





'''simple docstring'''






from __future__ import annotations

A__							:  Any    =[
    [-1, 0],  # left
    [0, -1],  # down
    [1, 0],  # right
    [0, 1],  # up
]
def   UpperCamelCase__ (						lowerCAmelCase				,      lowerCAmelCase				,      lowerCAmelCase				,      lowerCAmelCase				,      lowerCAmelCase				,      ):





      """simple docstring"""


      _lowerCAmelCase					=				[
          [0 for col in range(len(grid[0]    )    )] for row in range(len(lowerCAmelCase    )    )
      ]  # the reference grid
      _lowerCAmelCase					=				1
      _lowerCAmelCase					=				[
          [0 for col in range(len(grid[0]    )    )] for row in range(len(lowerCAmelCase    )    )
      ]  # 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(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					=				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(lowerCAmelCase    )    ):  # to try out different valid actions
                              _lowerCAmelCase					=				x + DIRECTIONS[i][0]
                              _lowerCAmelCase					=				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					=				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(lowerCAmelCase    )    ):
            path.append(invpath[len(lowerCAmelCase    ) - 1 - i]    )
      return path, action


if __name__ == "__main__":
      A__							:  List[Any]    =[
          [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],
      ]

      A__							:  str    =[0, 0]
      # all coordinates are given in format [y,x]
      A__							:  Dict    =[len(grid) - 1, len(grid[0]) - 1]
      A__							:  Optional[Any]    =1

      # the cost map which pushes the path closer to the goal
      A__							:  Dict    =[[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])):
                  A__							:  Any    =abs(i - goal[0]) + abs(j - goal[1])
                  if grid[i][j] == 1:
                        # added extra penalty in the heuristic map
                        A__							:  Tuple    =99

      A__  ,		A__							:  Optional[int]    =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 ..utils import DummyObject, requires_backends




class 					UpperCAmelCase	(     metaclass=snake_case_  ):
      _lowercase:     List[Any]			=  ['''torch''', '''scipy''']




      def __init__(     self     :					Tuple     ,     *__snake_case     :					Dict     ,     **__snake_case     :					List[str]    )							-> str:
            requires_backends(self     ,     ["""torch""", """scipy"""]    )




      @classmethod
      def 							lowercase__       (     cls     :					str     ,     *__snake_case     :					List[str]     ,     **__snake_case     :					str    )							-> Tuple:
            requires_backends(cls     ,     ["""torch""", """scipy"""]    )




      @classmethod
      def 							lowercase__       (     cls     :					Optional[int]     ,     *__snake_case     :					int     ,     **__snake_case     :					Union[str, Any]    )							-> Optional[int]:
            requires_backends(cls     ,     ["""torch""", """scipy"""]    )






