





'''simple docstring'''







from collections import Counter
from functools import total_ordering

from data_structures.heap.heap import Heap


@total_ordering
class        __a   :

							def __init__(				self				:  Union[str, Any]							,  __magic_name__				:  str							,  __magic_name__				:  int )       ->							None:







													"""simple docstring"""
													UpperCAmelCase_      :   Union[str, Any]      =	word
													UpperCAmelCase_      :   Optional[Any]      =	count

							def __eq__(				self				:  Dict							,  __magic_name__				:  object )       ->							bool:







													"""simple docstring"""
													if not isinstance(__magic_name__							,  __magic_name__ ):
																			return NotImplemented
													return self.count == other.count



							def __lt__(				self				:  List[str]							,  __magic_name__				:  object )       ->							bool:







													"""simple docstring"""
													if not isinstance(__magic_name__							,  __magic_name__ ):
																			return NotImplemented
													return self.count < other.count





def 							lowerCamelCase_   (	SCREAMING_SNAKE_CASE__   :      list[str],      SCREAMING_SNAKE_CASE__   :      int )			->						list[str]:
						UpperCAmelCase_      :   Heap[WordCount]      =	Heap()
						UpperCAmelCase_      :   int      =	Counter(SCREAMING_SNAKE_CASE__ )
						heap.build_max_heap(
						    [WordCount(SCREAMING_SNAKE_CASE__,      SCREAMING_SNAKE_CASE__ ) for word, count in count_by_word.items()] )
						return [heap.extract_max().word for _ in range(min(SCREAMING_SNAKE_CASE__,      len(SCREAMING_SNAKE_CASE__ ) ) )]


if __name__ == "__main__":
					import doctest

					doctest.testmod()











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()