




"""simple docstring"""




import numpy as np







def       __UpperCAmelCase      (				__UpperCamelCase					,							__UpperCamelCase					):
			__lowercase	:       Tuple				=   np.array(_lowerCamelCase					)
			__lowercase	:       str				=   np.array(_lowerCamelCase					)

			__lowercase	:       Optional[Any]				=   abs(predict - actual					)
			__lowercase	:       Any				=   difference.mean()

			return score







def       __UpperCAmelCase      (				__UpperCamelCase					,							__UpperCamelCase					):
			__lowercase	:       Tuple				=   np.array(_lowerCamelCase					)
			__lowercase	:       List[Any]				=   np.array(_lowerCamelCase					)

			__lowercase	:       List[Any]				=   predict - actual
			__lowercase	:       Optional[Any]				=   np.square(_lowerCamelCase					)

			__lowercase	:       Tuple				=   square_diff.mean()
			return score







def       __UpperCAmelCase      (				__UpperCamelCase					,							__UpperCamelCase					):
			__lowercase	:       List[Any]				=   np.array(_lowerCamelCase					)
			__lowercase	:       int				=   np.array(_lowerCamelCase					)

			__lowercase	:       Dict				=   predict - actual
			__lowercase	:       Optional[int]				=   np.square(_lowerCamelCase					)
			__lowercase	:       Tuple				=   square_diff.mean()
			__lowercase	:       int				=   np.sqrt(_lowerCamelCase					)
			return score







def       __UpperCAmelCase      (				__UpperCamelCase					,							__UpperCamelCase					):
			__lowercase	:       str				=   np.array(_lowerCamelCase					)
			__lowercase	:       Optional[Any]				=   np.array(_lowerCamelCase					)

			__lowercase	:       Optional[int]				=   np.log(predict + 1					)
			__lowercase	:       int				=   np.log(actual + 1					)

			__lowercase	:       Tuple				=   log_predict - log_actual
			__lowercase	:       int				=   np.square(_lowerCamelCase					)
			__lowercase	:       Union[str, Any]				=   square_diff.mean()

			__lowercase	:       str				=   np.sqrt(_lowerCamelCase					)

			return score







def       __UpperCAmelCase      (				__UpperCamelCase					,							__UpperCamelCase					):
			__lowercase	:       Tuple				=   np.array(_lowerCamelCase					)
			__lowercase	:       Tuple				=   np.array(_lowerCamelCase					)

			__lowercase	:       List[Any]				=   predict - actual
			__lowercase	:       str				=   np.sum(_lowerCamelCase					) / len(_lowerCamelCase					)
			__lowercase	:       Tuple				=   np.sum(_lowerCamelCase					) / len(_lowerCamelCase					)
			# print(numerator, denumerator)
			__lowercase	:       int				=   float(_lowerCamelCase					) / denumerator * 1_00

			return score







def       __UpperCAmelCase      (				__UpperCamelCase					,							__UpperCamelCase					):
			return np.mean(np.array(_lowerCamelCase					) == np.array(_lowerCamelCase					)					)









"""simple docstring"""




from collections.abc import Callable

a_            =   Callable[[float], float]  # type alias for a real -> real function







def       __UpperCAmelCase      (				__UpperCamelCase					,							__UpperCamelCase					,							__UpperCamelCase					,							):
			__lowercase	:       str				=   float(__UpperCamelCase					)
			while True:
						try:
									__lowercase	:       Dict				=   prev_guess - function(__UpperCamelCase					) / derivative(__UpperCamelCase					)
						except ZeroDivisionError:
									raise ZeroDivisionError('''Could not find root'''					) from None
						if abs(prev_guess - next_guess					) < 10**-5:
									return next_guess
						__lowercase	:       List[Any]				=   next_guess







def       __UpperCAmelCase      (				__UpperCamelCase					):
			return (x**3) - (2 * x) - 5







def       __UpperCAmelCase      (				__UpperCamelCase					):
			return 3 * (x**2) - 2


if __name__ == "__main__":
			print(newton(f, fa, 3))



