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    §ñ:iZ  ã                   óL   • S r SSKrSSKrSSKJr  SSKJr  SSK	J
r
  S/rSS jrg)	zUtilities for random sampling.é    Né   )Úcheck_random_state)Úsample_without_replacementr   c           	      ó|  • [         R                   " S5      n[         R                   " S5      n[         R                   " SS/5      n[        [        U5      5       GH¹  n[        R                  " X   5      X'   X   R
                  R                  S:w  a  [        SX   R
                  -  5      eX   R                  [        R                  SS9X'   UcG  [        R                  " X   R                  S   S9nUR                  SX   R                  S   -  5        O[        R                  " X'   5      n[        R                  " [        R                  " U5      S5      (       d  [        S	R                  U5      5      eUR                  S   X   R                  S   :w  a8  [        S
R                  XqU   R                  S   UR                  S   5      5      eSX   ;  a4  [        R                   " X   SS5      X'   [        R                   " USS5      n[#        U5      n	X   R                  S   S:”  aÇ  [        R$                  " X   S:H  5      R'                  5       n
SXŠ   -
  n[)        X-  5      n[+        XUS9nUR-                  U5        X   S:g  nXŽ   nU[        R                  " U5      -  n[        R.                  " UR1                  5       U	R3                  US95      nUR-                  X   U   U   5        UR5                  [        U5      5        GM¼     [6        R8                  " XEU4U [        U5      4[(        S9$ )a¤  Generate a sparse random matrix given column class distributions

Parameters
----------
n_samples : int,
    Number of samples to draw in each column.

classes : list of size n_outputs of arrays of size (n_classes,)
    List of classes for each column.

class_probability : list of size n_outputs of arrays of         shape (n_classes,), default=None
    Class distribution of each column. If None, uniform distribution is
    assumed.

random_state : int, RandomState instance or None, default=None
    Controls the randomness of the sampled classes.
    See :term:`Glossary <random_state>`.

Returns
-------
random_matrix : sparse csc matrix of size (n_samples, n_outputs)

Úir   zclass dtype %s is not supportedF)Úcopy)Úshaper   g      ð?z2Probability array at index {0} does not sum to onezXclasses[{0}] (length {1}) and class_probability[{0}] (length {2}) have different length.g        )Ún_populationÚ	n_samplesÚrandom_state)Úsize)Údtype)ÚarrayÚrangeÚlenÚnpÚasarrayr   ÚkindÚ
ValueErrorÚastypeÚint64Úemptyr	   ÚfillÚiscloseÚsumÚformatÚinsertr   ÚflatnonzeroÚitemÚintr   ÚextendÚsearchsortedÚcumsumÚuniformÚappendÚspÚ
csc_matrix)r   ÚclassesÚclass_probabilityr   ÚdataÚindicesÚindptrÚjÚclass_prob_jÚrngÚindex_class_0Ú	p_nonzeroÚnnzÚ
ind_sampleÚclasses_j_nonzeroÚclass_probability_nzÚclass_probability_nz_normÚclasses_inds                     ÚW/srv/projetos/modelo_ml_acdoc/venv/lib/python3.13/site-packages/sklearn/utils/random.pyÚ_random_choice_cscr9      sÞ  € ô2 �;Š;�sÓ€DÜ�kŠk˜#Ó€GÜ�[Š[˜˜q˜cÓ"€Fä”3�w“<× ˆÜ—Z’Z ¡
Ó+ˆ‰
Ø‰:×Ñ× Ñ  CÓ'ÜÐ>ÀÁ×AQÑAQÑQÓRÐRØ‘Z×&Ñ&¤r§x¡x°eÐ&Ð<ˆ‰
ð Ñ$ÜŸ8š8¨'©*×*:Ñ*:¸1Ñ*=Ñ>ˆLØ×Ñ˜a '¡*×"2Ñ"2°1Ñ"5Ñ5Õ6äŸ:š:Ð&7Ñ&:Ó;ˆLä�zŠzœ"Ÿ&š& Ó.°×4Ñ4ÜØD×KÑKÈAÓNóð ð ×Ñ˜aÑ  G¡J×$4Ñ$4°QÑ$7Ó7Üð$ç$*¡FØ˜q‘z×'Ñ'¨Ñ*¨L×,>Ñ,>¸qÑ,Aó%óð ð �G‘JÓÜŸš 7¡:¨q°!Ó4ˆG‰JÜŸ9š9 \°1°cÓ:ˆLô ! Ó.ˆØ‰:×Ñ˜AÑ Ó"ÜŸNšN¨7©:¸©?Ó;×@Ñ@ÓBˆMØ˜LÑ7Ñ7ˆIÜ�iÑ+Ó,ˆCÜ3Ø&ÀLñˆJð �N‰N˜:Ô&ð !(¡
¨a¡ÐØ#/Ñ#BÐ Ø(<¼r¿vºvØ$ó@ñ )Ð%ô Ÿ/š/Ø)×0Ñ0Ó2°C·K±KÀS°KÐ4IóˆKð �K‰K˜™
Ð#4Ñ5°kÑBÔCØ�‰”c˜'“l×#ñk !ôn �=Š=˜$¨Ð0°9¼cÀ'»lÐ2KÔSVÑWÐWó    )NN)Ú__doc__r   Únumpyr   Úscipy.sparseÚsparser&   Ú r   Ú_randomr   Ú__all__r9   © r:   r8   Ú<module>rC      s(   ðÙ $ó
 ã Ý å  Ý /à'Ð
(€õTXr:   