

import numpy as np





def    _snake_case		(snake_case_				:    Union[str, Any]						,					snake_case_				:    int						,					snake_case_				:    Optional[int]     )       ->		Union[str, Any]:
  __UpperCAmelCase  :     Optional[int]		=    n_draws * class_counts / class_counts.sum()
  # floored means we don't overshoot n_samples, but probably undershoot
  __UpperCAmelCase  :     List[str]		=    np.floor(snake_case_     )
  # we add samples according to how much "left over" probability
  # they had, until we arrive at n_samples
  __UpperCAmelCase  :     int		=    int(n_draws - floored.sum()     )
  if need_to_add > 0:
    __UpperCAmelCase  :     Any		=    continuous - floored
    __UpperCAmelCase  :     Any		=    np.sort(np.unique(snake_case_     )     )[::-1]
    # add according to remainder, but break ties
    # randomly to avoid biases
    for value in values:
      ((__UpperCAmelCase), )  :     Tuple		=    np.where(remainder == value     )
      # if we need_to_add less than what's in inds
      # we draw randomly from them.
      # if we need to add more, we add them all and
      # go to the next value
      __UpperCAmelCase  :     Dict		=    min(len(snake_case_     )						,					snake_case_     )
      __UpperCAmelCase  :     str		=    rng.choice(snake_case_						,					size=snake_case_						,					replace=snake_case_     )
      floored[inds] += 1
      need_to_add -= add_now
      if need_to_add == 0:
        break
  return floored.astype(np.intaa     )







def    _snake_case		(snake_case_				:    Optional[int]						,					snake_case_				:    Union[str, Any]						,					snake_case_				:    Union[str, Any]						,					snake_case_				:    Dict						,					snake_case_				:    Tuple=10     )       ->		str:
  __UpperCAmelCase, __UpperCAmelCase  :     Optional[Any]		=    np.unique(snake_case_						,					return_inverse=snake_case_     )
  __UpperCAmelCase  :     Optional[Any]		=    classes.shape[0]
  __UpperCAmelCase  :     List[Any]		=    np.bincount(snake_case_     )
  if np.min(snake_case_     ) < 2:
    raise ValueError('Minimum class count error'     )
  if n_train < n_classes:
    raise ValueError(
        'The train_size = %d should be greater or ' 'equal to the number of classes = %d' % (n_train, n_classes)     )
  if n_test < n_classes:
    raise ValueError(
        'The test_size = %d should be greater or ' 'equal to the number of classes = %d' % (n_test, n_classes)     )
  __UpperCAmelCase  :     List[str]		=    np.split(np.argsort(snake_case_						,					kind='mergesort'     )						,					np.cumsum(snake_case_     )[:-1]     )
  for _ in range(snake_case_     ):
    __UpperCAmelCase  :     Optional[int]		=    approximate_mode(snake_case_						,					snake_case_						,					snake_case_     )
    __UpperCAmelCase  :     int		=    class_counts - n_i
    __UpperCAmelCase  :     Tuple		=    approximate_mode(snake_case_						,					snake_case_						,					snake_case_     )

    __UpperCAmelCase  :     str		=    []
    __UpperCAmelCase  :     Any		=    []

    for i in range(snake_case_     ):
      __UpperCAmelCase  :     int		=    rng.permutation(class_counts[i]     )
      __UpperCAmelCase  :     Dict		=    class_indices[i].take(snake_case_						,					mode='clip'     )
      train.extend(perm_indices_class_i[: n_i[i]]     )
      test.extend(perm_indices_class_i[n_i[i] : n_i[i] + t_i[i]]     )
    __UpperCAmelCase  :     Optional[int]		=    rng.permutation(snake_case_     )
    __UpperCAmelCase  :     Union[str, Any]		=    rng.permutation(snake_case_     )

    yield train, test








from __future__ import annotations

from collections.abc import Iterable
from dataclasses import dataclass
from typing import Any


class     lowerCamelCase_   :
 _lowerCAmelCase       		=  ('''_front''', '''_back''', '''_len''')


 @dataclass
 class     lowerCamelCase_   :
  _lowerCAmelCase       		=  None
  _lowerCAmelCase       		=  None
  _lowerCAmelCase       		=  None



 class     lowerCamelCase_   :
  _lowerCAmelCase       		=  ('''_cur''',)




  def __init__( self     ,     _UpperCAmelCase       ):
    __UpperCAmelCase  :     Tuple		=    cur




  def __iter__( self       ):
    return self




  def 						a					( self       ):
    if self._cur is None:
      # finished iterating
      raise StopIteration
    __UpperCAmelCase  :     str		=    self._cur.val
    __UpperCAmelCase  :     Dict		=    self._cur.next_node

    return val




 def __init__( self     ,     _UpperCAmelCase = None       ):
   __UpperCAmelCase  :     Any		=    None
   __UpperCAmelCase  :     Any		=    None
   __UpperCAmelCase  :     int		=    0

   if iterable is not None:
     # append every value to the deque
     for val in iterable:
       self.append(_UpperCAmelCase       )




 def 						a					( self     ,     _UpperCAmelCase       ):
   __UpperCAmelCase  :     Optional[Any]		=    self._Node(_UpperCAmelCase     ,     _UpperCAmelCase     ,     _UpperCAmelCase       )
   if self.is_empty():
     # front = back
     __UpperCAmelCase  :     Dict		=    node
     __UpperCAmelCase  :     List[str]		=    1
   else:
     # connect nodes
     __UpperCAmelCase  :     Any		=    node
     __UpperCAmelCase  :     Tuple		=    self._back
     __UpperCAmelCase  :     Optional[Any]		=    node  # assign new back to the new node

     self._len += 1

     # make sure there were no errors
     assert not self.is_empty(), "Error on appending value."




 def 						a					( self     ,     _UpperCAmelCase       ):
   __UpperCAmelCase  :     Optional[Any]		=    self._Node(_UpperCAmelCase     ,     _UpperCAmelCase     ,     _UpperCAmelCase       )
   if self.is_empty():
     # front = back
     __UpperCAmelCase  :     str		=    node
     __UpperCAmelCase  :     List[str]		=    1
   else:
     # connect nodes
     __UpperCAmelCase  :     List[str]		=    self._front
     __UpperCAmelCase  :     Any		=    node
     __UpperCAmelCase  :     Dict		=    node  # assign new front to the new node

     self._len += 1

     # make sure there were no errors
     assert not self.is_empty(), "Error on appending value."




 def 						a					( self     ,     _UpperCAmelCase       ):
   for val in iterable:
     self.append(_UpperCAmelCase       )




 def 						a					( self     ,     _UpperCAmelCase       ):
   for val in iterable:
     self.appendleft(_UpperCAmelCase       )




 def 						a					( self       ):
   assert not self.is_empty(), "Deque is empty."

   __UpperCAmelCase  :     List[Any]		=    self._back
   __UpperCAmelCase  :     Optional[int]		=    self._back.prev_node  # set new back
   # drop the last node - python will deallocate memory automatically
   __UpperCAmelCase  :     int		=    None

   self._len -= 1

   return topop.val




 def 						a					( self       ):
   assert not self.is_empty(), "Deque is empty."

   __UpperCAmelCase  :     List[Any]		=    self._front
   __UpperCAmelCase  :     Union[str, Any]		=    self._front.next_node  # set new front and drop the first node
   __UpperCAmelCase  :     Union[str, Any]		=    None

   self._len -= 1

   return topop.val




 def 						a					( self       ):
   return self._front is None




 def __len__( self       ):
   return self._len




 def __eq__( self     ,     _UpperCAmelCase       ):

   if not isinstance(_UpperCAmelCase     ,     _UpperCAmelCase       ):
     return NotImplemented

   __UpperCAmelCase  :     List[str]		=    self._front
   __UpperCAmelCase  :     str		=    other._front

   # if the length of the dequeues are not the same, they are not equal
   if len(self       ) != len(_UpperCAmelCase       ):
     return False

   while me is not None and oth is not None:
     # compare every value
     if me.val != oth.val:
       return False
     __UpperCAmelCase  :     Any		=    me.next_node
     __UpperCAmelCase  :     str		=    oth.next_node

   return True




 def __iter__( self       ):
   return Deque._Iterator(self._front       )




 def __repr__( self       ):
   __UpperCAmelCase  :     int		=    []
   __UpperCAmelCase  :     Dict		=    self._front
   while aux is not None:
     # append the values in a list to display
     values_list.append(aux.val       )
     __UpperCAmelCase  :     List[str]		=    aux.next_node

   return F"[{', '.join(repr(_UpperCAmelCase       ) for val in values_list       )}]"


if __name__ == "__main__":
      import doctest

      doctest.testmod()





