



from __future__ import annotations

a_   :List[str]        =      [
    [-1, 0],  # left
    [0, -1],  # down
    [1, 0],  # right
    [0, 1],  # up
]
def        lowercase_							(A : Tuple		,					A : str		,					A : List[Any]		,					A : Dict		,					A : Any		,					):
       snake_case__							:	Dict   	=	[
           [0 for col in range(len(grid[0]      )      )] for row in range(len(__snake_case      )      )
       ]  # the reference grid
       snake_case__							:	Dict   	=	1
       snake_case__							:	int   	=	[
           [0 for col in range(len(grid[0]      )      )] for row in range(len(__snake_case      )      )
       ]  # the action grid

       snake_case__							:	int   	=	init[0]
       snake_case__							:	Optional[int]   	=	init[1]
       snake_case__							:	str   	=	0
       snake_case__							:	List[Any]   	=	g + heuristic[x][y]  # cost from starting cell to destination cell
       snake_case__							:	Optional[int]   	=	[[f, g, x, y]]

       snake_case__							:	Optional[Any]   	=	False  # flag that is set when search is complete
       snake_case__							:	int   	=	False  # flag set if we can't find expand

       while not found and not resign:
              if len(__snake_case      ) == 0:
                     raise ValueError('Algorithm is unable to find solution'      )
              else:  # to choose the least costliest action so as to move closer to the goal
                     cell.sort()
                     cell.reverse()
                     snake_case__							:	Dict   	=	cell.pop()
                     snake_case__							:	Optional[Any]   	=	next_cell[2]
                     snake_case__							:	List[Any]   	=	next_cell[3]
                     snake_case__							:	int   	=	next_cell[1]

                     if x == goal[0] and y == goal[1]:
                            snake_case__							:	List[str]   	=	True
                     else:
                            for i in range(len(__snake_case      )      ):  # to try out different valid actions
                                   snake_case__							:	str   	=	x + DIRECTIONS[i][0]
                                   snake_case__							:	List[str]   	=	y + DIRECTIONS[i][1]
                                   if xa >= 0 and xa < len(__snake_case      ) and ya >= 0 and ya < len(grid[0]      ):
                                          if closed[xa][ya] == 0 and grid[xa][ya] == 0:
                                                 snake_case__							:	List[str]   	=	g + cost
                                                 snake_case__							:	Optional[int]   	=	ga + heuristic[xa][ya]
                                                 cell.append([fa, ga, xa, ya]      )
                                                 snake_case__							:	Any   	=	1
                                                 snake_case__							:	List[Any]   	=	i
       snake_case__							:	Any   	=	[]
       snake_case__							:	List[str]   	=	goal[0]
       snake_case__							:	str   	=	goal[1]
       invpath.append([x, y]      )  # we get the reverse path from here
       while x != init[0] or y != init[1]:
              snake_case__							:	List[str]   	=	x - DIRECTIONS[action[x][y]][0]
              snake_case__							:	List[str]   	=	y - DIRECTIONS[action[x][y]][1]
              snake_case__							:	List[Any]   	=	xa
              snake_case__							:	str   	=	ya
              invpath.append([x, y]      )

       snake_case__							:	Any   	=	[]
       for i in range(len(__snake_case      )      ):
              path.append(invpath[len(__snake_case      ) - 1 - i]      )
       return path, action


if __name__ == "__main__":
 a_   :int        =      [
     [0, 1, 0, 0, 0, 0],
     [0, 1, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
     [0, 1, 0, 0, 0, 0],
     [0, 1, 0, 0, 1, 0],
     [0, 0, 0, 0, 1, 0],
 ]

 a_   :Union[str, Any]        =      [0, 0]
 # all coordinates are given in format [y,x]
 a_   :Any        =      [len(grid) - 1, len(grid[0]) - 1]
 a_   :str        =      1

 # the cost map which pushes the path closer to the goal
 a_   :int        =      [[0 for row in range(len(grid[0]))] for col in range(len(grid))]
 for i in range(len(grid)):
  for j in range(len(grid[0])):
   a_   :int        =      abs(i - goal[0]) + abs(j - goal[1])
   if grid[i][j] == 1:
    # added extra penalty in the heuristic map
    a_   :Any        =      99

 a_  ,						a_   :Optional[Any]        =      search(grid, init, goal, cost, heuristic)

 print("ACTION MAP")
 for i in range(len(action)):
  print(action[i])

 for i in range(len(path)):
  print(path[i])













def lowerCAmelCase__(__snake_case							)				->      list:







	'''simple docstring'''







	lowerCamelCase__								=		len(__snake_case							)
	for _ in range(__snake_case							):
		for i in range(_ % 2       ,arr_size - 1       ,2							):
			if arr[i + 1] < arr[i]:
				lowerCamelCase__				,	lowerCamelCase__								=		arr[i + 1], arr[i]

	return arr


if __name__ == "__main__":
			_a 						=      list(range(10, 0, -1))
			print(f"""Original: {arr}. Sorted: {odd_even_transposition(arr)}""")



