




from random import randint
from tempfile import TemporaryFile

import numpy as np

def 			a   (_lowerCAmelCase  ,    _lowerCAmelCase  ,    _lowerCAmelCase     ):
							SCREAMING_SNAKE_CASE_   	=    0
							if start < end:
														SCREAMING_SNAKE_CASE_   	=    randint(_lowerCAmelCase  ,    _lowerCAmelCase     )
														SCREAMING_SNAKE_CASE_   	=    a[end]
														SCREAMING_SNAKE_CASE_   	=    a[pivot]
														SCREAMING_SNAKE_CASE_   	=    temp

														SCREAMING_SNAKE_CASE_   	=    _in_place_partition(_lowerCAmelCase  ,    _lowerCAmelCase  ,    _lowerCAmelCase     )
														count += _in_place_quick_sort(_lowerCAmelCase  ,    _lowerCAmelCase  ,    p - 1     )
														count += _in_place_quick_sort(_lowerCAmelCase  ,    p + 1  ,    _lowerCAmelCase     )
							return count

def 			a   (_lowerCAmelCase  ,    _lowerCAmelCase  ,    _lowerCAmelCase     ):
							SCREAMING_SNAKE_CASE_   	=    0
							SCREAMING_SNAKE_CASE_   	=    randint(_lowerCAmelCase  ,    _lowerCAmelCase     )
							SCREAMING_SNAKE_CASE_   	=    a[end]
							SCREAMING_SNAKE_CASE_   	=    a[pivot]
							SCREAMING_SNAKE_CASE_   	=    temp
							SCREAMING_SNAKE_CASE_   	=    start - 1
							for index in range(_lowerCAmelCase  ,    _lowerCAmelCase     ):
														count += 1
														if a[index] < a[end]:  # check if current val is less than pivot value
																					SCREAMING_SNAKE_CASE_   	=    new_pivot_index + 1
																					SCREAMING_SNAKE_CASE_   	=    a[new_pivot_index]
																					SCREAMING_SNAKE_CASE_   	=    a[index]
																					SCREAMING_SNAKE_CASE_   	=    temp

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


__SCREAMING_SNAKE_CASE 						=TemporaryFile()
__SCREAMING_SNAKE_CASE 						=100  # 1000 elements are to be sorted


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


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

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






print(z)






def 			a   (_lowerCAmelCase     ):
							if number > 0:
														raise ValueError('''input must be a negative integer'''     )
							SCREAMING_SNAKE_CASE_   	=    len(bin(_lowerCAmelCase     )[3:]     )
							SCREAMING_SNAKE_CASE_   	=    bin(abs(_lowerCAmelCase     ) - (1 << binary_number_length)     )[3:]
							SCREAMING_SNAKE_CASE_   	=    (
							    (
							        '''1'''
							        + '''0''' * (binary_number_length - len(_lowerCAmelCase     ))
							        + twos_complement_number
							    )
							    if number < 0
							    else '''0'''
							)
							return "0b" + twos_complement_number


if __name__ == "__main__":
			import doctest

			doctest.testmod()


