


from __future__ import annotations

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






def 		lowercase_(  SCREAMING_SNAKE_CASE_      ,						SCREAMING_SNAKE_CASE_      ,						SCREAMING_SNAKE_CASE_      ,						SCREAMING_SNAKE_CASE_      ,						SCREAMING_SNAKE_CASE_      ,						):


  '''simple docstring'''

  lowerCamelCase :					Tuple    =				[
      [0 for col in range(len(grid[0]	)	)] for row in range(len(lowerCAmelCase_	)	)
  ]  # the reference grid
  lowerCamelCase :					Union[str, Any]    =				1
  lowerCamelCase :					int    =				[
      [0 for col in range(len(grid[0]	)	)] for row in range(len(lowerCAmelCase_	)	)
  ]  # the action grid

  lowerCamelCase :					List[str]    =				init[0]
  lowerCamelCase :					Tuple    =				init[1]
  lowerCamelCase :					int    =				0
  lowerCamelCase :					Dict    =				g + heuristic[x][y]  # cost from starting cell to destination cell
  lowerCamelCase :					Tuple    =				[[f, g, x, y]]

  lowerCamelCase :					Optional[int]    =				False  # flag that is set when search is complete
  lowerCamelCase :					Tuple    =				False  # flag set if we can't find expand

  while not found and not resign:
    if len(lowerCAmelCase_	) == 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 :					Optional[int]    =				cell.pop()
      lowerCamelCase :					int    =				next_cell[2]
      lowerCamelCase :					Any    =				next_cell[3]
      lowerCamelCase :					Union[str, Any]    =				next_cell[1]

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

  lowerCamelCase :					Optional[int]    =				[]
  for i in range(len(lowerCAmelCase_	)	):
    path.append(invpath[len(lowerCAmelCase_	) - 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             =     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])







"""simple docstring"""







from abc import ABC, abstractmethod
from argparse import ArgumentParser




class  UpperCamelCase_	( UpperCamelCase):

	"""simple docstring"""





	@staticmethod
	@abstractmethod
	def   UpperCAmelCase_      ( UpperCAmelCase__			:				ArgumentParser   )       ->	int:
						raise NotImplementedError()




	@abstractmethod
	def   UpperCAmelCase_      ( self			:				int   )       ->	Optional[int]:
						raise NotImplementedError()
