



from heapq import heappop, heappush

import numpy as np




def    _lowerCAmelCase  (	A__:      np.ndarray						,		A__:      tuple[int, int]						,		A__:      tuple[int, int]						,		A__:      bool						,		):


    '''simple docstring'''


    UpperCAmelCase      =       grid.shape
    UpperCAmelCase      =       [-1, 1, 0, 0]
    UpperCAmelCase      =       [0, 0, -1, 1]
    if allow_diagonal:
        dx += [-1, -1, 1, 1]
        dy += [-1, 1, -1, 1]

    UpperCAmelCase      =       [(0, source)], set()
    UpperCAmelCase      =       np.full((rows, cols)						,		np.inf						)
    UpperCAmelCase      =       0
    UpperCAmelCase      =       np.empty((rows, cols)						,		dtype=__UpperCAmelCase						)
    UpperCAmelCase      =       None

    while queue:
        (UpperCAmelCase)      =       heappop(__UpperCAmelCase						)
        if (x, y) in visited:
            continue
        visited.add((x, y)						)

        if (x, y) == destination:
            UpperCAmelCase      =       []
            while (x, y) != source:
                path.append((x, y)						)
                UpperCAmelCase      =       predecessors[x, y]
            path.append(__UpperCAmelCase						)  # add the source manually
            path.reverse()
            return matrix[destination], path

        for i in range(len(__UpperCAmelCase						)						):
            UpperCAmelCase      =       x + dx[i], y + dy[i]
            if 0 <= nx < rows and 0 <= ny < cols:
                UpperCAmelCase      =       grid[nx][ny]
                if next_node == 1 and matrix[nx, ny] > dist + 1:
                    heappush(__UpperCAmelCase						,		(dist + 1, (nx, ny))						)
                    UpperCAmelCase      =       dist + 1
                    UpperCAmelCase      =       (x, y)

    return np.inf, []


if __name__ == "__main__":
    import doctest

    doctest.testmod()












"""simple docstring"""





from random import randint
from tempfile import TemporaryFile

import numpy as np



def   a    (     __UpperCAmelCase      :    Optional[Any]      ,   __UpperCAmelCase      :    Optional[int]      ,   __UpperCAmelCase      :    Optional[int]  )    ->							int:
						__magic_name__:	Optional[int]							=       0
						if start < end:
												__magic_name__:	Union[str, Any]							=       randint(__UpperCAmelCase      ,   __UpperCAmelCase  )
												__magic_name__:	int							=       a[end]
												__magic_name__:	Optional[int]							=       a[pivot]
												__magic_name__:	Tuple							=       temp

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

						__magic_name__:	List[Any]							=       a[new_pivot_index + 1]
						__magic_name__:	Union[str, Any]							=       a[end]
						__magic_name__:	Dict							=       temp
						return new_pivot_index + 1, count


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


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


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

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

print(z)



