

from __future__ import annotations

import time
from math import sqrt

# 1 for manhattan, 0 for euclidean
A_	:			List[Any]  	=      0

A_	:			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],
]

A_	:			Any  	=      [[-1, 0], [0, -1], [1, 0], [0, 1]]  # up, left, down, right

A_	:			Dict  	=      tuple[int, int]



class    _a						:


					'''simple docstring'''






					def __init__(			self   ,	A__   ,	A__   ,	A__   ,	A__   ,	A__   ,	A__   ,	):
						A__							:   int					       =		pos_x
						A__							:   Dict					       =		pos_y
						A__							:   Tuple					       =		(pos_y, pos_x)
						A__							:   List[Any]					       =		goal_x
						A__							:   Dict					       =		goal_y
						A__							:   Union[str, Any]					       =		g_cost
						A__							:   Union[str, Any]					       =		parent
						A__							:   List[str]					       =		self.calculate_heuristic()
						A__							:   Optional[int]					       =		self.g_cost + self.h_cost






					def   __A      (			self      ):
						A__							:   Any					       =		self.pos_x - self.goal_x
						A__							:   int					       =		self.pos_y - self.goal_y
						if HEURISTIC == 1:
							return abs(A__      ) + abs(A__      )
						else:
							return sqrt(dy**2 + dx**2      )






					def __lt__(			self   ,	A__      ):
						return self.f_cost < other.f_cost



class    _a						:


					'''simple docstring'''






					def __init__(			self   ,	A__   ,	A__      ):
						A__							:   Optional[Any]					       =		Node(start[1]   ,	start[0]   ,	goal[1]   ,	goal[0]   ,	0   ,	A__      )
						A__							:   Optional[int]					       =		Node(goal[1]   ,	goal[0]   ,	goal[1]   ,	goal[0]   ,	9_9999   ,	A__      )

						A__							:   Union[str, Any]					       =		[self.start]
						A__							:   list[Node]					       =		[]

						A__							:   Any					       =		False






					def   __A      (			self      ):
						while self.open_nodes:
							# Open Nodes are sorted using __lt__
							self.open_nodes.sort()
							A__							:   str					       =		self.open_nodes.pop(0      )

							if current_node.pos == self.target.pos:
								return self.retrace_path(A__      )

							self.closed_nodes.append(A__      )
							A__							:   List[str]					       =		self.get_successors(A__      )

							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(A__      )
								else:
									# retrieve the best current path
									A__							:   Optional[Any]					       =		self.open_nodes.pop(self.open_nodes.index(A__      )      )

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

						return [self.start.pos]






					def   __A      (			self   ,	A__      ):
						A__							:   List[str]					       =		[]
						for action in delta:
							A__							:   int					       =		parent.pos_x + action[1]
							A__							:   Union[str, Any]					       =		parent.pos_y + action[0]
							if not (0 <= pos_x <= len(grid[0]      ) - 1 and 0 <= pos_y <= len(A__      ) - 1):
								continue

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

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






					def   __A      (			self   ,	A__      ):
						A__							:   Dict					       =		node
						A__							:   List[str]					       =		[]
						while current_node is not None:
							path.append((current_node.pos_y, current_node.pos_x)      )
							A__							:   Dict					       =		current_node.parent
						path.reverse()
						return path



class    _a						:


					'''simple docstring'''






					def __init__(			self   ,	A__   ,	A__      ):
						A__							:   str					       =		AStar(A__   ,	A__      )
						A__							:   str					       =		AStar(A__   ,	A__      )
						A__							:   Tuple					       =		False






					def   __A      (			self      ):
						while self.fwd_astar.open_nodes or self.bwd_astar.open_nodes:
							self.fwd_astar.open_nodes.sort()
							self.bwd_astar.open_nodes.sort()
							A__							:   List[str]					       =		self.fwd_astar.open_nodes.pop(0      )
							A__							:   List[Any]					       =		self.bwd_astar.open_nodes.pop(0      )

							if current_bwd_node.pos == current_fwd_node.pos:
								return self.retrace_bidirectional_path(
								    A__   ,	A__      )

							self.fwd_astar.closed_nodes.append(A__      )
							self.bwd_astar.closed_nodes.append(A__      )

							A__							:   int					       =		current_bwd_node
							A__							:   Tuple					       =		current_fwd_node

							A__							:   str					       =		{
							    self.fwd_astar: self.fwd_astar.get_successors(A__      ),
							    self.bwd_astar: self.bwd_astar.get_successors(A__      ),
							}

							for astar in [self.fwd_astar, self.bwd_astar]:
								for child_node in successors[astar]:
									if child_node in astar.closed_nodes:
										continue

									if child_node not in astar.open_nodes:
										astar.open_nodes.append(A__      )
									else:
										# retrieve the best current path
										A__							:   str					       =		astar.open_nodes.pop(
										    astar.open_nodes.index(A__      )      )

										if child_node.g_cost < better_node.g_cost:
											astar.open_nodes.append(A__      )
										else:
											astar.open_nodes.append(A__      )

						return [self.fwd_astar.start.pos]






					def   __A      (			self   ,	A__   ,	A__      ):
						A__							:   List[Any]					       =		self.fwd_astar.retrace_path(A__      )
						A__							:   Optional[Any]					       =		self.bwd_astar.retrace_path(A__      )
						bwd_path.pop()
						bwd_path.reverse()
						A__							:   Any					       =		fwd_path + bwd_path
						return path


if __name__ == "__main__":
	# all coordinates are given in format [y,x]
	A_	:			List[str]  	=      (0, 0)
	A_	:			str  	=      (len(grid) - 1, len(grid[0]) - 1)
	for elem in grid:
		print(elem)

	A_	:			Optional[int]  	=      time.time()
	A_	:			Union[str, Any]  	=      AStar(init, goal)
	A_	:			Optional[Any]  	=      a_star.search()
	A_	:			Optional[int]  	=      time.time() - start_time
	print(f'''AStar execution time = {end_time:f} seconds''')

	A_	:			Union[str, Any]  	=      time.time()
	A_	:			Optional[int]  	=      BidirectionalAStar(init, goal)
	A_	:			Optional[Any]  	=      time.time() - bd_start_time
	print(f'''BidirectionalAStar execution time = {bd_end_time:f} seconds''')






from typing import Any

def 						UpperCamelCase (lowercase_:			list )					->				list[Any]:
	if not input_list:
		return []
	A__							:   Any					       =		[input_list.count(lowercase_ ) for value in input_list]
	A__							:   List[Any]					       =		max(lowercase_ )  # Gets the maximum count in the input list.
	# Gets values of modes
	return sorted({input_list[i] for i, value in enumerate(lowercase_ ) if value == y} )


if __name__ == "__main__":
	import doctest

	doctest.testmod()



