
    Гh                     l    S r SSKJrJr  SSKrSSKrSSKrSSK	J
r
  SSKJr  S\SS4S jrS\SS4S	 jrg)
zTests for evaluation metrics.    )DictListN)concat)_parse_eval_strtree_methodreturnc           
         [         R                  " S5      nUR                  SSSSS9u  p#[        R                  " UR
                  S9n[        R                  " SU S9nUR                  X#US	9  UR                  S
SSSS9u  p#UR                  SS9  [        UR                  5       R                  [        R                  " X#5      S4/S95      nUS   S   n/ n/ n	Sn
/ n[        U
5       Hx  nUR                  S
SSSS9u  p#UR                  U5        U	R                  U5        [        R                   " UR
                  U[        R"                  S9nUR                  U5        Mz     [%        U5      n[%        U5      n[%        U	5      n[        UR                  5       R                  [        R                  " X#US	9S4/S95      nUS   S   R'                  S5      (       d   eUS   S   nX:X  d   eg)z3Test for precision with ranking and classification.zsklearn.datasetsi         i  )	n_samples
n_features	n_classesrandom_state)shape)n_estimatorsr   )qidi   i  zpre@32)eval_metricXy)evals      )r   
fill_valuedtyper   N)pytestimportorskipmake_classificationnpzerosr   xgb	XGBRankerfit
set_paramsr   get_boostereval_setDMatrixrangeappendfulluint64r   endswith)r   datasetsXyr   ltrresultscore_0X_listy_listn_query_groupsq_listiqscore_1s                  jC:\Users\julio\OneDrive\Documentos\Trabajo\Ideas Frescas\venv\Lib\site-packages\xgboost/testing/metrics.pycheck_precision_scorer9      s   ""#56H''1 ( DA ((
!C
--QK
@CGGAcG ''!qt ( DA NNxN(""3;;q+<d*C)D"EF QilGFFN!F>"++a14 , 
 	aaGG!''aryyAa # .CvAvA""3;;q+Et*L)M"NF !9Q<  ****QilG    c                    SSK Jn  SSKJn  [        R
                  R                  S5      nU" SSUS9u  pE[        R                  " XE5      n0 n[        R                  " U SS	S
.UUS4/US9nUR                  U5      n	U" XYS	S9n
[        R                  R                  US   S   S   U
5        / SQn[        R                  " U SUSS.UUS4/US9nUR                  U5      n	[        R                  " [        S5       Vs/ s H  o" XYSS2U4   X   S9PM     sn5      n
[        R                  R                  US   S   S   U
5        gs  snf )zTest for the `quantile` loss.r   )make_regression)mean_pinball_loss      r   )r   quantileg333333?)r   r   quantile_alphaTrain)r   evals_result)alpha)g      ?g      ?g      ?zreg:quantileerror)r   r   rA   	objectiveN)sklearn.datasetsr<   sklearn.metricsr=   r   randomRandomStater   QuantileDMatrixtraininplace_predicttestingassert_allclosemeanr&   )r   r<   r=   rngr,   r-   r   rC   boosterpredtlossrD   r5   s                r8   check_quantile_errorrU   >   sR   01
))


#C34DA			Q	"B$&Lii#JRUV
G}o!	G ##A&EQS1DJJ|G4Z@DdKEii&%#,		
 	G}o!
G ##A&E77DI!HMHq	1AqDk	:HMD JJ|G4Z@DdK 	Ns   >E)__doc__typingr   r   numpyr   r   xgboostr   xgboost.compatr   xgboost.corer   strr9   rU    r:   r8   <module>r^      sD    #     ! (.s .t .b$Lc $Ld $Lr:   