
from __future__ import annotations

SCREAMING_SNAKE_CASE__   :			Optional[Any]												=    list[tuple[int, int]]

SCREAMING_SNAKE_CASE__   :			Tuple												=    [
    [0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0],
    [1, 0, 1, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 1, 0, 0],
]

SCREAMING_SNAKE_CASE__   :			Optional[Any]												=    ([-1, 0], [0, -1], [1, 0], [0, 1])  # up, left, down, right

class    lowerCAmelCase__     :






		def __init__(		self		:							Optional[Any]							,			SCREAMING_SNAKE_CASE__		:							int							,			SCREAMING_SNAKE_CASE__		:							int							,			SCREAMING_SNAKE_CASE__		:							int							,			SCREAMING_SNAKE_CASE__		:							int							,			SCREAMING_SNAKE_CASE__		:							float							,			SCREAMING_SNAKE_CASE__		:							Node | None							,			)     ->							str:
						__lowerCamelCase    					=	pos_x
						__lowerCamelCase    					=	pos_y
						__lowerCamelCase    					=	(pos_y, pos_x)
						__lowerCamelCase    					=	goal_x
						__lowerCamelCase    					=	goal_y
						__lowerCamelCase    					=	g_cost
						__lowerCamelCase    					=	parent
						__lowerCamelCase    					=	self.calculate_heuristic()






		def  __A       (		self		:							Optional[int]  )     ->							float:
						__lowerCamelCase    					=	abs(self.pos_x - self.goal_x  )
						__lowerCamelCase    					=	abs(self.pos_y - self.goal_y  )
						return dx + dy







		def __lt__(		self		:							Dict							,			SCREAMING_SNAKE_CASE__		:							List[str]  )     ->							bool:
						return self.f_cost < other.f_cost





class    lowerCAmelCase__     :






		def __init__(		self		:							int							,			SCREAMING_SNAKE_CASE__		:							tuple[int, int]							,			SCREAMING_SNAKE_CASE__		:							tuple[int, int]  )     ->							str:
						__lowerCamelCase    					=	Node(start[1]							,			start[0]							,			goal[1]							,			goal[0]							,			0							,			SCREAMING_SNAKE_CASE__  )
						__lowerCamelCase    					=	Node(goal[1]							,			goal[0]							,			goal[1]							,			goal[0]							,			9_99_99							,			SCREAMING_SNAKE_CASE__  )

						__lowerCamelCase    					=	[self.start]
						__lowerCamelCase    					=	[]

						__lowerCamelCase    					=	False






		def  __A       (		self		:							Dict  )     ->							Path | None:
						while self.open_nodes:
										# Open Nodes are sorted using __lt__
										self.open_nodes.sort()
										__lowerCamelCase    					=	self.open_nodes.pop(0  )

										if current_node.pos == self.target.pos:
														__lowerCamelCase    					=	True
														return self.retrace_path(SCREAMING_SNAKE_CASE__  )

										self.closed_nodes.append(SCREAMING_SNAKE_CASE__  )
										__lowerCamelCase    					=	self.get_successors(SCREAMING_SNAKE_CASE__  )

										for child_node in successors:
														if child_node in self.closed_nodes:
																		continue

														if child_node not in self.open_nodes:
																		self.open_nodes.append(SCREAMING_SNAKE_CASE__  )
														else:
																		# retrieve the best current path
																		__lowerCamelCase    					=	self.open_nodes.pop(self.open_nodes.index(SCREAMING_SNAKE_CASE__  )  )

																		if child_node.g_cost < better_node.g_cost:
																						self.open_nodes.append(SCREAMING_SNAKE_CASE__  )
																		else:
																						self.open_nodes.append(SCREAMING_SNAKE_CASE__  )

						if not self.reached:
										return [self.start.pos]
						return None






		def  __A       (		self		:							List[Any]							,			SCREAMING_SNAKE_CASE__		:							Node  )     ->							list[Node]:
						__lowerCamelCase    					=	[]
						for action in delta:
										__lowerCamelCase    					=	parent.pos_x + action[1]
										__lowerCamelCase    					=	parent.pos_y + action[0]

										if not (0 <= pos_x <= len(grid[0]  ) - 1 and 0 <= pos_y <= len(SCREAMING_SNAKE_CASE__  ) - 1):
														continue

										if grid[pos_y][pos_x] != 0:
														continue

										successors.append(
										    Node(
										        SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__							,			self.target.pos_y							,			self.target.pos_x							,			parent.g_cost + 1							,			SCREAMING_SNAKE_CASE__							,			)  )
						return successors







		def  __A       (		self		:							List[str]							,			SCREAMING_SNAKE_CASE__		:							Node | None  )     ->							Path:
						__lowerCamelCase    					=	node
						__lowerCamelCase    					=	[]
						while current_node is not None:
										path.append((current_node.pos_y, current_node.pos_x)  )
										__lowerCamelCase    					=	current_node.parent
						path.reverse()
						return path


if __name__ == "__main__":
					SCREAMING_SNAKE_CASE__   :			Optional[int]												=    (0, 0)
					SCREAMING_SNAKE_CASE__   :			Optional[Any]												=    (len(grid) - 1, len(grid[0]) - 1)
					for elem in grid:
										print(elem)

					print("------")

					SCREAMING_SNAKE_CASE__   :			str												=    GreedyBestFirst(init, goal)
					SCREAMING_SNAKE_CASE__   :			Dict												=    greedy_bf.search()
					if path:
										for pos_x, pos_y in path:
															SCREAMING_SNAKE_CASE__   :			Tuple												=    2

										for elem in grid:
															print(elem)





from queue import PriorityQueue
from typing import Any

import numpy as np




def  __magic_name__ (   __lowerCAmelCase	:						dict		,  __lowerCAmelCase	:						str		,  __lowerCAmelCase	:						set		,  __lowerCAmelCase	:						set		,  __lowerCAmelCase	:						dict		,  __lowerCAmelCase	:						dict		,  __lowerCAmelCase	:						PriorityQueue		,  __lowerCAmelCase	:						dict		,  __lowerCAmelCase	:						float | int		,  )			->   float | int:
				for nxt, d in graph[v]:
								if nxt in visited_forward:
												continue
								__lowerCamelCase    					=	cst_fwd.get(__lowerCAmelCase		,  np.inf							)
								__lowerCamelCase    					=	cst_fwd[v] + d
								if new_cost_f < old_cost_f:
												queue.put((new_cost_f, nxt)							)
												__lowerCamelCase    					=	new_cost_f
												__lowerCamelCase    					=	v
								if nxt in visited_backward:
												if cst_fwd[v] + d + cst_bwd[nxt] < shortest_distance:
																__lowerCamelCase    					=	cst_fwd[v] + d + cst_bwd[nxt]
				return shortest_distance




def  __magic_name__ (   __lowerCAmelCase	:						str		,  __lowerCAmelCase	:						str		,  __lowerCAmelCase	:						dict		,  __lowerCAmelCase	:						dict							)			->   int:
				__lowerCamelCase    					=	-1

				__lowerCamelCase    					=	set()
				__lowerCamelCase    					=	set()
				__lowerCamelCase    					=	{source: 0}
				__lowerCamelCase    					=	{destination: 0}
				__lowerCamelCase    					=	{source: None}
				__lowerCamelCase    					=	{destination: None}
				__lowerCamelCase    					=	PriorityQueue()
				__lowerCamelCase    					=	PriorityQueue()

				__lowerCamelCase    					=	np.inf

				queue_forward.put((0, source)							)
				queue_backward.put((0, destination)							)

				if source == destination:
								return 0

				while not queue_forward.empty() and not queue_backward.empty():
								__lowerCamelCase					,    __lowerCamelCase    					=	queue_forward.get()
								visited_forward.add(__lowerCAmelCase							)

								__lowerCamelCase					,    __lowerCamelCase    					=	queue_backward.get()
								visited_backward.add(__lowerCAmelCase							)

								__lowerCamelCase    					=	pass_and_relaxation(
								    __lowerCAmelCase		,  __lowerCAmelCase		,  __lowerCAmelCase		,  __lowerCAmelCase		,  __lowerCAmelCase		,  __lowerCAmelCase		,  __lowerCAmelCase		,  __lowerCAmelCase		,  __lowerCAmelCase		,  )

								__lowerCamelCase    					=	pass_and_relaxation(
								    __lowerCAmelCase		,  __lowerCAmelCase		,  __lowerCAmelCase		,  __lowerCAmelCase		,  __lowerCAmelCase		,  __lowerCAmelCase		,  __lowerCAmelCase		,  __lowerCAmelCase		,  __lowerCAmelCase		,  )

								if cst_fwd[v_fwd] + cst_bwd[v_bwd] >= shortest_distance:
												break

				if shortest_distance != np.inf:
								__lowerCamelCase    					=	shortest_distance
				return shortest_path_distance


SCREAMING_SNAKE_CASE__   :			List[Any]												=    {
    "B": [["C", 1]],
    "C": [["D", 1]],
    "D": [["F", 1]],
    "E": [["B", 1], ["G", 2]],
    "F": [],
    "G": [["F", 1]],
}
SCREAMING_SNAKE_CASE__   :			Optional[int]												=    {
    "B": [["E", 1]],
    "C": [["B", 1]],
    "D": [["C", 1]],
    "F": [["D", 1], ["G", 1]],
    "E": [[None, np.inf]],
    "G": [["E", 2]],
}

if __name__ == "__main__":
					import doctest

					doctest.testmod()



