






import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey





class 						SCREAMING_SNAKE_CASE				:





							"""simple docstring"""

							def __init__(  self:   int		,     __A:   Union[str, Any]		,     __A:   int		,     __A:   int   )    ->				Optional[int]:
												if dst_width < 0 or dst_height < 0:
																	raise ValueError('''Destination width/height should be > 0'''   )

												_A								= img
												_A								= img.shape[1]
												_A								= img.shape[0]
												_A								= dst_width
												_A								= dst_height

												_A								= self.src_w / self.dst_w
												_A								= self.src_h / self.dst_h

												_A								= _A								= (
												    np.ones((self.dst_h, self.dst_w, 3)		,     np.uinta   ) * 2_55
												)

							def       __A (  self:   Optional[int]   )    ->				List[str]:
												for i in range(self.dst_h   ):
																	for j in range(self.dst_w   ):
																						_A								= self.img[self.get_y(__A   )][self.get_x(__A   )]

							def       __A (  self:   List[str]		,     __A:   int   )    ->				int:
												return int(self.ratio_x * x   )



							def       __A (  self:   Dict		,     __A:   int   )    ->				int:
												return int(self.ratio_y * y   )


if __name__ == "__main__":
				__A ,  __A      =				800, 600
				__A      =				imread('image_data/lena.jpg', 1)
				__A      =				NearestNeighbour(im, dst_w, dst_h)
				n.process()

				imshow(
				    f'Image resized from: {im.shape[1]}x{im.shape[0]} to {dst_w}x{dst_h}', n.output
				)
				waitKey(0)
				destroyAllWindows()











__A      =				{0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}

__A      =				{0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}




def      __A					(     _lowercase					,			_lowercase					,			_lowercase ):

					'''simple docstring'''







					_A								= True
					_A								= []

					for neighbour in graph[vert]:
										if not visited[neighbour]:
															order += topology_sort(_lowercase					,			_lowercase					,			_lowercase )

					order.append(_lowercase )

					return order




def      __A					(     _lowercase					,			_lowercase					,			_lowercase ):

					'''simple docstring'''







					_A								= True
					_A								= [vert]

					for neighbour in reversed_graph[vert]:
										if not visited[neighbour]:
															component += find_components(_lowercase					,			_lowercase					,			_lowercase )

					return component




def      __A					(     _lowercase ):

					'''simple docstring'''







					_A								= len(_lowercase ) * [False]
					_A								= {vert: [] for vert in range(len(_lowercase ) )}

					for vert, neighbours in graph.items():
										for neighbour in neighbours:
															reversed_graph[neighbour].append(_lowercase )

					_A								= []
					for i, was_visited in enumerate(_lowercase ):
										if not was_visited:
															order += topology_sort(_lowercase					,			_lowercase					,			_lowercase )

					_A								= []
					_A								= len(_lowercase ) * [False]

					for i in range(len(_lowercase ) ):
										_A								= order[len(_lowercase ) - i - 1]
										if not visited[vert]:
															_A								= find_components(_lowercase					,			_lowercase					,			_lowercase )
															components_list.append(_lowercase )

					return components_list



