

'''simple docstring'''



from __future__ import annotations

import math

import numpy as np
from numpy.linalg import norm
def 						__lowerCamelCase	(       __snake_case					:		np.ndarray,		__snake_case					:		np.ndarray	)	->							float:






						"""simple docstring"""





						return math.sqrt(sum(pow(a - b,		2	) for a, b in zip(__snake_case,		__snake_case	)	)	)
def 						__lowerCamelCase	(       __snake_case					:		np.ndarray,		__snake_case					:		np.ndarray	)	->							list[list[list[float] | float]]:






						"""simple docstring"""





						if dataset.ndim != value_array.ndim:
												A__					:       Optional[int]     =(
												    """Wrong input data's dimensions... """
												    f"dataset : {dataset.ndim}, value_array : {value_array.ndim}"
												)
												raise ValueError(__snake_case	)

						try:
												if dataset.shape[1] != value_array.shape[1]:
																		A__					:       Tuple     =(
																		    """Wrong input data's shape... """
																		    f"dataset : {dataset.shape[1]}, value_array : {value_array.shape[1]}"
																		)
																		raise ValueError(__snake_case	)
						except IndexError:
												if dataset.ndim != value_array.ndim:
																		raise TypeError("""Wrong shape"""	)

						if dataset.dtype != value_array.dtype:
												A__					:       int     =(
												    """Input data have different datatype... """
												    f"dataset : {dataset.dtype}, value_array : {value_array.dtype}"
												)
												raise TypeError(__snake_case	)

						A__					:       Tuple     =[]

						for value in value_array:
												A__					:       List[Any]     =euclidean(__snake_case,		dataset[0]	)
												A__					:       List[str]     =dataset[0].tolist()

												for dataset_value in dataset[1:]:
																		A__					:       Optional[int]     =euclidean(__snake_case,		__snake_case	)

																		if dist > temp_dist:
																								A__					:       Optional[int]     =temp_dist
																								A__					:       Any     =dataset_value.tolist()

												answer.append([vector, dist]	)

						return answer
def 						__lowerCamelCase	(       __snake_case					:		np.ndarray,		__snake_case					:		np.ndarray	)	->							float:






						"""simple docstring"""





						return np.dot(__snake_case,		__snake_case	) / (norm(__snake_case	) * norm(__snake_case	))


if __name__ == "__main__":
		import doctest

		doctest.testmod()




'''simple docstring'''



from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def 						__lowerCamelCase	(       __snake_case					:		int	)	->							int:






						"""simple docstring"""





						A__					:       List[Any]     =prime_factors(__snake_case	)
						if is_square_free(__snake_case	):
												return -1 if len(__snake_case	) % 2 else 1
						return 0


if __name__ == "__main__":
		import doctest

		doctest.testmod()

