




'''simple docstring'''






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




class 		a__    :





							'''simple docstring'''






							def __init__(		self ,   lowerCamelCase_ ,   lowerCamelCase_ ,   lowerCamelCase_       )	->							Tuple:
														if dst_width < 0 or dst_height < 0:
																					raise ValueError('''Destination width/height should be > 0'''       )

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

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

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







							def   __SCREAMING_SNAKE_CASE							(		self       )	->							List[Any]:
														for i in range(self.dst_h       ):
																					for j in range(self.dst_w       ):
																												lowerCAmelCase__	       =     self.img[self.get_y(_lowerCamelCase       )][self.get_x(_lowerCamelCase       )]







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_       )	->							Optional[int]:
														return int(self.ratio_x * x       )







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


if __name__ == "__main__":
		__UpperCAmelCase    ,      __UpperCAmelCase       =							800, 600
		__UpperCAmelCase       =							imread('''image_data/lena.jpg''', 1)
		__UpperCAmelCase       =							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()



'''simple docstring'''






from __future__ import annotations




class 		a__    :





							'''simple docstring'''






							def __init__(		self ,   lowerCamelCase_       )	->							None:
														lowerCAmelCase__	       =     order

														# a_{0} ... a_{k}
														lowerCAmelCase__	       =     [1.0] + [0.0] * order
														# b_{0} ... b_{k}
														lowerCAmelCase__	       =     [1.0] + [0.0] * order

														# x[n-1] ... x[n-k]
														lowerCAmelCase__	       =     [0.0] * self.order
														# y[n-1] ... y[n-k]
														lowerCAmelCase__	       =     [0.0] * self.order







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_ ,   lowerCamelCase_       )	->							None:
														if len(lowerCamelCase_       ) < self.order:
																					lowerCAmelCase__	       =     [1.0, *a_coeffs]

														if len(lowerCamelCase_       ) != self.order + 1:
																					lowerCAmelCase__	       =     (
																					    F"""Expected a_coeffs to have {self.order + 1} elements """
																					    F"""for {self.order}-order filter, got {len(lowerCamelCase_       )}"""
																					)
																					raise ValueError(lowerCamelCase_       )

														if len(lowerCamelCase_       ) != self.order + 1:
																					lowerCAmelCase__	       =     (
																					    F"""Expected b_coeffs to have {self.order + 1} elements """
																					    F"""for {self.order}-order filter, got {len(lowerCamelCase_       )}"""
																					)
																					raise ValueError(lowerCamelCase_       )

														lowerCAmelCase__	       =     a_coeffs
														lowerCAmelCase__	       =     b_coeffs







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_       )	->							float:
														lowerCAmelCase__	       =     0.0

														# Start at index 1 and do index 0 at the end.
														for i in range(1 ,   self.order + 1       ):
																					result += (
																					    self.b_coeffs[i] * self.input_history[i - 1]
																					    - self.a_coeffs[i] * self.output_history[i - 1]
																					)

														lowerCAmelCase__	       =     (result + self.b_coeffs[0] * sample) / self.a_coeffs[0]

														lowerCAmelCase__	       =     self.input_history[:-1]
														lowerCAmelCase__	       =     self.output_history[:-1]

														lowerCAmelCase__	       =     sample
														lowerCAmelCase__	       =     result

														return result