


"""simple docstring"""


from __future__ import annotations

import time
from math import sqrt

# 1 for manhattan, 0 for euclidean
_snake_case          =							0

_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],
]

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

_snake_case          =							tuple[int, int]



class   _a      :
    def __init__( self							:					Tuple							,					SCREAMING_SNAKE_CASE__							:					int							,					SCREAMING_SNAKE_CASE__							:					int							,					SCREAMING_SNAKE_CASE__							:					int							,					SCREAMING_SNAKE_CASE__							:					int							,					SCREAMING_SNAKE_CASE__							:					int							,					SCREAMING_SNAKE_CASE__							:					Node | None							,					):
          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()
          lowerCamelCase__           =		self.g_cost + self.h_cost
    def      _UpperCamelCase       ( self							:					List[Any]				):
          lowerCamelCase__           =		self.pos_x - self.goal_x
          lowerCamelCase__           =		self.pos_y - self.goal_y
          if HEURISTIC == 1:
                return abs(SCREAMING_SNAKE_CASE__				) + abs(SCREAMING_SNAKE_CASE__				)
          else:
                return sqrt(dy**2 + dx**2				)


    def __lt__( self							:					str							,					SCREAMING_SNAKE_CASE__							:					Node				):
          return self.f_cost < other.f_cost





class   _a      :
    def __init__( self							:					Union[str, Any]							,					SCREAMING_SNAKE_CASE__							:					TPosition							,					SCREAMING_SNAKE_CASE__							:					TPosition				):
          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      _UpperCamelCase       ( self							:					Dict				):
          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:
                      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__				)

          return [self.start.pos]
    def      _UpperCamelCase       ( self							:					Tuple							,					SCREAMING_SNAKE_CASE__							:					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      _UpperCamelCase       ( self							:					List[Any]							,					SCREAMING_SNAKE_CASE__							:					Node | None				):
          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





class   _a      :
    def __init__( self							:					Any							,					SCREAMING_SNAKE_CASE__							:					TPosition							,					SCREAMING_SNAKE_CASE__							:					TPosition				):
          lowerCamelCase__           =		AStar(SCREAMING_SNAKE_CASE__							,					SCREAMING_SNAKE_CASE__				)
          lowerCamelCase__           =		AStar(SCREAMING_SNAKE_CASE__							,					SCREAMING_SNAKE_CASE__				)
          lowerCamelCase__           =		False
    def      _UpperCamelCase       ( self							:					Dict				):
          while self.fwd_astar.open_nodes or self.bwd_astar.open_nodes:
                self.fwd_astar.open_nodes.sort()
                self.bwd_astar.open_nodes.sort()
                lowerCamelCase__           =		self.fwd_astar.open_nodes.pop(0				)
                lowerCamelCase__           =		self.bwd_astar.open_nodes.pop(0				)

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

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

                lowerCamelCase__           =		current_bwd_node
                lowerCamelCase__           =		current_fwd_node

                lowerCamelCase__           =		{
                    self.fwd_astar: self.fwd_astar.get_successors(SCREAMING_SNAKE_CASE__				),
                    self.bwd_astar: self.bwd_astar.get_successors(SCREAMING_SNAKE_CASE__				),
                }

                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(SCREAMING_SNAKE_CASE__				)
                            else:
                                  # retrieve the best current path
                                  lowerCamelCase__           =		astar.open_nodes.pop(
                                      astar.open_nodes.index(SCREAMING_SNAKE_CASE__				)				)

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

          return [self.fwd_astar.start.pos]


    def      _UpperCamelCase       ( self							:					Optional[int]							,					SCREAMING_SNAKE_CASE__							:					Node							,					SCREAMING_SNAKE_CASE__							:					Node				):
          lowerCamelCase__           =		self.fwd_astar.retrace_path(SCREAMING_SNAKE_CASE__				)
          lowerCamelCase__           =		self.bwd_astar.retrace_path(SCREAMING_SNAKE_CASE__				)
          bwd_path.pop()
          bwd_path.reverse()
          lowerCamelCase__           =		fwd_path + bwd_path
          return path


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

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

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







"""simple docstring"""


from __future__ import annotations

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



def   snake_case						(				_a:     list[list[int]]		,   _a:     list[int]		,   _a:     list[int]		,   _a:     int		,   _a:     list[list[int]]		,   )->		tuple[list[list[int]], list[list[int]]]:
      '''simple docstring'''


      lowerCamelCase__           =		[
          [0 for col in range(len(grid[0]							)							)] for row in range(len(_a							)							)
      ]  # the reference grid
      lowerCamelCase__           =		1
      lowerCamelCase__           =		[
          [0 for col in range(len(grid[0]							)							)] for row in range(len(_a							)							)
      ]  # the action grid

      lowerCamelCase__           =		init[0]
      lowerCamelCase__           =		init[1]
      lowerCamelCase__           =		0
      lowerCamelCase__           =		g + heuristic[x][y]  # cost from starting cell to destination cell
      lowerCamelCase__           =		[[f, g, x, y]]

      lowerCamelCase__           =		False  # flag that is set when search is complete
      lowerCamelCase__           =		False  # flag set if we can't find expand

      while not found and not resign:
            if len(_a							) == 0:
                  raise ValueError('Algorithm is unable to find solution'							)
            else:  # to choose the least costliest action so as to move closer to the goal
                  cell.sort()
                  cell.reverse()
                  lowerCamelCase__           =		cell.pop()
                  lowerCamelCase__           =		next_cell[2]
                  lowerCamelCase__           =		next_cell[3]
                  lowerCamelCase__           =		next_cell[1]

                  if x == goal[0] and y == goal[1]:
                        lowerCamelCase__           =		True
                  else:
                        for i in range(len(_a							)							):  # to try out different valid actions
                              lowerCamelCase__           =		x + DIRECTIONS[i][0]
                              lowerCamelCase__           =		y + DIRECTIONS[i][1]
                              if xa >= 0 and xa < len(_a							) and ya >= 0 and ya < len(grid[0]							):
                                    if closed[xa][ya] == 0 and grid[xa][ya] == 0:
                                          lowerCamelCase__           =		g + cost
                                          lowerCamelCase__           =		ga + heuristic[xa][ya]
                                          cell.append([fa, ga, xa, ya]							)
                                          lowerCamelCase__           =		1
                                          lowerCamelCase__           =		i
      lowerCamelCase__           =		[]
      lowerCamelCase__           =		goal[0]
      lowerCamelCase__           =		goal[1]
      invpath.append([x, y]							)  # we get the reverse path from here
      while x != init[0] or y != init[1]:
            lowerCamelCase__           =		x - DIRECTIONS[action[x][y]][0]
            lowerCamelCase__           =		y - DIRECTIONS[action[x][y]][1]
            lowerCamelCase__           =		xa
            lowerCamelCase__           =		ya
            invpath.append([x, y]							)

      lowerCamelCase__           =		[]
      for i in range(len(_a							)							):
            path.append(invpath[len(_a							) - 1 - i]							)
      return path, action


if __name__ == "__main__":
   _snake_case          =							[
       [0, 1, 0, 0, 0, 0],
       [0, 1, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
       [0, 1, 0, 0, 0, 0],
       [0, 1, 0, 0, 1, 0],
       [0, 0, 0, 0, 1, 0],
   ]

   _snake_case          =							[0, 0]
   # all coordinates are given in format [y,x]
   _snake_case          =							[len(grid) - 1, len(grid[0]) - 1]
   _snake_case          =							1

   # the cost map which pushes the path closer to the goal
   _snake_case          =							[[0 for row in range(len(grid[0]))] for col in range(len(grid))]
   for i in range(len(grid)):
      for j in range(len(grid[0])):
         _snake_case          =							abs(i - goal[0]) + abs(j - goal[1])
         if grid[i][j] == 1:
            # added extra penalty in the heuristic map
            _snake_case          =							99

   _snake_case      ,					_snake_case          =							search(grid, init, goal, cost, heuristic)

   print("ACTION MAP")
   for i in range(len(action)):
      print(action[i])

   for i in range(len(path)):
      print(path[i])



