





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


class 					__magic_name__  :





     """simple docstring"""



     def __init__(							self       :str			,      snake_case       :int			,      snake_case       :int  ):





        '''simple docstring'''




        A_					:				Optional[int]          =			0
        # max greyscale value for #FFFFFF
        A_					:				Optional[Any]          =			int(self.get_greyscale(255			,      255			,      255  )  )

        if not self.min_threshold < threshold < self.max_threshold:
           A_					:				Dict          =			f"Factor value should be from 0 to {self.max_threshold}"
           raise ValueError(snake_case  )

        A_					:				Tuple          =			input_img
        A_					:				Optional[Any]          =			threshold
        A_      ,						A_					:				Dict          =			self.input_img.shape[1], self.input_img.shape[0]

        # error table size (+4 columns and +1 row) greater than input image because of
        # lack of if statements
        A_					:				Optional[Any]          =			[
            [0 for _ in range(self.height + 4  )] for __ in range(self.width + 1  )
        ]
        A_					:				Optional[int]          =			np.ones((self.width, self.height, 3)			,      np.uinta  ) * 255



     @classmethod
     def 						SCREAMING_SNAKE_CASE		(							cls       :int			,      snake_case       :int			,      snake_case       :int			,      snake_case       :int  ):





        '''simple docstring'''




        return 0.114 * blue + 0.587 * green + 0.2126 * red





     def 						SCREAMING_SNAKE_CASE		(							self       :List[Any]  ):





        '''simple docstring'''




        for y in range(self.height  ):
           for x in range(self.width  ):
              A_					:				Tuple          =			int(self.get_greyscale(*self.input_img[y][x]  )  )
              if self.threshold > greyscale + self.error_table[y][x]:
                 A_					:				List[Any]          =			(0, 0, 0)
                 A_					:				Tuple          =			greyscale + self.error_table[x][y]
              else:
                 A_					:				Optional[Any]          =			(255, 255, 255)
                 A_					:				Dict          =			greyscale + self.error_table[x][y] - 255
              self.error_table[y][x + 1] += int(8 / 32 * current_error  )
              self.error_table[y][x + 2] += int(4 / 32 * current_error  )
              self.error_table[y + 1][x] += int(8 / 32 * current_error  )
              self.error_table[y + 1][x + 1] += int(4 / 32 * current_error  )
              self.error_table[y + 1][x + 2] += int(2 / 32 * current_error  )
              self.error_table[y + 1][x - 1] += int(4 / 32 * current_error  )
              self.error_table[y + 1][x - 2] += int(2 / 32 * current_error  )


if __name__ == "__main__":
 # create Burke's instances with original images in greyscale
 _lowerCAmelCase							:      Any						=	[
     Burkes(imread('''image_data/lena.jpg''', 1), threshold)
     for threshold in (1, 126, 130, 140)
 ]

 for burkes in burkes_instances:
  burkes.process()

 for burkes in burkes_instances:
  imshow(
      F'''Original image with dithering threshold: {burkes.threshold}''',
      burkes.output_img,
  )

 waitKey(0)
 destroyAllWindows()







def      __snake_case						(					_lowerCAmelCase : float				,				_lowerCAmelCase : float				,				_lowerCAmelCase : int	) ->						float:
   A_					:				List[str]          =			[1 / first_term]
   A_					:				Tuple          =			1 / first_term
   for _ in range(number_of_terms - 1	):
      first_term += common_difference
      arithmetic_progression.append(_lowerCAmelCase	)
   A_					:				List[str]          =			[1 / step for step in arithmetic_progression]
   return sum(_lowerCAmelCase	)


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 print(sum_of_harmonic_progression(1 / 2, 2, 2))
