





"""simple docstring"""




from __future__ import annotations

import time

a		:				Optional[Any]  			=    list[tuple[int, int]]

a		:				str  			=    [
    [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],
]

a		:				Dict  			=    [[-1, 0], [0, -1], [1, 0], [0, 1]]  # up, left, down, right


class  __UpperCamelCase       :






							def __init__(     self   ,      lowerCAmelCase__   ,      lowerCAmelCase__   ,      lowerCAmelCase__   ,      lowerCAmelCase__   ,      lowerCAmelCase__   )			->				List[str]:
								a   :	int			=       pos_x
								a   :	str			=       pos_y
								a   :	Tuple			=       (pos_y, pos_x)
								a   :	Optional[int]			=       goal_x
								a   :	Optional[Any]			=       goal_y
								a   :	List[Any]			=       parent


class  __UpperCamelCase       :






							def __init__(     self   ,      lowerCAmelCase__   ,      lowerCAmelCase__   )			->				List[Any]:
								a   :	List[str]			=       Node(start[1]   ,      start[0]   ,      goal[1]   ,      goal[0]   ,      lowerCAmelCase__   )
								a   :	Union[str, Any]			=       Node(goal[1]   ,      goal[0]   ,      goal[1]   ,      goal[0]   ,      lowerCAmelCase__   )

								a   :	Any			=       [self.start]
								a   :	Any			=       False






							def 					__a     (     self   )			->				Path | None:
								while self.node_queue:
									a   :	Optional[int]			=       self.node_queue.pop(0   )

									if current_node.pos == self.target.pos:
										a   :	str			=       True
										return self.retrace_path(lowerCAmelCase__   )

									a   :	Union[str, Any]			=       self.get_successors(lowerCAmelCase__   )

									for node in successors:
										self.node_queue.append(lowerCAmelCase__   )

								if not self.reached:
									return [self.start.pos]
								return None






							def 					__a     (     self   ,      lowerCAmelCase__   )			->				list[Node]:
								a   :	int			=       []
								for action in delta:
									a   :	str			=       parent.pos_x + action[1]
									a   :	Optional[Any]			=       parent.pos_y + action[0]
									if not (0 <= pos_x <= len(grid[0]   ) - 1 and 0 <= pos_y <= len(lowerCAmelCase__   ) - 1):
										continue

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

									successors.append(
									    Node(lowerCAmelCase__   ,      lowerCAmelCase__   ,      self.target.pos_y   ,      self.target.pos_x   ,      lowerCAmelCase__   )   )
								return successors






							def 					__a     (     self   ,      lowerCAmelCase__   )			->				Path:
								a   :	int			=       node
								a   :	Optional[int]			=       []
								while current_node is not None:
									path.append((current_node.pos_y, current_node.pos_x)   )
									a   :	str			=       current_node.parent
								path.reverse()
								return path


class  __UpperCamelCase       :






							def __init__(     self   ,      lowerCAmelCase__   ,      lowerCAmelCase__   )			->				Optional[Any]:
								a   :	Tuple			=       BreadthFirstSearch(lowerCAmelCase__   ,      lowerCAmelCase__   )
								a   :	str			=       BreadthFirstSearch(lowerCAmelCase__   ,      lowerCAmelCase__   )
								a   :	int			=       False






							def 					__a     (     self   )			->				Path | None:
								while self.fwd_bfs.node_queue or self.bwd_bfs.node_queue:
									a   :	Tuple			=       self.fwd_bfs.node_queue.pop(0   )
									a   :	List[Any]			=       self.bwd_bfs.node_queue.pop(0   )

									if current_bwd_node.pos == current_fwd_node.pos:
										a   :	Dict			=       True
										return self.retrace_bidirectional_path(
										    lowerCAmelCase__   ,      lowerCAmelCase__   )

									a   :	Any			=       current_bwd_node
									a   :	List[str]			=       current_fwd_node

									a   :	Optional[Any]			=       {
									    self.fwd_bfs: self.fwd_bfs.get_successors(lowerCAmelCase__   ),
									    self.bwd_bfs: self.bwd_bfs.get_successors(lowerCAmelCase__   ),
									}

									for bfs in [self.fwd_bfs, self.bwd_bfs]:
										for node in successors[bfs]:
											bfs.node_queue.append(lowerCAmelCase__   )

								if not self.reached:
									return [self.fwd_bfs.start.pos]
								return None






							def 					__a     (     self   ,      lowerCAmelCase__   ,      lowerCAmelCase__   )			->				Path:
								a   :	str			=       self.fwd_bfs.retrace_path(lowerCAmelCase__   )
								a   :	List[Any]			=       self.bwd_bfs.retrace_path(lowerCAmelCase__   )
								bwd_path.pop()
								bwd_path.reverse()
								a   :	int			=       fwd_path + bwd_path
								return path


if __name__ == "__main__":
		# all coordinates are given in format [y,x]
		import doctest

		doctest.testmod()
		a		:				Optional[Any]  			=    (0, 0)
		a		:				int  			=    (len(grid) - 1, len(grid[0]) - 1)
		for elem in grid:
				print(elem)

		a		:				Optional[int]  			=    time.time()
		a		:				Optional[Any]  			=    BreadthFirstSearch(init, goal)
		a		:				Tuple  			=    bfs.search()
		a		:				int  			=    time.time() - start_bfs_time

		print('''Unidirectional BFS computation time : ''', bfs_time)

		a		:				Optional[Any]  			=    time.time()
		a		:				Union[str, Any]  			=    BidirectionalBreadthFirstSearch(init, goal)
		a		:				str  			=    bd_bfs.search()
		a		:				List[str]  			=    time.time() - start_bd_bfs_time

		print('''Bidirectional BFS computation time : ''', bd_bfs_time)









"""simple docstring"""




from random import randint
from tempfile import TemporaryFile

import numpy as np






def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					Optional[int]					, _lowercase		:					Optional[Any]					, _lowercase		:					Union[str, Any]      )				->Dict:






	'''simple docstring'''






	a   :	List[str]			=       0
	if start < end:
		a   :	Tuple			=       randint(_lowercase					, _lowercase      )
		a   :	List[str]			=       a[end]
		a   :	str			=       a[pivot]
		a   :	Optional[int]			=       temp

		a, a   :	Dict			=       _in_place_partition(_lowercase					, _lowercase					, _lowercase      )
		count += _in_place_quick_sort(_lowercase					, _lowercase					, p - 1      )
		count += _in_place_quick_sort(_lowercase					, p + 1					, _lowercase      )
	return count






def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					Optional[Any]					, _lowercase		:					str					, _lowercase		:					List[Any]      )				->str:






	'''simple docstring'''






	a   :	Union[str, Any]			=       0
	a   :	List[Any]			=       randint(_lowercase					, _lowercase      )
	a   :	int			=       a[end]
	a   :	List[str]			=       a[pivot]
	a   :	Tuple			=       temp
	a   :	Union[str, Any]			=       start - 1
	for index in range(_lowercase					, _lowercase      ):
		count += 1
		if a[index] < a[end]:  # check if current val is less than pivot value
			a   :	List[str]			=       new_pivot_index + 1
			a   :	Optional[int]			=       a[new_pivot_index]
			a   :	Union[str, Any]			=       a[index]
			a   :	List[Any]			=       temp

	a   :	Tuple			=       a[new_pivot_index + 1]
	a   :	str			=       a[end]
	a   :	Dict			=       temp
	return new_pivot_index + 1, count


a		:				int  			=    TemporaryFile()
a		:				Tuple  			=    100  # 1000 elements are to be sorted


a			,				a		:				int  			=    0, 1  # mean and standard deviation
a		:				List[Any]  			=    np.random.normal(mu, sigma, p)
np.save(outfile, X)
print('''The array is''')
print(X)


outfile.seek(0)  # using the same array
a		:				int  			=    np.load(outfile)
a		:				Tuple  			=    len(M) - 1
a		:				Union[str, Any]  			=    _in_place_quick_sort(M, 0, r)

print(
    '''No of Comparisons for 100 elements selected from a standard normal distribution'''
    '''is :'''
)







print(z)


