






'''simple docstring'''



from __future__ import annotations

import time
from math import sqrt

# 1 for manhattan, 0 for euclidean
SCREAMING_SNAKE_CASE						=	0

SCREAMING_SNAKE_CASE						=	[
    [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						=	[[-1, 0], [0, -1], [1, 0], [0, 1]]  # up, left, down, right

SCREAMING_SNAKE_CASE						=	tuple[int, int]
class UpperCAmelCase_					:




      """simple docstring"""




      def __init__( self			:		Optional[Any]     ,      UpperCAmelCase			:		int     ,      UpperCAmelCase			:		int     ,      UpperCAmelCase			:		int     ,      UpperCAmelCase			:		int     ,      UpperCAmelCase			:		int     ,      UpperCAmelCase			:		Node | None     ,      )  ->  None:


       '''simple docstring'''

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






      def 				A__      ( self			:		Any		)  ->  float:


       '''simple docstring'''

       lowercase					:   List[Any]				  =self.pos_x - self.goal_x
       lowercase					:   Dict				  =self.pos_y - self.goal_y
       if HEURISTIC == 1:
        return abs(UpperCAmelCase		) + abs(UpperCAmelCase		)
       else:
        return sqrt(dy**2 + dx**2		)






      def __lt__( self			:		int     ,      UpperCAmelCase			:		Node		)  ->  bool:


       '''simple docstring'''

       return self.f_cost < other.f_cost





class UpperCAmelCase_					:




      """simple docstring"""




      def __init__( self			:		str     ,      UpperCAmelCase			:		TPosition     ,      UpperCAmelCase			:		TPosition		)  ->  List[Any]:


       '''simple docstring'''

       lowercase					:   List[Any]				  =Node(start[1]     ,      start[0]     ,      goal[1]     ,      goal[0]     ,      0     ,      UpperCAmelCase		)
       lowercase					:   str				  =Node(goal[1]     ,      goal[0]     ,      goal[1]     ,      goal[0]     ,      9_9999     ,      UpperCAmelCase		)

       lowercase					:   Tuple				  =[self.start]
       lowercase					:   list[Node]				  =[]

       lowercase					:   Optional[int]				  =False






      def 				A__      ( self			:		int		)  ->  list[TPosition]:


       '''simple docstring'''

       while self.open_nodes:
        # Open Nodes are sorted using __lt__
        self.open_nodes.sort()
        lowercase					:   Optional[Any]				  =self.open_nodes.pop(0		)

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

        self.closed_nodes.append(UpperCAmelCase		)
        lowercase					:   Optional[Any]				  =self.get_successors(UpperCAmelCase		)

        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(UpperCAmelCase		)
         else:
          # retrieve the best current path
          lowercase					:   List[str]				  =self.open_nodes.pop(self.open_nodes.index(UpperCAmelCase		)		)

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

       return [self.start.pos]






      def 				A__      ( self			:		List[Any]     ,      UpperCAmelCase			:		Node		)  ->  list[Node]:


       '''simple docstring'''

       lowercase					:   Optional[Any]				  =[]
       for action in delta:
        lowercase					:   Optional[int]				  =parent.pos_x + action[1]
        lowercase					:   List[str]				  =parent.pos_y + action[0]
        if not (0 <= pos_x <= len(grid[0]		) - 1 and 0 <= pos_y <= len(UpperCAmelCase		) - 1):
         continue

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

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






      def 				A__      ( self			:		Tuple     ,      UpperCAmelCase			:		Node | None		)  ->  list[TPosition]:


       '''simple docstring'''

       lowercase					:   Union[str, Any]				  =node
       lowercase					:   Union[str, Any]				  =[]
       while current_node is not None:
        path.append((current_node.pos_y, current_node.pos_x)		)
        lowercase					:   Tuple				  =current_node.parent
       path.reverse()
       return path





class UpperCAmelCase_					:




      """simple docstring"""




      def __init__( self			:		Dict     ,      UpperCAmelCase			:		TPosition     ,      UpperCAmelCase			:		TPosition		)  ->  None:


       '''simple docstring'''

       lowercase					:   List[Any]				  =AStar(UpperCAmelCase     ,      UpperCAmelCase		)
       lowercase					:   Optional[Any]				  =AStar(UpperCAmelCase     ,      UpperCAmelCase		)
       lowercase					:   List[str]				  =False






      def 				A__      ( self			:		Optional[Any]		)  ->  list[TPosition]:


       '''simple docstring'''

       while self.fwd_astar.open_nodes or self.bwd_astar.open_nodes:
        self.fwd_astar.open_nodes.sort()
        self.bwd_astar.open_nodes.sort()
        lowercase					:   Tuple				  =self.fwd_astar.open_nodes.pop(0		)
        lowercase					:   Union[str, Any]				  =self.bwd_astar.open_nodes.pop(0		)

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

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

        lowercase					:   Optional[int]				  =current_bwd_node
        lowercase					:   Optional[Any]				  =current_fwd_node

        lowercase					:   Optional[Any]				  ={
            self.fwd_astar: self.fwd_astar.get_successors(UpperCAmelCase		),
            self.bwd_astar: self.bwd_astar.get_successors(UpperCAmelCase		),
        }

        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(UpperCAmelCase		)
          else:
           # retrieve the best current path
           lowercase					:   Optional[Any]				  =astar.open_nodes.pop(
               astar.open_nodes.index(UpperCAmelCase		)		)

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

       return [self.fwd_astar.start.pos]






      def 				A__      ( self			:		int     ,      UpperCAmelCase			:		Node     ,      UpperCAmelCase			:		Node		)  ->  list[TPosition]:


       '''simple docstring'''

       lowercase					:   Any				  =self.fwd_astar.retrace_path(UpperCAmelCase		)
       lowercase					:   Tuple				  =self.bwd_astar.retrace_path(UpperCAmelCase		)
       bwd_path.pop()
       bwd_path.reverse()
       lowercase					:   Optional[int]				  =fwd_path + bwd_path
       return path


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

      SCREAMING_SNAKE_CASE						=	time.time()
      SCREAMING_SNAKE_CASE						=	AStar(init, goal)
      SCREAMING_SNAKE_CASE						=	a_star.search()
      SCREAMING_SNAKE_CASE						=	time.time() - start_time
      print(f"""AStar execution time = {end_time:f} seconds""")

      SCREAMING_SNAKE_CASE						=	time.time()
      SCREAMING_SNAKE_CASE						=	BidirectionalAStar(init, goal)
      SCREAMING_SNAKE_CASE						=	time.time() - bd_start_time
      print(f"""BidirectionalAStar execution time = {bd_end_time:f} seconds""")











'''simple docstring'''



import importlib.metadata
from typing import Union

from packaging.version import Version, parse

from .constants import STR_OPERATION_TO_FUNC


SCREAMING_SNAKE_CASE						=	parse(importlib.metadata.version('torch'))


def 							lowercase_				(    __A :       Union[str, Version]					,      __A :       str					,      __A :       str			)       ->      Union[str, Any]:



 """simple docstring"""




 if operation not in STR_OPERATION_TO_FUNC.keys():
  raise ValueError(F'`operation` must be one of {list(STR_OPERATION_TO_FUNC.keys()			)}, received {operation}'			)
 lowercase					:   Any				  =STR_OPERATION_TO_FUNC[operation]
 if isinstance(__A					,      __A			):
  lowercase					:   List[Any]				  =parse(importlib.metadata.version(__A			)			)
 return operation(__A					,      parse(__A			)			)





def 							lowercase_				(    __A :       str					,      __A :       str			)       ->      Tuple:



 """simple docstring"""




 return compare_versions(__A					,      __A					,      __A			)



