


'''simple docstring'''

from __future__ import annotations

import time
from math import sqrt

# 1 for manhattan, 0 for euclidean
lowercase__				     =		0

lowercase__				     =		[
    [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],
]

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

lowercase__				     =		tuple[int, int]





class 						__SCREAMING_SNAKE_CASE					:






     def __init__(			self     ,							__UpperCamelCase     ,							__UpperCamelCase     ,							__UpperCamelCase     ,							__UpperCamelCase     ,							__UpperCamelCase     ,							__UpperCamelCase     ,							)       ->    None:
          _a						=		pos_x
          _a						=		pos_y
          _a						=		(pos_y, pos_x)
          _a						=		goal_x
          _a						=		goal_y
          _a						=		g_cost
          _a						=		parent
          _a						=		self.calculate_heuristic()
          _a						=		self.g_cost + self.h_cost






     def  a_					(			self		)       ->    float:
          _a						=		self.pos_x - self.goal_x
          _a						=		self.pos_y - self.goal_y
          if HEURISTIC == 1:
               return abs(__UpperCamelCase		) + abs(__UpperCamelCase		)
          else:
               return sqrt(dy**2 + dx**2		)






     def __lt__(			self     ,							__UpperCamelCase		)       ->    bool:
          return self.f_cost < other.f_cost







class 						__SCREAMING_SNAKE_CASE					:






     def __init__(			self     ,							__UpperCamelCase     ,							__UpperCamelCase		)       ->    Tuple:
          _a						=		Node(start[1]     ,							start[0]     ,							goal[1]     ,							goal[0]     ,							0     ,							__UpperCamelCase		)
          _a						=		Node(goal[1]     ,							goal[0]     ,							goal[1]     ,							goal[0]     ,							99_999     ,							__UpperCamelCase		)

          _a						=		[self.start]
          _a						=		[]

          _a						=		False






     def  a_					(			self		)       ->    list[TPosition]:
          while self.open_nodes:
               # Open Nodes are sorted using __lt__
               self.open_nodes.sort()
               _a						=		self.open_nodes.pop(0		)

               if current_node.pos == self.target.pos:
                    return self.retrace_path(__UpperCamelCase		)

               self.closed_nodes.append(__UpperCamelCase		)
               _a						=		self.get_successors(__UpperCamelCase		)

               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(__UpperCamelCase		)
                    else:
                         # retrieve the best current path
                         _a						=		self.open_nodes.pop(self.open_nodes.index(__UpperCamelCase		)		)

                         if child_node.g_cost < better_node.g_cost:
                              self.open_nodes.append(__UpperCamelCase		)
                         else:
                              self.open_nodes.append(__UpperCamelCase		)

          return [self.start.pos]






     def  a_					(			self     ,							__UpperCamelCase		)       ->    list[Node]:
          _a						=		[]
          for action in delta:
               _a						=		parent.pos_x + action[1]
               _a						=		parent.pos_y + action[0]
               if not (0 <= pos_x <= len(grid[0]		) - 1 and 0 <= pos_y <= len(__UpperCamelCase		) - 1):
                    continue

               if grid[pos_y][pos_x] != 0:
                    continue

               successors.append(
                   Node(
                       __UpperCamelCase     ,							__UpperCamelCase     ,							self.target.pos_y     ,							self.target.pos_x     ,							parent.g_cost + 1     ,							__UpperCamelCase     ,							)		)
          return successors






     def  a_					(			self     ,							__UpperCamelCase		)       ->    list[TPosition]:
          _a						=		node
          _a						=		[]
          while current_node is not None:
               path.append((current_node.pos_y, current_node.pos_x)		)
               _a						=		current_node.parent
          path.reverse()
          return path







class 						__SCREAMING_SNAKE_CASE					:






     def __init__(			self     ,							__UpperCamelCase     ,							__UpperCamelCase		)       ->    None:
          _a						=		AStar(__UpperCamelCase     ,							__UpperCamelCase		)
          _a						=		AStar(__UpperCamelCase     ,							__UpperCamelCase		)
          _a						=		False






     def  a_					(			self		)       ->    list[TPosition]:
          while self.fwd_astar.open_nodes or self.bwd_astar.open_nodes:
               self.fwd_astar.open_nodes.sort()
               self.bwd_astar.open_nodes.sort()
               _a						=		self.fwd_astar.open_nodes.pop(0		)
               _a						=		self.bwd_astar.open_nodes.pop(0		)

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

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

               _a						=		current_bwd_node
               _a						=		current_fwd_node

               _a						=		{
                   self.fwd_astar: self.fwd_astar.get_successors(__UpperCamelCase		),
                   self.bwd_astar: self.bwd_astar.get_successors(__UpperCamelCase		),
               }

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

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

          return [self.fwd_astar.start.pos]






     def  a_					(			self     ,							__UpperCamelCase     ,							__UpperCamelCase		)       ->    list[TPosition]:
          _a						=		self.fwd_astar.retrace_path(__UpperCamelCase		)
          _a						=		self.bwd_astar.retrace_path(__UpperCamelCase		)
          bwd_path.pop()
          bwd_path.reverse()
          _a						=		fwd_path + bwd_path
          return path


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

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

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





'''simple docstring'''

def __UpperCamelCase   (			__lowerCamelCase		: int = 400_0000				)      ->     int:







     '''simple docstring'''






     _a						=		[]
     _a			,			_a						=		0, 1
     while b <= n:
          if b % 2 == 0:
               even_fibs.append(__lowerCamelCase				)
          _a			,			_a						=		b, a + b
     return sum(__lowerCamelCase				)


if __name__ == "__main__":
   print(f'''{solution() = }''')

