


"""simple docstring"""


from random import randint
from tempfile import TemporaryFile

import numpy as np






def      a__ (				__lowercase     ,			__lowercase     ,			__lowercase   )	->	str:
				_A					  =			0
				if start < end:
								_A					  =			randint(__UpperCamelCase     ,			__UpperCamelCase   )
								_A					  =			a[end]
								_A					  =			a[pivot]
								_A					  =			temp

								_A  ,		_A					  =			_in_place_partition(__UpperCamelCase     ,			__UpperCamelCase     ,			__UpperCamelCase   )
								count += _in_place_quick_sort(__UpperCamelCase     ,			__UpperCamelCase     ,			p - 1   )
								count += _in_place_quick_sort(__UpperCamelCase     ,			p + 1     ,			__UpperCamelCase   )
				return count






def      a__ (				__lowercase     ,			__lowercase     ,			__lowercase   )	->	List[Any]:
				_A					  =			0
				_A					  =			randint(__UpperCamelCase     ,			__UpperCamelCase   )
				_A					  =			a[end]
				_A					  =			a[pivot]
				_A					  =			temp
				_A					  =			start - 1
				for index in range(__UpperCamelCase     ,			__UpperCamelCase   ):
								count += 1
								if a[index] < a[end]:  # check if current val is less than pivot value
												_A					  =			new_pivot_index + 1
												_A					  =			a[new_pivot_index]
												_A					  =			a[index]
												_A					  =			temp

				_A					  =			a[new_pivot_index + 1]
				_A					  =			a[end]
				_A					  =			temp
				return new_pivot_index + 1, count


a_       							=    TemporaryFile()
a_       							=    1_00  # 1000 elements are to be sorted


a_							,     a_       							=    0, 1  # mean and standard deviation
a_       							=    np.random.normal(mu, sigma, p)
np.save(outfile, X)
print("The array is")
print(X)


outfile.seek(0)  # using the same array
a_       							=    np.load(outfile)
a_       							=    len(M) - 1
a_       							=    _in_place_quick_sort(M, 0, r)

print(
    "No of Comparisons for 100 elements selected from a standard normal distribution"
    "is :"
)




print(z)






"""simple docstring"""


from __future__ import annotations






def      a__ (				__lowercase     ,			__lowercase   )	->	float:
				_A					  =			sorted(numsa + numsa   )
				_A  ,		_A					  =			divmod(len(__lowercase   )     ,			2   )
				if mod == 1:
								return all_numbers[div]
				else:
								return (all_numbers[div] + all_numbers[div - 1]) / 2


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		a_       							=    [float(x) for x in input("Enter the elements of first array: ").split()]
		a_       							=    [float(x) for x in input("Enter the elements of second array: ").split()]
		print(f'''The median of two arrays is: {median_of_two_arrays(array_a, array_a)}''')