r   r  r  r  r  r  additional_paramsmetric_kwargs_combinationsr  r  rj   rj   rk   0check_array_api_multiclass_classification_metric  sH   r	  c           
      C   s   t jddgddgddgg|d}t jddgddgddgg|d}ddd}t| |d}|D ])}t| |||f||d d| t jg d	|d}	t| |||f|||	d| q-d S )
Nra   r   ra  r   r  ry   r  r  )r  r-  r  r  r  rj   rj   rk   0check_array_api_multilabel_classification_metric  sH     r
  c           	      C   s   t | tr	| jjn| j}|dkrttdk rtd tj	g d|d}tj	g d|d}i }t
| j}d|v r<d |d< t| |||f||d| d|v ritj	g d	|d|d< t| |||f||d| d S d S )
Nr%   z1.14.0zJmean_poisson_deviance's dependency `xlogy` is available as of scipy 1.14.0)r  r-  r  g      @ra  )ru   ru   rr   rr   r  r  r  )r-  r        ?ru   )rV  r   funcrX  rP   rO   r   skiprf   r   r   r  r  )	r   r  r  r  	func_namer  r  r  metric_paramsrj   rj   rk   !check_array_api_regression_metric  sL   



r  c                 C   s   t jg dg dg|d}t jg dg dg|d}t| |||||d d t jddg|d}t| ||||||d t| |||||t jg d	|dd
 t| |||||dd
 d S )N)ra   r"  rr   )ra   rr   rr   ra  )ra   r7  r7  )ra   ra   ra   r  r-  r  )r-  r/  ffffff?)r  r  rU   
raw_valuesr  r  rj   rj   rk   -check_array_api_regression_metric_multioutput$  sN   



r  c                 C   s   t jg dg dg|d}t jg dg dg|d}i }dt| jv r9d|d< t| |||f||d| d	|d< t| |||f||d| d S )
Nr,  )皙?ru   333333?ra  )r.  r/  r  )ru   r  r  dense_outputFr  T)rf   r   r   r  r  )r   r  r  r  X_npY_npr  rj   rj   rk   check_array_api_metric_pairwiseU  s8   	
r  g      r  c                 c   s,    |   D ]\}}|D ]}||fV  qqd S r   )items)metric_checkersr   checkerscheckerrj   rj   rk   !yield_metric_checker_combinations  s   r  z#array_namespace, device, dtype_name)idszmetric, check_funcc                 C   s   || ||| d S r   rj   )r   r  r  r  
check_funcrj   rj   rk   test_array_api_compliance  s   r"  df_lib_namepandaspolarsc                 C   s|   t |}|g d}|g d}t|  }z|| | }W n ty3   t |  d Y nw t|||| d S )N)r  r  r   r  )r  r  r  r  z can not deal with 1d inputs)r   importorskipSeriesr   to_numpyr   r  rI   )r  r#  df_libr   r   r   expected_metricrj   rj   rk   test_metrics_dataframe_series  s   
r+  c           	      C   sb   i g}|  D ]'\}}|t| jvrqg }|D ]}|D ]}| }|||< || qq|}q|S )zHelper function to enable specifying a variety of additional params and
    their corresponding values, so that they can be passed to a metric function
    when testing for array api compliance.)r  r   r  r  append)	r   r  r  paramr3  new_combinationsri   value
new_kwargsrj   rj   rk   r    s   r  c                 C   s   t jd}|jdddd}|jdddd}| tv r!t||\}}| tv r5|jdddd}|jdddd}t|  }|||}t|t	t j
tfsIJ t|t jt jfrTJ t|trmtdd |D sotdd |D sqJ d	S d	S d	S )
zEnsure that the returned values of all metrics are consistent.

    It can either be a float, a numpy array, or a tuple of floats or numpy arrays.
    It should not be a numpy float64 or float32.
    r   rr   r   r   r  c                 s   s    | ]}t |tV  qd S r   )rV  r`   rQ  vrj   rj   rk   	<genexpr>*	  s    z2test_returned_value_consistency.<locals>.<genexpr>c                 s   s    | ]	}t |tjV  qd S r   )rV  rf   r  r1  rj   rj   rk   r3  *	  s    
N)rf   r  r  r   r   r   r   r   rV  r`   r  tupler   float32r%  )r   r  r   r   r   r  rj   rj   rk   test_returned_value_consistency	  s$   

r6  )r   	functoolsr   inspectr   	itertoolsr   r   r   numpyrf   r   sklearn._configr   sklearn.datasetsr   sklearn.exceptionsr	   sklearn.metricsr
   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r    r!   r"   r#   r$   r%   r&   r'   r(   r)   r*   r+   r,   r-   r.   r/   r0   r1   r2   r3   r4   r5   sklearn.metrics._baser6   sklearn.metrics.pairwiser7   r8   r9   r:   r;   r<   r=   r>   r?   r@   rA   sklearn.preprocessingrB   sklearn.utilsrC   sklearn.utils._array_apirD   rE   rF   rG   sklearn.utils._testingrH   rI   rJ   rK   rL   rM   sklearn.utils.fixesrN   rO   rP   sklearn.utils.multiclassrQ   sklearn.utils.validationrR   rS   REGRESSION_METRICSr  r   CURVE_METRICSr   dictr   updater   METRIC_UNDEFINED_MULTICLASSunionr   r  r  r  r  METRICS_WITH_NORMALIZE_OPTIONr   r   r   r   r   METRICS_WITHOUT_SAMPLE_WEIGHTr   r   r   r   r   markparametrizesortedr   r   r   r   r   r   r
  r  r   infr   invalids_nan_infr3  r!  r)  r0  r6  r:  filterwarningsr>  r?  rA  rF  r_  re  ro  rp  intersectionrr  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  r  strr`  r  r  r  r	  r
  r  r  r  array_api_metric_checkersr  r"  r+  r  r6  rj   rj   rj   rk   <module>   sX   .4 #	
	
 !"#$%&'()*+,
-




9 	

"




&"$$	

!

-
~
5
+		




	

K



/6





a



	
	


	

!

@((*1#(-./0459=AEILMNOPQUVWXYZ[\`h