# Create a node - the datapoints within the graph class Node: definit_(self, x, y): self.x = x self.y = y self.neighbours = list() # Start function - acts as a starting point for the flood fill algorithm def start(): # Sample image represented as 2D array of numbers image = [ [1,0,0,0,0], [1,1,0,1,0], [0,1,1,1,0], [0,1,1,1,1], [0,1,1,0,1] ] graph= Graph() print(graph.floodFill(image, 2, 2, 2)) # DO NOT REMOVE THIS RETURN STATEMENT! return graph # The flood fill algorithm - flood fill algorithm using breadth first search class Graph: numberOfNonUniqueEdges = 0 visited=set()
# Create a node - the datapoints within the graph class Node: definit_(self, x, y): self.x = x self.y = y self.neighbours = list() # Start function - acts as a starting point for the flood fill algorithm def start(): # Sample image represented as 2D array of numbers image = [ [1,0,0,0,0], [1,1,0,1,0], [0,1,1,1,0], [0,1,1,1,1], [0,1,1,0,1] ] graph= Graph() print(graph.floodFill(image, 2, 2, 2)) # DO NOT REMOVE THIS RETURN STATEMENT! return graph # The flood fill algorithm - flood fill algorithm using breadth first search class Graph: numberOfNonUniqueEdges = 0 visited=set()
Computer Networking: A Top-Down Approach (7th Edition)
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Question
Can you help me on two section of this code. I need some guidance
The code has to implement the flood fill
- blank pixels are ignored.
- I understand I can use any breadth first search algorithm.
The code is partially written below. DO NOT re-write any code. Just need assistance where its highlighted in yellow
Please dont copy the previous bartleby tutors repsonse or fro any other source
![# Create a node - the datapoints within the graph
class Node:
def __init__(self, x, y):
self.x = x
self.y = y
self.neighbours = list()
# Start function - acts as a starting point for the flood fill algorithm
def start():
# Sample image represented as 2D array of numbers
image = [
[1,0,0,0,0],
[1,1,0,1,0],
[0,1,1,1,0],
[0,1,1,1,1],
[0,1,1,0,1]
]
graph = Graph()
print(graph.flood Fill(image, 2, 2, 2))
# DO NOT REMOVE THIS RETURN STATEMENT!
return graph
# The flood fill algorithm - flood fill algorithm using breadth first search
class Graph:
numberOfNonUniqueEdges = 0
visited=set()
def floodFill(self, image, x, y, pixel):
start Node(x, y)
queue = list()
queue.append(start)
# Remember to add the x and y coordinates of newly discovered nodes to the visited set
###
### YOUR CODE HERE
###
# Return the modified image represented as 2D array of numbers
return image
def neighbours(self, image, x, y, currentNode):
U=y-1
D=y+1
L=x-1
R = x + 1
# An edge is valid if the pixel is newly discovered, i.e. an edge is created when the neighbour's
pixel value is one.
# Write the neighbours function to find the neighbours in four directions for a given pixel.
# Append
valid Node to the neighbours of the currentNode
#Remember to do boundary checking
###
### YOUR CODE HERE
###
### DO NOT REMOVE THIS LINE ###
self.numberOfNonUniqueEdges = self.numberOfNonUniqueEdges + len(currentNode.neighbours)
### ## ### ###### #### #### ####
# Return the current node's (the pixel in question) neighbours, not always a maximum of four.
# Call the start function
return currentNode.neighbours
graph = start()
●●●](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F659d3413-5117-4cc0-a948-b648c6732aa0%2F8681d95f-5371-4285-9e4b-541fe0b83567%2Fbq2at9r_processed.jpeg&w=3840&q=75)
Transcribed Image Text:# Create a node - the datapoints within the graph
class Node:
def __init__(self, x, y):
self.x = x
self.y = y
self.neighbours = list()
# Start function - acts as a starting point for the flood fill algorithm
def start():
# Sample image represented as 2D array of numbers
image = [
[1,0,0,0,0],
[1,1,0,1,0],
[0,1,1,1,0],
[0,1,1,1,1],
[0,1,1,0,1]
]
graph = Graph()
print(graph.flood Fill(image, 2, 2, 2))
# DO NOT REMOVE THIS RETURN STATEMENT!
return graph
# The flood fill algorithm - flood fill algorithm using breadth first search
class Graph:
numberOfNonUniqueEdges = 0
visited=set()
def floodFill(self, image, x, y, pixel):
start Node(x, y)
queue = list()
queue.append(start)
# Remember to add the x and y coordinates of newly discovered nodes to the visited set
###
### YOUR CODE HERE
###
# Return the modified image represented as 2D array of numbers
return image
def neighbours(self, image, x, y, currentNode):
U=y-1
D=y+1
L=x-1
R = x + 1
# An edge is valid if the pixel is newly discovered, i.e. an edge is created when the neighbour's
pixel value is one.
# Write the neighbours function to find the neighbours in four directions for a given pixel.
# Append
valid Node to the neighbours of the currentNode
#Remember to do boundary checking
###
### YOUR CODE HERE
###
### DO NOT REMOVE THIS LINE ###
self.numberOfNonUniqueEdges = self.numberOfNonUniqueEdges + len(currentNode.neighbours)
### ## ### ###### #### #### ####
# Return the current node's (the pixel in question) neighbours, not always a maximum of four.
# Call the start function
return currentNode.neighbours
graph = start()
●●●
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