


"""simple docstring"""


import numpy as np
class snake_case      :







		def __init__(					self      :       str		)       ->						int:





						'''simple docstring'''







						_A					  =			(0, 0)
						_A					  =			None
						_A					  =			0
						_A					  =			0
						_A					  =			0







		def __eq__(					self      :       Optional[Any]    ,   a__      :       Any		)       ->						Optional[Any]:





						'''simple docstring'''







						return self.position == cell.position







		def  a_ (					self      :       List[Any]		)       ->						Any:





						'''simple docstring'''







						print(self.position		)





class snake_case      :







		def __init__(					self      :       Union[str, Any]    ,   a__      :       Dict=(5, 5)		)       ->						List[str]:





						'''simple docstring'''







						_A					  =			np.zeros(a__		)
						_A					  =			world_size[0]
						_A					  =			world_size[1]







		def  a_ (					self      :       Any		)       ->						Optional[int]:





						'''simple docstring'''







						print(self.w		)







		def  a_ (					self      :       Any    ,   a__      :       Any		)       ->						Any:





						'''simple docstring'''







						_A					  =			[
						    (-1, -1),
						    (-1, 0),
						    (-1, 1),
						    (0, -1),
						    (0, 1),
						    (1, -1),
						    (1, 0),
						    (1, 1),
						]
						_A					  =			cell.position[0]
						_A					  =			cell.position[1]
						_A					  =			[]
						for n in neughbour_cord:
										_A					  =			current_x + n[0]
										_A					  =			current_y + n[1]
										if 0 <= x < self.world_x_limit and 0 <= y < self.world_y_limit:
														_A					  =			Cell()
														_A					  =			(x, y)
														_A					  =			cell
														neighbours.append(a__		)
						return neighbours






def      a__ (				__lowercase     ,			__lowercase     ,			__lowercase   )	->	List[str]:
				_A					  =			[]
				_A					  =			[]
				_open.append(__lowercase   )

				while _open:
								_A					  =			np.argmin([n.f for n in _open]   )
								_A					  =			_open[min_f]
								_closed.append(_open.pop(__lowercase   )   )
								if current == goal:
												break
								for n in world.get_neigbours(__lowercase   ):
												for c in _closed:
																if c == n:
																				continue
												_A					  =			current.g + 1
												_A  ,		_A					  =			n.position
												_A  ,		_A					  =			goal.position
												_A					  =			(ya - ya) ** 2 + (xa - xa) ** 2
												_A					  =			n.h + n.g

												for c in _open:
																if c == n and c.f < n.f:
																				continue
												_open.append(__lowercase   )
				_A					  =			[]
				while current.parent is not None:
								path.append(current.position   )
								_A					  =			current.parent
				path.append(current.position   )
				return path[::-1]


if __name__ == "__main__":
		a_       							=    Gridworld()
		# Start position and goal
		a_       							=    Cell()
		a_       							=    (0, 0)
		a_       							=    Cell()
		a_       							=    (4, 4)
		print(f'''path from {start.position} to {goal.position}''')
		a_       							=    astar(world, start, goal)
		#   Just for visual reasons.
		for i in s:
				a_       							=    1
		print(world.w)



"""simple docstring"""


def      a__ (				__lowercase     ,			__lowercase     ,			__lowercase     ,			__lowercase   )	->	str:
				# Return True if there is node that has not iterated.
				_A					  =			[False] * len(__lowercase   )
				_A					  =			[]
				queue.append(__lowercase   )
				_A					  =			True

				while queue:
								_A					  =			queue.pop(0   )
								for ind in range(len(graph[u]   )   ):
												if visited[ind] is False and graph[u][ind] > 0:
																queue.append(__lowercase   )
																_A					  =			True
																_A					  =			u

				return visited[t]






def      a__ (				__lowercase     ,			__lowercase     ,			__lowercase   )	->	int:
				# This array is filled by BFS and to store path
				_A					  =			[-1] * (len(__lowercase   ))
				_A					  =			0
				while bfs(__lowercase     ,			__lowercase     ,			__lowercase     ,			__lowercase   ):
								_A					  =			float("Inf"   )
								_A					  =			sink

								while s != source:
												# Find the minimum value in select path
												_A					  =			min(__lowercase     ,			graph[parent[s]][s]   )
												_A					  =			parent[s]

								max_flow += path_flow
								_A					  =			sink

								while v != source:
												_A					  =			parent[v]
												graph[u][v] -= path_flow
												graph[v][u] += path_flow
												_A					  =			parent[v]
				return max_flow


a_       							=    [
    [0, 16, 13, 0, 0, 0],
    [0, 0, 10, 12, 0, 0],
    [0, 4, 0, 0, 14, 0],
    [0, 0, 9, 0, 0, 20],
    [0, 0, 0, 7, 0, 4],
    [0, 0, 0, 0, 0, 0],
]

a_							,     a_       							=    0, 5




print(ford_fulkerson(graph, source, sink))