






from __future__ import annotations

__lowerCamelCase      :    Optional[Any]   		=   [
    [-1, 0],  # left
    [0, -1],  # down
    [1, 0],  # right
    [0, 1],  # up
]







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							list[list[int]]  ,						snake_case_      :							list[int]  ,						snake_case_      :							list[int]  ,						snake_case_      :							int  ,						snake_case_      :							list[list[int]]  ,						):
 snake_case__				:   Any     =						[
     [0 for col in range(len(grid[0]     )     )] for row in range(len(_lowerCamelCase     )     )
 ]  # the reference grid
 snake_case__				:   Optional[int]     =						1
 snake_case__				:   Tuple     =						[
     [0 for col in range(len(grid[0]     )     )] for row in range(len(_lowerCamelCase     )     )
 ]  # the action grid

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

 snake_case__				:   List[Any]     =						False  # flag that is set when search is complete
 snake_case__				:   Optional[Any]     =						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()
   snake_case__				:   Dict     =						cell.pop()
   snake_case__				:   Any     =						next_cell[2]
   snake_case__				:   str     =						next_cell[3]
   snake_case__				:   str     =						next_cell[1]

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

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


if __name__ == "__main__":
 __lowerCamelCase      :    int   		=   [
     [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],
 ]

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

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

 __lowerCamelCase      :    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])











# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run

import sys
import warnings
from os.path import abspath, dirname, join


# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
__lowerCamelCase      :    Dict   		=   abspath(join(dirname(dirname(__file__)), """src"""))
sys.path.insert(1, git_repo_path)

# silence FutureWarning warnings in tests since often we can't act on them until
# they become normal warnings - i.e. the tests still need to test the current functionality
warnings.simplefilter(action="""ignore""", category=FutureWarning)







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							str     ):
	from diffusers.utils.testing_utils import pytest_addoption_shared

	pytest_addoption_shared(snake_case_     )







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Any     ):
	from diffusers.utils.testing_utils import pytest_terminal_summary_main

	snake_case__				:   Optional[int]     =						terminalreporter.config.getoption("--make-reports"     )
	if make_reports:
		pytest_terminal_summary_main(snake_case_  ,						id=snake_case_     )



