

"""simple docstring"""




from __future__ import annotations

__UpperCAmelCase =				[
    [-1, 0],  # left
    [0, -1],  # down
    [1, 0],  # right
    [0, 1],  # up
]
def   lowerCAmelCase						(					__UpperCamelCase							,    __UpperCamelCase							,    __UpperCamelCase							,    __UpperCamelCase							,    __UpperCamelCase							,    ):
 '''simple docstring'''





 UpperCAmelCase__					:  List[Any]					   =					[
     [0 for col in range(len(grid[0]      )      )] for row in range(len(__UpperCamelCase      )      )
 ]  # the reference grid
 UpperCAmelCase__					:  str					   =					1
 UpperCAmelCase__					:  Dict					   =					[
     [0 for col in range(len(grid[0]      )      )] for row in range(len(__UpperCamelCase      )      )
 ]  # the action grid

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

 UpperCAmelCase__					:  List[str]					   =					False  # flag that is set when search is complete
 UpperCAmelCase__					:  Any					   =					False  # flag set if we can't find expand

 while not found and not resign:
  if len(__UpperCamelCase      ) == 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()
   UpperCAmelCase__					:  str					   =					cell.pop()
   UpperCAmelCase__					:  Dict					   =					next_cell[2]
   UpperCAmelCase__					:  Any					   =					next_cell[3]
   UpperCAmelCase__					:  Union[str, Any]					   =					next_cell[1]

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

 UpperCAmelCase__					:  List[Any]					   =					[]
 for i in range(len(__UpperCamelCase      )      ):
  path.append(invpath[len(__UpperCamelCase      ) - 1 - i]      )
 return path, action


if __name__ == "__main__":
      __UpperCAmelCase =				[
          [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],
      ]

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

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

      __UpperCAmelCase,		__UpperCAmelCase =				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 __future__ import annotations
def   lowerCAmelCase						(					__UpperCamelCase							,    __UpperCamelCase							,    __UpperCamelCase      ):
 '''simple docstring'''





 UpperCAmelCase__					:  Dict					   =					list(range(len(__UpperCamelCase      )      )      )
 UpperCAmelCase__					:  Union[str, Any]					   =					[v / w for v, w in zip(__UpperCamelCase							,    __UpperCamelCase      )]
 index.sort(key=lambda __UpperCamelCase      : ratio[i]							,    reverse=__UpperCamelCase      )

 UpperCAmelCase__					:  float					   =					0
 UpperCAmelCase__					:  list[float]					   =					[0] * len(__UpperCamelCase      )
 for i in index:
  if weight[i] <= capacity:
   UpperCAmelCase__					:  Optional[Any]					   =					1
   max_value += value[i]
   capacity -= weight[i]
  else:
   UpperCAmelCase__					:  Union[str, Any]					   =					capacity / weight[i]
   max_value += value[i] * capacity / weight[i]
   break

 return max_value, fractions


if __name__ == "__main__":
      import doctest

      doctest.testmod()





