






from cva import destroyAllWindows, imread, imshow, waitKey





def 		A_			(		lowercase_					,       lowercase_	)							->Optional[Any]:







 """simple docstring"""

 SCREAMING_SNAKE_CASE  , SCREAMING_SNAKE_CASE							  =						img.shape[0], img.shape[1]

 def to_grayscale(lowercase_					,       lowercase_					,       lowercase_	):
  return 0.2_1_2_6 * red + 0.5_8_7 * green + 0.1_1_4 * blue

 def normalize(lowercase_	):
  return min(lowercase_					,       2_5_5	)

 for i in range(lowercase_	):
  for j in range(lowercase_	):
   SCREAMING_SNAKE_CASE							  =						int(to_grayscale(*img[i][j]	)	)
   SCREAMING_SNAKE_CASE							  =						[
       normalize(lowercase_	),
       normalize(greyscale + factor	),
       normalize(greyscale + 2 * factor	),
   ]

 return img


if __name__ == "__main__":
      # read original image
      __UpperCAmelCase      				=							{
          percentage: imread("image_data/lena.jpg", 1) for percentage in (1_0, 2_0, 3_0, 4_0)
      }

      for percentage, img in images.items():
            make_sepia(img, percentage)

      for percentage, img in images.items():
            imshow(f'Original image with sepia (factor: {percentage})', img)

      waitKey(0)
      destroyAllWindows()












import math
import sys
class 					a_:



     """simple docstring"""



     def __init__(						self			:					Optional[int])    ->					List[Any]:

      """simple docstring"""
      SCREAMING_SNAKE_CASE							  =						0
      SCREAMING_SNAKE_CASE							  =						[]
      SCREAMING_SNAKE_CASE							  =						{}  # To store the pos of node in array





     def   __UpperCamelCase		(						self			:					Optional[int])    ->					Optional[int]:

      """simple docstring"""
      return self.cur_size == 0





     def   __UpperCamelCase		(						self			:					List[str]       ,       lowerCAmelCase__			:					str)    ->					Dict:

      """simple docstring"""
      SCREAMING_SNAKE_CASE							  =						self.left(lowerCAmelCase__)
      SCREAMING_SNAKE_CASE							  =						self.right(lowerCAmelCase__)
      if lc < self.cur_size and self.array(lowerCAmelCase__)[0] < self.array(lowerCAmelCase__)[0]:
       SCREAMING_SNAKE_CASE							  =						lc
      else:
       SCREAMING_SNAKE_CASE							  =						idx
      if rc < self.cur_size and self.array(lowerCAmelCase__)[0] < self.array(lowerCAmelCase__)[0]:
       SCREAMING_SNAKE_CASE							  =						rc
      if smallest != idx:
       self.swap(lowerCAmelCase__       ,       lowerCAmelCase__)
       self.min_heapify(lowerCAmelCase__)





     def   __UpperCamelCase		(						self			:					Any       ,       lowerCAmelCase__			:					Tuple)    ->					Optional[Any]:

      """simple docstring"""
      # Inserts a node into the Priority Queue
      SCREAMING_SNAKE_CASE							  =						self.cur_size
      self.cur_size += 1
      self.array.append((sys.maxsize, tup[1]))
      self.decrease_key((sys.maxsize, tup[1])       ,       tup[0])





     def   __UpperCamelCase		(						self			:					Dict)    ->					Optional[Any]:

      """simple docstring"""
      # Removes and returns the min element at top of priority queue
      SCREAMING_SNAKE_CASE							  =						self.array[0][1]
      SCREAMING_SNAKE_CASE							  =						self.array[self.cur_size - 1]
      self.cur_size -= 1
      self.min_heapify(1)
      del self.pos[min_node]
      return min_node





     def   __UpperCamelCase		(						self			:					List[Any]       ,       lowerCAmelCase__			:					Dict)    ->					int:

      """simple docstring"""
      # returns the index of left child
      return 2 * i + 1





     def   __UpperCamelCase		(						self			:					Any       ,       lowerCAmelCase__			:					List[str])    ->					Optional[Any]:

      """simple docstring"""
      # returns the index of right child
      return 2 * i + 2





     def   __UpperCamelCase		(						self			:					Tuple       ,       lowerCAmelCase__			:					List[Any])    ->					Dict:

      """simple docstring"""
      # returns the index of parent
      return math.floor(i / 2)





     def   __UpperCamelCase		(						self			:					List[str]       ,       lowerCAmelCase__			:					List[str]       ,       lowerCAmelCase__			:					Any)    ->					List[str]:

      """simple docstring"""
      # swaps array elements at indices i and j
      # update the pos{}
      SCREAMING_SNAKE_CASE							  =						j
      SCREAMING_SNAKE_CASE							  =						i
      SCREAMING_SNAKE_CASE							  =						self.array[i]
      SCREAMING_SNAKE_CASE							  =						self.array[j]
      SCREAMING_SNAKE_CASE							  =						temp





     def   __UpperCamelCase		(						self			:					Union[str, Any]       ,       lowerCAmelCase__			:					Dict       ,       lowerCAmelCase__			:					Optional[Any])    ->					Any:

      """simple docstring"""
      SCREAMING_SNAKE_CASE							  =						self.pos[tup[1]]
      # assuming the new_d is atmost old_d
      SCREAMING_SNAKE_CASE							  =						(new_d, tup[1])
      while idx > 0 and self.array[self.par(lowerCAmelCase__)][0] > self.array[idx][0]:
       self.swap(lowerCAmelCase__       ,       self.par(lowerCAmelCase__))
       SCREAMING_SNAKE_CASE							  =						self.par(lowerCAmelCase__)

class 					a_:



     """simple docstring"""



     def __init__(						self			:					Any       ,       lowerCAmelCase__			:					str)    ->					str:

      """simple docstring"""
      SCREAMING_SNAKE_CASE							  =						{}  # To store graph: u -> (v,w)
      SCREAMING_SNAKE_CASE							  =						num  # Number of nodes in graph
      # To store the distance from source vertex
      SCREAMING_SNAKE_CASE							  =						[0] * self.num_nodes
      SCREAMING_SNAKE_CASE							  =						[-1] * self.num_nodes  # To store the path





     def   __UpperCamelCase		(						self			:					List[str]       ,       lowerCAmelCase__			:					Optional[Any]       ,       lowerCAmelCase__			:					Union[str, Any]       ,       lowerCAmelCase__			:					List[Any])    ->					Tuple:

      """simple docstring"""
      #  Edge going from node u to v and v to u with weight w
      # u (w)-> v, v (w) -> u
      # Check if u already in graph
      if u in self.adjList:
       self.adjList[u].append((v, w))
      else:
       SCREAMING_SNAKE_CASE							  =						[(v, w)]

      # Assuming undirected graph
      if v in self.adjList:
       self.adjList[v].append((u, w))
      else:
       SCREAMING_SNAKE_CASE							  =						[(u, w)]





     def   __UpperCamelCase		(						self			:					Optional[int])    ->					Tuple:

      """simple docstring"""
      # u -> v(w)
      for u in self.adjList:
       print(lowerCAmelCase__       ,       '->'       ,       ' -> '.join(str(f'''{v}({w})''') for v, w in self.adjList[u]))





     def   __UpperCamelCase		(						self			:					int       ,       lowerCAmelCase__			:					List[str])    ->					List[Any]:

      """simple docstring"""
      # Flush old junk values in par[]
      SCREAMING_SNAKE_CASE							  =						[-1] * self.num_nodes
      # src is the source node
      SCREAMING_SNAKE_CASE							  =						0
      SCREAMING_SNAKE_CASE							  =						PriorityQueue()
      q.insert((0, src))  # (dist from src, node)
      for u in self.adjList:
       if u != src:
        SCREAMING_SNAKE_CASE							  =						sys.maxsize  # Infinity
        SCREAMING_SNAKE_CASE							  =						-1

      while not q.is_empty():
       SCREAMING_SNAKE_CASE							  =						q.extract_min()  # Returns node with the min dist from source
       # Update the distance of all the neighbours of u and
       # if their prev dist was INFINITY then push them in Q
       for v, w in self.adjList[u]:
        SCREAMING_SNAKE_CASE							  =						self.dist[u] + w
        if self.dist[v] > new_dist:
         if self.dist[v] == sys.maxsize:
          q.insert((new_dist, v))
         else:
          q.decrease_key((self.dist[v], v)       ,       lowerCAmelCase__)
         SCREAMING_SNAKE_CASE							  =						new_dist
         SCREAMING_SNAKE_CASE							  =						u

        # Show the shortest distances from src
      self.show_distances(lowerCAmelCase__)





     def   __UpperCamelCase		(						self			:					Dict       ,       lowerCAmelCase__			:					List[str])    ->					Tuple:

      """simple docstring"""
      print(f'''Distance from node: {src}''')
      for u in range(self.num_nodes):
       print(f'''Node {u} has distance: {self.dist[u]}''')





     def   __UpperCamelCase		(						self			:					List[Any]       ,       lowerCAmelCase__			:					Optional[Any]       ,       lowerCAmelCase__			:					Any)    ->					Optional[int]:

      """simple docstring"""
      # To show the shortest path from src to dest
      # WARNING: Use it *after* calling dijkstra
      SCREAMING_SNAKE_CASE							  =						[]
      SCREAMING_SNAKE_CASE							  =						0
      SCREAMING_SNAKE_CASE							  =						dest
      # Backtracking from dest to src
      while self.par[temp] != -1:
       path.append(lowerCAmelCase__)
       if temp != src:
        for v, w in self.adjList[temp]:
         if v == self.par[temp]:
          cost += w
          break
       SCREAMING_SNAKE_CASE							  =						self.par[temp]
      path.append(lowerCAmelCase__)
      path.reverse()

      print(f'''----Path to reach {dest} from {src}----''')
      for u in path:
       print(f'''{u}'''       ,       end=' ')
       if u != dest:
        print('-> '       ,       end='')

      print('\nTotal cost of path: '       ,       lowerCAmelCase__)


if __name__ == "__main__":
      __UpperCAmelCase      				=							Graph(9)
      graph.add_edge(0, 1, 4)
      graph.add_edge(0, 7, 8)
      graph.add_edge(1, 2, 8)
      graph.add_edge(1, 7, 1_1)
      graph.add_edge(2, 3, 7)
      graph.add_edge(2, 8, 2)
      graph.add_edge(2, 5, 4)
      graph.add_edge(3, 4, 9)
      graph.add_edge(3, 5, 1_4)
      graph.add_edge(4, 5, 1_0)
      graph.add_edge(5, 6, 2)
      graph.add_edge(6, 7, 1)
      graph.add_edge(6, 8, 6)
      graph.add_edge(7, 8, 7)
      graph.show_graph()
      graph.dijkstra(0)
      graph.show_path(0, 4)

# OUTPUT
# 0 -> 1(4) -> 7(8)
# 1 -> 0(4) -> 2(8) -> 7(11)
# 7 -> 0(8) -> 1(11) -> 6(1) -> 8(7)
# 2 -> 1(8) -> 3(7) -> 8(2) -> 5(4)
# 3 -> 2(7) -> 4(9) -> 5(14)
# 8 -> 2(2) -> 6(6) -> 7(7)
# 5 -> 2(4) -> 3(14) -> 4(10) -> 6(2)
# 4 -> 3(9) -> 5(10)
# 6 -> 5(2) -> 7(1) -> 8(6)
# Distance from node: 0
# Node 0 has distance: 0
# Node 1 has distance: 4
# Node 2 has distance: 12
# Node 3 has distance: 19
# Node 4 has distance: 21
# Node 5 has distance: 11
# Node 6 has distance: 9
# Node 7 has distance: 8
# Node 8 has distance: 14
# ----Path to reach 4 from 0----
# 0 -> 7 -> 6 -> 5 -> 4
# Total cost of path:  21




