
import numpy as np




def     a						(							snake_case__: List[str]						,       snake_case__: Optional[Any]						,       snake_case__: Optional[int] ):


				'''simple docstring'''
				lowercase_					  = n_draws * class_counts / class_counts.sum()
				# floored means we don't overshoot n_samples, but probably undershoot
				lowercase_					  = np.floor(snake_case__ )
				# we add samples according to how much "left over" probability
				# they had, until we arrive at n_samples
				lowercase_					  = int(n_draws - floored.sum() )
				if need_to_add > 0:
								lowercase_					  = continuous - floored
								lowercase_					  = np.sort(np.unique(snake_case__ ) )[::-1]
								# add according to remainder, but break ties
								# randomly to avoid biases
								for value in values:
												((lowercase_)  ,     )					  = 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
												lowercase_					  = min(len(snake_case__ )						,       snake_case__ )
												lowercase_					  = 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     a						(							snake_case__: Any						,       snake_case__: Dict						,       snake_case__: Optional[Any]						,       snake_case__: Tuple						,       snake_case__: int=10 ):


				'''simple docstring'''
				lowercase_  ,     lowercase_					  = np.unique(snake_case__						,       return_inverse=snake_case__ )
				lowercase_					  = classes.shape[0]
				lowercase_					  = 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) )
				lowercase_					  = np.split(np.argsort(snake_case__						,       kind='''mergesort''' )						,       np.cumsum(snake_case__ )[:-1] )
				for _ in range(snake_case__ ):
								lowercase_					  = approximate_mode(snake_case__						,       snake_case__						,       snake_case__ )
								lowercase_					  = class_counts - n_i
								lowercase_					  = approximate_mode(snake_case__						,       snake_case__						,       snake_case__ )

								lowercase_					  = []
								lowercase_					  = []

								for i in range(snake_case__ ):
												lowercase_					  = rng.permutation(class_counts[i] )
												lowercase_					  = 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]] )
								lowercase_					  = rng.permutation(snake_case__ )
								lowercase_					  = rng.permutation(snake_case__ )

								yield train, test






class 			lowercase__:



	"""simple docstring"""




	def __init__(	self  :      str	)	->					None:
					lowercase_					  = [0, 1]




	def 						_lowercase  (	self  :      str	,							SCREAMING_SNAKE_CASE_  :      int	)	->					list:
					if (difference := index - (len(self.sequence	) - 2)) >= 1:
									for _ in range(SCREAMING_SNAKE_CASE_	):
													self.sequence.append(self.sequence[-1] + self.sequence[-2]	)
					return self.sequence[:index]




def     a						(							):


				'''simple docstring'''
				print(
				    '''Fibonacci Series Using Dynamic Programming\n'''						,       '''Enter the index of the Fibonacci number you want to calculate '''						,       '''in the prompt below. (To exit enter exit or Ctrl-C)\n'''						,       sep=''''''						,       )
				lowercase_					  = Fibonacci()

				while True:
								lowercase_					  = input('''>> ''' )
								if prompt in {"exit", "quit"}:
												break

								try:
												lowercase_					  = int(snake_case__ )
								except ValueError:
												print('''Enter a number or \'exit\'''' )
												continue

								print(fibonacci.get(snake_case__ ) )


if __name__ == "__main__":
						main()




