






from __future__ import annotations






def 					lowerCamelCase__					(_UpperCAmelCase = 4):
			SCREAMING_SNAKE_CASE							=			abs(_UpperCAmelCase) or 4
			return [[1 + x + y * row_size for x in range(_UpperCAmelCase)] for y in range(_UpperCAmelCase)]






def 					lowerCamelCase__					(_UpperCAmelCase):
			return reverse_row(transpose(_UpperCAmelCase))
			# OR.. transpose(reverse_column(matrix))






def 					lowerCamelCase__					(_UpperCAmelCase):
			return reverse_row(reverse_column(_UpperCAmelCase))
			# OR.. reverse_column(reverse_row(matrix))






def 					lowerCamelCase__					(_UpperCAmelCase):
			return reverse_column(transpose(_UpperCAmelCase))
			# OR.. transpose(reverse_row(matrix))






def 					lowerCamelCase__					(_UpperCAmelCase):
			SCREAMING_SNAKE_CASE							=			[list(_UpperCAmelCase) for x in zip(*_UpperCAmelCase)]
			return matrix






def 					lowerCamelCase__					(_UpperCAmelCase):
			SCREAMING_SNAKE_CASE							=			matrix[::-1]
			return matrix






def 					lowerCamelCase__					(_UpperCAmelCase):
			SCREAMING_SNAKE_CASE							=			[x[::-1] for x in matrix]
			return matrix






def 					lowerCamelCase__					(_UpperCAmelCase):
			for i in matrix:
						print(*_UpperCAmelCase)


if __name__ == "__main__":
				a_		:    Optional[Any]   							=     make_matrix()
				print('\norigin:\n')
				print_matrix(matrix)
				print('\nrotate 90 counterclockwise:\n')
				print_matrix(rotate_aa(matrix))

				a_		:    Any   							=     make_matrix()
				print('\norigin:\n')
				print_matrix(matrix)
				print('\nrotate 180:\n')
				print_matrix(rotate_aaa(matrix))

				a_		:    List[str]   							=     make_matrix()
				print('\norigin:\n')
				print_matrix(matrix)
				print('\nrotate 270 counterclockwise:\n')
				print_matrix(rotate_aaa(matrix))









'''simple docstring'''

from random import randint
from tempfile import TemporaryFile

import numpy as np







def a_     (    __UpperCAmelCase				,							__UpperCAmelCase				,							__UpperCAmelCase					)				->					int:





			"""simple docstring"""







			snake_case:    int      							=0
			if start < end:
						snake_case:    Tuple      							=randint(__UpperCAmelCase				,							__UpperCAmelCase					)
						snake_case:    Optional[Any]      							=a[end]
						snake_case:    List[Any]      							=a[pivot]
						snake_case:    int      							=temp

						snake_case							,  snake_case:    Optional[int]      							=_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_     (    __UpperCAmelCase				,							__UpperCAmelCase				,							__UpperCAmelCase					)				->					Optional[int]:





			"""simple docstring"""







			snake_case:    Tuple      							=0
			snake_case:    Tuple      							=randint(__UpperCAmelCase				,							__UpperCAmelCase					)
			snake_case:    List[Any]      							=a[end]
			snake_case:    List[str]      							=a[pivot]
			snake_case:    Dict      							=temp
			snake_case:    Union[str, Any]      							=start - 1
			for index in range(__UpperCAmelCase				,							__UpperCAmelCase					):
						count += 1
						if a[index] < a[end]:  # check if current val is less than pivot value
									snake_case:    Optional[Any]      							=new_pivot_index + 1
									snake_case:    Dict      							=a[new_pivot_index]
									snake_case:    Union[str, Any]      							=a[index]
									snake_case:    List[Any]      							=temp

			snake_case:    Union[str, Any]      							=a[new_pivot_index + 1]
			snake_case:    Tuple      							=a[end]
			snake_case:    Union[str, Any]      							=temp
			return new_pivot_index + 1, count


a							   =				TemporaryFile()
a							   =				100  # 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)




