

from __future__ import annotations

class 				a  :


						def __init__(       self						,					A_	):







										'''simple docstring'''


										_UpperCAmelCase       :		Optional[Any] 		=    order

										# a_{0} ... a_{k}
										_UpperCAmelCase       :		Tuple 		=    [1.0] + [0.0] * order
										# b_{0} ... b_{k}
										_UpperCAmelCase       :		Dict 		=    [1.0] + [0.0] * order

										# x[n-1] ... x[n-k]
										_UpperCAmelCase       :		int 		=    [0.0] * self.order
										# y[n-1] ... y[n-k]
										_UpperCAmelCase       :		int 		=    [0.0] * self.order


						def        _UpperCAmelCase				(       self						,					A_						,					A_	):







										'''simple docstring'''


										if len(A_	) < self.order:
														_UpperCAmelCase       :		Dict 		=    [1.0, *a_coeffs]

										if len(A_	) != self.order + 1:
														_UpperCAmelCase       :		List[str] 		=    (
														    f'Expected a_coeffs to have {self.order + 1} elements '
														    f'for {self.order}-order filter, got {len(A_	)}'
														)
														raise ValueError(A_	)

										if len(A_	) != self.order + 1:
														_UpperCAmelCase       :		int 		=    (
														    f'Expected b_coeffs to have {self.order + 1} elements '
														    f'for {self.order}-order filter, got {len(A_	)}'
														)
														raise ValueError(A_	)

										_UpperCAmelCase       :		int 		=    a_coeffs
										_UpperCAmelCase       :		List[Any] 		=    b_coeffs





						def        _UpperCAmelCase				(       self						,					A_	):







										'''simple docstring'''


										_UpperCAmelCase       :		Any 		=    0.0

										# Start at index 1 and do index 0 at the end.
										for i in range(1						,					self.order + 1	):
														result += (
														    self.b_coeffs[i] * self.input_history[i - 1]
														    - self.a_coeffs[i] * self.output_history[i - 1]
														)

										_UpperCAmelCase       :		Any 		=    (result + self.b_coeffs[0] * sample) / self.a_coeffs[0]

										_UpperCAmelCase       :		str 		=    self.input_history[:-1]
										_UpperCAmelCase       :		Optional[Any] 		=    self.output_history[:-1]

										_UpperCAmelCase       :		Dict 		=    sample
										_UpperCAmelCase       :		int 		=    result

										return result





from __future__ import annotations

import numpy as np

def 							__SCREAMING_SNAKE_CASE							(				lowerCAmelCase:  list[float] )   ->       Dict:
				return np.maximum(0  ,      lowerCAmelCase )


if __name__ == "__main__":
					print(np.array(relu([-1, 0, 5])))  # --> [0, 0, 5]


