






'''simple docstring'''




def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__						)->    int:



			"""simple docstring"""



			while a != 0:
						snake_case_,	snake_case_				:					Any   =       b % a, a
			return b






def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__						)->    int:



			"""simple docstring"""



			if gcd(__magic_name__     ,__magic_name__						) != 1:
						snake_case_				:					List[Any]   =       F'''mod inverse of {a!r} and {m!r} does not exist'''
						raise ValueError(__magic_name__						)
			snake_case_,	snake_case_,	snake_case_				:					int   =       1, 0, a
			snake_case_,	snake_case_,	snake_case_				:					Tuple   =       0, 1, m
			while va != 0:
						snake_case_				:					int   =       ua // va
						snake_case_,	snake_case_,	snake_case_,	snake_case_,	snake_case_,	snake_case_				:					Tuple   =       (ua - q * va), (ua - q * va), (ua - q * va), va, va, va
			return ua % m












'''simple docstring'''




from __future__ import annotations

import math

import numpy as np
from numpy.linalg import norm

def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__						)->    float:



			"""simple docstring"""



			return math.sqrt(sum(pow(a - b     ,2						) for a, b in zip(__magic_name__     ,__magic_name__						)						)						)

def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__						)->    list[list[list[float] | float]]:



			"""simple docstring"""



			if dataset.ndim != value_array.ndim:
						snake_case_				:					int   =       (
						    "Wrong input data's dimensions... "
						    F'''dataset : {dataset.ndim}, value_array : {value_array.ndim}'''
						)
						raise ValueError(__magic_name__						)

			try:
						if dataset.shape[1] != value_array.shape[1]:
									snake_case_				:					Dict   =       (
									    "Wrong input data's shape... "
									    F'''dataset : {dataset.shape[1]}, value_array : {value_array.shape[1]}'''
									)
									raise ValueError(__magic_name__						)
			except IndexError:
						if dataset.ndim != value_array.ndim:
									raise TypeError("Wrong shape"						)

			if dataset.dtype != value_array.dtype:
						snake_case_				:					Dict   =       (
						    "Input data have different datatype... "
						    F'''dataset : {dataset.dtype}, value_array : {value_array.dtype}'''
						)
						raise TypeError(__magic_name__						)

			snake_case_				:					Optional[int]   =       []

			for value in value_array:
						snake_case_				:					List[str]   =       euclidean(__magic_name__     ,dataset[0]						)
						snake_case_				:					int   =       dataset[0].tolist()

						for dataset_value in dataset[1:]:
									snake_case_				:					Optional[Any]   =       euclidean(__magic_name__     ,__magic_name__						)

									if dist > temp_dist:
												snake_case_				:					Tuple   =       temp_dist
												snake_case_				:					Optional[int]   =       dataset_value.tolist()

						answer.append([vector, dist]						)

			return answer

def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__						)->    float:



			"""simple docstring"""



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


if __name__ == "__main__":
		import doctest

		doctest.testmod()




