

import heapq

def      a__	(						UpperCAmelCase				:     Optional[int]							,					UpperCAmelCase				:     Optional[Any]							,					UpperCAmelCase				:     List[str]     )    ->		str:
  UpperCAmelCase			:				Union[str, Any]										=					[(0, start)]  # cost from start node,end node
  UpperCAmelCase			:				Optional[int]										=					set()
  while heap:
    ((UpperCAmelCase)					,		(UpperCAmelCase))			:				Tuple										=					heapq.heappop(__lowerCamelCase     )
    if u in visited:
      continue
    visited.add(__lowerCamelCase     )
    if u == end:
      return cost
    for v, c in graph[u]:
      if v in visited:
        continue
      UpperCAmelCase			:				Dict										=					cost + c
      heapq.heappush(__lowerCamelCase							,					(next_item, v)     )
  return -1


_lowerCamelCase							:  Optional[Any]     =				{
    "A": [["B", 2], ["C", 5]],
    "B": [["A", 2], ["D", 3], ["E", 1], ["F", 1]],
    "C": [["A", 5], ["F", 3]],
    "D": [["B", 3]],
    "E": [["B", 4], ["F", 3]],
    "F": [["C", 3], ["E", 3]],
}
_lowerCamelCase							:  Optional[int]     =				{
    "B": [["C", 1]],
    "C": [["D", 1]],
    "D": [["F", 1]],
    "E": [["B", 1], ["F", 3]],
    "F": [],
}
_lowerCamelCase							:  str     =				{
    "B": [["C", 1]],
    "C": [["D", 1]],
    "D": [["F", 1]],
    "E": [["B", 1], ["G", 2]],
    "F": [],
    "G": [["F", 1]],
}

_lowerCamelCase							:  Union[str, Any]     =				dijkstra(G, "E", "C")
print(short_distance)  # E -- 3 --> F -- 3 --> C == 6

_lowerCamelCase							:  List[str]     =				dijkstra(Ga, "E", "F")
print(short_distance)  # E -- 3 --> F == 3

_lowerCamelCase							:  Dict     =				dijkstra(Ga, "E", "F")
print(short_distance)  # E -- 2 --> G -- 1 --> F == 3

if __name__ == "__main__":
     import doctest

     doctest.testmod()









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







class     __lowerCamelCase     :


							"""simple docstring"""

							def __init__(  self						,       UpperCAmelCase						,       UpperCAmelCase  )     ->       Tuple:






								'''simple docstring'''






								lowercase_			 = 0
								# max greyscale value for #FFFFFF
								lowercase_			 = int(self.get_greyscale(255						,       255						,       255  )  )

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

								lowercase_			 = input_img
								lowercase_			 = threshold
								lowercase_ ,	lowercase_			 = 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
								lowercase_			 = [
								    [0 for _ in range(self.height + 4  )] for __ in range(self.width + 1  )
								]
								lowercase_			 = np.ones((self.width, self.height, 3)						,       np.uinta  ) * 255




							@classmethod
							def 				A__      (  cls						,       UpperCAmelCase						,       UpperCAmelCase						,       UpperCAmelCase  )     ->       float:






								'''simple docstring'''






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




							def 				A__      (  self  )     ->       None:






								'''simple docstring'''






								for y in range(self.height  ):
									for x in range(self.width  ):
										lowercase_			 = int(self.get_greyscale(*self.input_img[y][x]  )  )
										if self.threshold > greyscale + self.error_table[y][x]:
											lowercase_			 = (0, 0, 0)
											lowercase_			 = greyscale + self.error_table[x][y]
										else:
											lowercase_			 = (255, 255, 255)
											lowercase_			 = 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
							SCREAMING_SNAKE_CASE__       			=				[
							    Burkes(imread("""image_data/lena.jpg""", 1), threshold)
							    for threshold in (1, 1_2_6, 1_3_0, 1_4_0)
							]

							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()

