



'''simple docstring'''





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





class 							lowerCAmelCase_		:





    def __init__(    self    :    Union[str, Any],    _snake_case    :    List[str],    _snake_case    :    int     ):



       '''simple docstring'''







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

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

       snake_case   :							Optional[Any]						  =input_img
       snake_case   :							Any						  =threshold
       snake_case  ,    snake_case   :							Any						  =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
       snake_case   :							List[Any]						  =[
           [0 for _ in range(self.height + 4     )] for __ in range(self.width + 1     )
       ]
       snake_case   :							Tuple						  =np.ones((self.width, self.height, 3),    np.uinta     ) * 255





    @classmethod
    def 					__snake_case       (    cls    :    Optional[Any],    _snake_case    :    int,    _snake_case    :    int,    _snake_case    :    int     ):



       '''simple docstring'''







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






    def 					__snake_case       (    self    :    Optional[Any]     ):



       '''simple docstring'''







       for y in range(self.height     ):
          for x in range(self.width     ):
             snake_case   :							List[Any]						  =int(self.get_greyscale(*self.input_img[y][x]     )     )
             if self.threshold > greyscale + self.error_table[y][x]:
                snake_case   :							int						  =(0, 0, 0)
                snake_case   :							List[Any]						  =greyscale + self.error_table[x][y]
             else:
                snake_case   :							Optional[int]						  =(255, 255, 255)
                snake_case   :							Optional[int]						  =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
      A			:   Dict			=      [
          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()










'''simple docstring'''





import doctest

import projectq
from projectq.ops import H, Measure
def 		_a   (  lowerCamelCase_							):
   snake_case   :							str						  =quantum_engine.allocate_qubit()
   H | qubit
   Measure | qubit
   return int(lowerCamelCase_							)


if __name__ == "__main__":
      doctest.testmod()

      # initialises a new quantum backend
      A			:   Dict			=      projectq.MainEngine()

      # Generate a list of 10 random numbers
      A			:   Dict			=      [get_random_number(quantum_engine) for _ in range(10)]

      # Flushes the quantum engine from memory
      quantum_engine.flush()

      print("""Random numbers""", random_numbers_list)





