




from string import ascii_uppercase

def       lowerCAmelCase_      (	lowerCamelCase:							str  ,					lowerCamelCase:							str  ,					lowerCamelCase:							bool = False  ,					lowerCamelCase:							str = ascii_uppercase    )       ->      str:


      '''simple docstring'''




      lowerCamelCase__   	=					keyword.upper()
      lowerCamelCase__   	=					plaintext.upper()
      lowerCamelCase__   	=					set(lowerCamelCase    )

      # create a list of unique characters in the keyword - their order matters
      # it determines how we will map plaintext characters to the ciphertext
      lowerCamelCase__   	=					[]
      for char in keyword:
            if char in alphabet_set and char not in unique_chars:
                  unique_chars.append(lowerCamelCase    )
    # the number of those unique characters will determine the number of rows
      lowerCamelCase__   	=					len(lowerCamelCase    )

      # create a shifted version of the alphabet
      lowerCamelCase__   	=					unique_chars + [
          char for char in alphabet if char not in unique_chars
      ]

      # create a modified alphabet by splitting the shifted alphabet into rows
      lowerCamelCase__   	=					[
          shifted_alphabet[k : k + num_unique_chars_in_keyword]
          for k in range(0  ,					26  ,					lowerCamelCase    )
      ]

      # map the alphabet characters to the modified alphabet characters
      # going 'vertically' through the modified alphabet - consider columns first
      lowerCamelCase__   	=					{}
      lowerCamelCase__   	=					0
      for column in range(lowerCamelCase    ):
            for row in modified_alphabet:
                  # if current row (the last one) is too short, break out of loop
                  if len(lowerCamelCase    ) <= column:
                        break

                  # map current letter to letter in modified alphabet
                  lowerCamelCase__   	=					row[column]
                  letter_index += 1

      if verbose:
            print(lowerCamelCase    )
      # create the encrypted text by mapping the plaintext to the modified alphabet
      return "".join(mapping[char] if char in mapping else char for char in plaintext    )


if __name__ == "__main__":
      # example use
      print(mixed_keyword("""college""", """UNIVERSITY"""))





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






class       A      :
     """simple docstring"""

     def __init__(     self	: int						,	A__	: List[Any]						,	A__	: int      )					->							List[str]:
           lowerCamelCase__   	=					0
           # max greyscale value for #FFFFFF
           lowerCamelCase__   	=					int(self.get_greyscale(2_5_5						,	2_5_5						,	2_5_5      )      )

           if not self.min_threshold < threshold < self.max_threshold:
                 lowerCamelCase__   	=					F"""Factor value should be from 0 to {self.max_threshold}"""
                 raise ValueError(A__      )

           lowerCamelCase__   	=					input_img
           lowerCamelCase__   	=					threshold
           lowerCamelCase__	,		lowerCamelCase__   	=					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
           lowerCamelCase__   	=					[
               [0 for _ in range(self.height + 4      )] for __ in range(self.width + 1      )
           ]
           lowerCamelCase__   	=					np.ones((self.width, self.height, 3)						,	np.uinta      ) * 2_5_5




     @classmethod
     def 			__snake_case (     cls	: int						,	A__	: int						,	A__	: int						,	A__	: int      )					->							float:
           return 0.114 * blue + 0.587 * green + 0.2126 * red




     def 			__snake_case (     self	: List[Any]      )					->							None:
           for y in range(self.height      ):
                 for x in range(self.width      ):
                       lowerCamelCase__   	=					int(self.get_greyscale(*self.input_img[y][x]      )      )
                       if self.threshold > greyscale + self.error_table[y][x]:
                             lowerCamelCase__   	=					(0, 0, 0)
                             lowerCamelCase__   	=					greyscale + self.error_table[x][y]
                       else:
                             lowerCamelCase__   	=					(2_5_5, 2_5_5, 2_5_5)
                             lowerCamelCase__   	=					greyscale + self.error_table[x][y] - 2_5_5
                       self.error_table[y][x + 1] += int(8 / 3_2 * current_error      )
                       self.error_table[y][x + 2] += int(4 / 3_2 * current_error      )
                       self.error_table[y + 1][x] += int(8 / 3_2 * current_error      )
                       self.error_table[y + 1][x + 1] += int(4 / 3_2 * current_error      )
                       self.error_table[y + 1][x + 2] += int(2 / 3_2 * current_error      )
                       self.error_table[y + 1][x - 1] += int(4 / 3_2 * current_error      )
                       self.error_table[y + 1][x - 2] += int(2 / 3_2 * current_error      )


if __name__ == "__main__":
      # create Burke's instances with original images in greyscale
      __SCREAMING_SNAKE_CASE     : Optional[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()