
from __future__ import annotations

import time
from math import sqrt

# 1 for manhattan, 0 for euclidean
SCREAMING_SNAKE_CASE							:Dict							 =				0

SCREAMING_SNAKE_CASE							:Optional[int]							 =				[
    [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							:Union[str, Any]							 =				[[-1, 0], [0, -1], [1, 0], [0, 1]]  # up, left, down, right

SCREAMING_SNAKE_CASE							:Optional[int]							 =				tuple[int, int]





class 							UpperCAmelCase      :




	'''simple docstring'''





	def __init__(       self					: Optional[int]							,A					: int							,A					: int							,A					: int							,A					: int							,A					: int							,A					: Node | None							,):
					__A   			= pos_x
					__A   			= pos_y
					__A   			= (pos_y, pos_x)
					__A   			= goal_x
					__A   			= goal_y
					__A   			= g_cost
					__A   			= parent
					__A   			= self.calculate_heuristic()
					__A   			= self.g_cost + self.h_cost






	def 				UpperCamelCase_  (       self					: Optional[int] ):
					__A   			= self.pos_x - self.goal_x
					__A   			= self.pos_y - self.goal_y
					if HEURISTIC == 1:
									return abs(A ) + abs(A )
					else:
									return sqrt(dy**2 + dx**2 )







	def __lt__(       self					: Union[str, Any]							,A					: Node ):
					return self.f_cost < other.f_cost





class 							UpperCAmelCase      :




	'''simple docstring'''





	def __init__(       self					: Optional[Any]							,A					: TPosition							,A					: TPosition ):
					__A   			= Node(start[1]							,start[0]							,goal[1]							,goal[0]							,0							,A )
					__A   			= Node(goal[1]							,goal[0]							,goal[1]							,goal[0]							,9_99_99							,A )

					__A   			= [self.start]
					__A   			= []

					__A   			= False






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

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

									self.closed_nodes.append(A )
									__A   			= 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   			= 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 				UpperCamelCase_  (       self					: List[str]							,A					: Node ):
					__A   			= []
					for action in delta:
									__A   			= parent.pos_x + action[1]
									__A   			= 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 				UpperCamelCase_  (       self					: int							,A					: Node | None ):
					__A   			= node
					__A   			= []
					while current_node is not None:
									path.append((current_node.pos_y, current_node.pos_x) )
									__A   			= current_node.parent
					path.reverse()
					return path





class 							UpperCAmelCase      :




	'''simple docstring'''





	def __init__(       self					: List[str]							,A					: TPosition							,A					: TPosition ):
					__A   			= AStar(A							,A )
					__A   			= AStar(A							,A )
					__A   			= False






	def 				UpperCamelCase_  (       self					: List[str] ):
					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   			= self.fwd_astar.open_nodes.pop(0 )
									__A   			= 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   			= current_bwd_node
									__A   			= current_fwd_node

									__A   			= {
									    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   			= 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 				UpperCamelCase_  (       self					: Dict							,A					: Node							,A					: Node ):
					__A   			= self.fwd_astar.retrace_path(A )
					__A   			= self.bwd_astar.retrace_path(A )
					bwd_path.pop()
					bwd_path.reverse()
					__A   			= fwd_path + bwd_path
					return path


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

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

					SCREAMING_SNAKE_CASE							:Tuple							 =				time.time()
					SCREAMING_SNAKE_CASE							:List[Any]							 =				BidirectionalAStar(init, goal)
					SCREAMING_SNAKE_CASE							:str							 =				time.time() - bd_start_time
					print(f'''BidirectionalAStar execution time = {bd_end_time:f} seconds''')




"""simple docstring"""


A     :   int			    =			{
    "Pillow": "Pillow",
    "accelerate": "accelerate>=0.11.0",
    "compel": "compel==0.1.8",
    "black": "black~=23.1",
    "datasets": "datasets",
    "filelock": "filelock",
    "flax": "flax>=0.4.1",
    "hf-doc-builder": "hf-doc-builder>=0.3.0",
    "huggingface-hub": "huggingface-hub>=0.13.2",
    "requests-mock": "requests-mock==1.10.0",
    "importlib_metadata": "importlib_metadata",
    "invisible-watermark": "invisible-watermark",
    "isort": "isort>=5.5.4",
    "jax": "jax>=0.2.8,!=0.3.2",
    "jaxlib": "jaxlib>=0.1.65",
    "Jinja2": "Jinja2",
    "k-diffusion": "k-diffusion>=0.0.12",
    "torchsde": "torchsde",
    "note_seq": "note_seq",
    "librosa": "librosa",
    "numpy": "numpy",
    "omegaconf": "omegaconf",
    "parameterized": "parameterized",
    "protobuf": "protobuf>=3.20.3,<4",
    "pytest": "pytest",
    "pytest-timeout": "pytest-timeout",
    "pytest-xdist": "pytest-xdist",
    "ruff": "ruff>=0.0.241",
    "safetensors": "safetensors",
    "sentencepiece": "sentencepiece>=0.1.91,!=0.1.92",
    "scipy": "scipy",
    "onnx": "onnx",
    "regex": "regex!=2019.12.17",
    "requests": "requests",
    "tensorboard": "tensorboard",
    "torch": "torch>=1.4",
    "torchvision": "torchvision",
    "transformers": "transformers>=4.25.1",
    "urllib3": "urllib3<=2.0.0",
}




