





'''simple docstring'''


from __future__ import annotations


def 						__a(SCREAMING_SNAKE_CASE_	:       list[int | float]		,							SCREAMING_SNAKE_CASE_	:       int		,							SCREAMING_SNAKE_CASE_	:       int     ):



    '''simple docstring'''





    if len(SCREAMING_SNAKE_CASE_     ) == 0:
        raise ValueError("find_max() arg is an empty sequence"     )
    if (
        left >= len(SCREAMING_SNAKE_CASE_     )
        or left < -len(SCREAMING_SNAKE_CASE_     )
        or right >= len(SCREAMING_SNAKE_CASE_     )
        or right < -len(SCREAMING_SNAKE_CASE_     )
    ):
        raise IndexError("list index out of range"     )
    if left == right:
        return nums[left]
    _lowerCAmelCase						      =   (left + right) >> 1  # the middle
    _lowerCAmelCase						      =   find_max(SCREAMING_SNAKE_CASE_		,							SCREAMING_SNAKE_CASE_		,							SCREAMING_SNAKE_CASE_     )  # find max in range[left, mid]
    _lowerCAmelCase						      =   find_max(SCREAMING_SNAKE_CASE_		,							mid + 1		,							SCREAMING_SNAKE_CASE_     )  # find max in range[mid + 1, right]

    return left_max if left_max >= right_max else right_max


if __name__ == "__main__":
       import doctest

       doctest.testmod(verbose=True)






"""simple docstring"""


from __future__ import annotations

import math

import numpy as np
from numpy.linalg import norm


def _lowerCamelCase      (						_UpperCamelCase       ,					_UpperCamelCase ):

			'''simple docstring'''




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


def _lowerCamelCase      (						_UpperCamelCase       ,					_UpperCamelCase ):

			'''simple docstring'''




			if dataset.ndim != value_array.ndim:
						__lowerCAmelCase							       =     (
						    "Wrong input data's dimensions... "
						    f"dataset : {dataset.ndim}, value_array : {value_array.ndim}"
						)
						raise ValueError(_UpperCamelCase )

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

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

			__lowerCAmelCase							       =     []

			for value in value_array:
						__lowerCAmelCase							       =     euclidean(_UpperCamelCase       ,					dataset[0] )
						__lowerCAmelCase							       =     dataset[0].tolist()

						for dataset_value in dataset[1:]:
									__lowerCAmelCase							       =     euclidean(_UpperCamelCase       ,					_UpperCamelCase )

									if dist > temp_dist:
												__lowerCAmelCase							       =     temp_dist
												__lowerCAmelCase							       =     dataset_value.tolist()

						answer.append([vector, dist] )

			return answer


def _lowerCamelCase      (						_UpperCamelCase       ,					_UpperCamelCase ):

			'''simple docstring'''




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


if __name__ == "__main__":
	import doctest

	doctest.testmod()




