






"""simple docstring"""
from __future__ import annotations

lowerCamelCase_					=      list[tuple[int, int]]

lowerCamelCase_					=      [
    [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],
]

lowerCamelCase_					=      ([-1, 0], [0, -1], [1, 0], [0, 1])  # up, left, down, right







class 			UpperCamelCase_       :





	def __init__(      self					: List[Any]	,	lowerCAmelCase_					: int	,	lowerCAmelCase_					: int	,	lowerCAmelCase_					: int	,	lowerCAmelCase_					: int	,	lowerCAmelCase_					: float	,	lowerCAmelCase_					: Node | None	,	)						->			Dict:
				UpperCAmelCase_     : List[str]			     =					pos_x
				UpperCAmelCase_     : str			     =					pos_y
				UpperCAmelCase_     : Any			     =					(pos_y, pos_x)
				UpperCAmelCase_     : Optional[Any]			     =					goal_x
				UpperCAmelCase_     : Tuple			     =					goal_y
				UpperCAmelCase_     : Tuple			     =					g_cost
				UpperCAmelCase_     : Optional[Any]			     =					parent
				UpperCAmelCase_     : Optional[int]			     =					self.calculate_heuristic()





	def      _SCREAMING_SNAKE_CASE      (      self					: Optional[Any]						)						->			float:
				UpperCAmelCase_     : Any			     =					abs(self.pos_x - self.goal_x						)
				UpperCAmelCase_     : int			     =					abs(self.pos_y - self.goal_y						)
				return dx + dy





	def __lt__(      self					: List[Any]	,	lowerCAmelCase_					: Optional[Any]						)						->			bool:
				return self.f_cost < other.f_cost







class 			UpperCamelCase_       :





	def __init__(      self					: str	,	lowerCAmelCase_					: tuple[int, int]	,	lowerCAmelCase_					: tuple[int, int]						)						->			Any:
				UpperCAmelCase_     : List[str]			     =					Node(start[1]	,	start[0]	,	goal[1]	,	goal[0]	,	0	,	lowerCAmelCase_						)
				UpperCAmelCase_     : Dict			     =					Node(goal[1]	,	goal[0]	,	goal[1]	,	goal[0]	,	99_999	,	lowerCAmelCase_						)

				UpperCAmelCase_     : Union[str, Any]			     =					[self.start]
				UpperCAmelCase_     : list[Node]			     =					[]

				UpperCAmelCase_     : Optional[Any]			     =					False





	def      _SCREAMING_SNAKE_CASE      (      self					: Optional[Any]						)						->			Path | None:
				while self.open_nodes:
							# Open Nodes are sorted using __lt__
							self.open_nodes.sort()
							UpperCAmelCase_     : Any			     =					self.open_nodes.pop(0						)

							if current_node.pos == self.target.pos:
										UpperCAmelCase_     : Union[str, Any]			     =					True
										return self.retrace_path(lowerCAmelCase_						)

							self.closed_nodes.append(lowerCAmelCase_						)
							UpperCAmelCase_     : List[Any]			     =					self.get_successors(lowerCAmelCase_						)

							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(lowerCAmelCase_						)
										else:
													# retrieve the best current path
													UpperCAmelCase_     : Optional[Any]			     =					self.open_nodes.pop(self.open_nodes.index(lowerCAmelCase_						)						)

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

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





	def      _SCREAMING_SNAKE_CASE      (      self					: Any	,	lowerCAmelCase_					: Node						)						->			list[Node]:
				UpperCAmelCase_     : Tuple			     =					[]
				for action in delta:
							UpperCAmelCase_     : List[str]			     =					parent.pos_x + action[1]
							UpperCAmelCase_     : Dict			     =					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	,	parent.g_cost + 1	,	lowerCAmelCase_	,	)						)
				return successors





	def      _SCREAMING_SNAKE_CASE      (      self					: int	,	lowerCAmelCase_					: Node | None						)						->			Path:
				UpperCAmelCase_     : List[str]			     =					node
				UpperCAmelCase_     : Any			     =					[]
				while current_node is not None:
							path.append((current_node.pos_y, current_node.pos_x)						)
							UpperCAmelCase_     : Tuple			     =					current_node.parent
				path.reverse()
				return path


if __name__ == "__main__":
			lowerCamelCase_					=      (0, 0)
			lowerCamelCase_					=      (len(grid) - 1, len(grid[0]) - 1)
			for elem in grid:
						print(elem)

			print('''------''')

			lowerCamelCase_					=      GreedyBestFirst(init, goal)
			lowerCamelCase_					=      greedy_bf.search()
			if path:
						for pos_x, pos_y in path:
									lowerCamelCase_					=      2

						for elem in grid:
									print(elem)











"""simple docstring"""
import copy
import os

import cva
import numpy as np
from matplotlib import pyplot as plt







class 			UpperCamelCase_       :





	def __init__(      self					: str						)						->			Dict:
				UpperCAmelCase_     : List[Any]			     =					""
				UpperCAmelCase_     : int			     =					""
				UpperCAmelCase_     : Dict			     =					[]
				UpperCAmelCase_     : int			     =					0
				UpperCAmelCase_     : List[Any]			     =					256
				UpperCAmelCase_     : Dict			     =					0
				UpperCAmelCase_     : List[Any]			     =					0
				UpperCAmelCase_     : str			     =					0
				UpperCAmelCase_     : List[str]			     =					0





	def      _SCREAMING_SNAKE_CASE      (      self					: List[str]	,	lowerCAmelCase_					: Dict						)						->			Optional[Any]:
				UpperCAmelCase_     : Dict			     =					cva.imread(lowerCAmelCase_	,	0						)
				UpperCAmelCase_     : Union[str, Any]			     =					copy.deepcopy(self.img						)
				UpperCAmelCase_     ,	UpperCAmelCase_     ,	UpperCAmelCase_     : List[Any]			     =					plt.hist(self.img.ravel()	,	256	,	[0, 256]	,	label="x"						)
				UpperCAmelCase_     : List[Any]			     =					np.sum(lowerCAmelCase_						)
				for i in range(len(lowerCAmelCase_						)						):
							UpperCAmelCase_     : List[Any]			     =					x[i] / self.k
							self.sk += prk
							UpperCAmelCase_     : Optional[Any]			     =					(self.L - 1) * self.sk
							if self.rem != 0:
										UpperCAmelCase_     : Any			     =					int(last % last						)
							UpperCAmelCase_     : List[str]			     =					int(last + 1 if self.rem >= 0.5 else last						)
							self.last_list.append(lowerCAmelCase_						)
							UpperCAmelCase_     : Optional[Any]			     =					int(np.ma.count(self.img						) / self.img[1].size						)
							UpperCAmelCase_     : Dict			     =					self.img[1].size
				for i in range(self.number_of_cols						):
							for j in range(self.number_of_rows						):
										UpperCAmelCase_     : Any			     =					self.img[j][i]
										if num != self.last_list[num]:
													UpperCAmelCase_     : Tuple			     =					self.last_list[num]
				cva.imwrite("output_data/output.jpg"	,	self.img						)





	def      _SCREAMING_SNAKE_CASE      (      self					: List[Any]						)						->			Union[str, Any]:
				plt.hist(self.img.ravel()	,	256	,	[0, 256]						)





	def      _SCREAMING_SNAKE_CASE      (      self					: Union[str, Any]						)						->			str:
				cva.imshow("Output-Image"	,	self.img						)
				cva.imshow("Input-Image"	,	self.original_image						)
				cva.waitKey(5_000						)
				cva.destroyAllWindows()


if __name__ == "__main__":
			lowerCamelCase_					=      os.path.join(os.path.basename(__file__), '''image_data/input.jpg''')
			lowerCamelCase_					=      ConstantStretch()
			stretcher.stretch(file_path)
			stretcher.plot_histogram()
			stretcher.show_image()



