# Problem 4
problem4_breadth_first_traversal = [0,]
problem4_depth_first_traversal = [0,]
def bfs(g,start):
start.setDistance(0)
start.setPred(None)
vertQueue = Queue()
vertQueue.enqueue(start)
while (vertQueue.size() > 0):
currentVert = vertQueue.dequeue()
for nbr in currentVert.getConnections():
if (nbr.getColor() == 'white'):
nbr.setColor('gray')
nbr.setDistance(currentVert.getDistance() + 1)
nbr.setPred(currentVert)
vertQueue.enqueue(nbr)
currentVert.setColor('black')
class DFSGraph(Graph):
def __init__(self):
super().__init__()
self.time = 0
def dfs(self):
for aVertex in self:
aVertex.setColor('white')
aVertex.setPred(-1)
for aVertex in self:
if aVertex.getColor() == 'white':
self.dfsvisit(aVertex)
def dfsvisit(self,startVertex):
startVertex.setColor('gray')
self.time += 1
startVertex.setDiscovery(self.time)
for nextVertex in startVertex.getConnections():
if nextVertex.getColor() == 'white':
nextVertex.setPred(startVertex)
self.dfsvisit(nextVertex)
startVertex.setColor('black')
self.time += 1
startVertex.setFinish(self.time)Homework Answers
a) BFS
Just create list and insert nodes while traversing
def bfs(g,start):
start.setDistance(0)
start.setPred(None)
List = []
vertQueue = Queue()
vertQueue.enqueue(start)
while (vertQueue.size() > 0):
currentVert = vertQueue.dequeue()
List.append(cuurentVert)
for nbr in currentVert.getConnections():
if (nbr.getColor() == 'white'):
nbr.setColor('gray')
nbr.setDistance(currentVert.getDistance() + 1)
nbr.setPred(currentVert)
vertQueue.enqueue(nbr)
currentVert.setColor('black')
return List
b) DFS
Just try to create a new list in dfs function and pass it as parameter to dfsvisit
def dfs(self):
List = []
for aVertex in self:
aVertex.setColor('white')
aVertex.setPred(-1)
for aVertex in self:
if aVertex.getColor() == 'white':
self.dfsvisit(aVertex)
return List
def dfsvisit(self,startVertex,List):
startVertex.setColor('gray')
List.append(startVertex)
self.time += 1
startVertex.setDiscovery(self.time)
for nextVertex in startVertex.getConnections():
if nextVertex.getColor() == 'white':
nextVertex.setPred(startVertex)
self.dfsvisit(nextVertex,List)
startVertex.setColor('black')
self.time += 1
startVertex.setFinish(self.time)
Add Answer to:
# Problem 4 problem4_breadth_first_traversal = [0,] problem4_depth_first_traversal = [0,] def bfs(g,start): start.set...
In Python 3 please Apply Breadth First Search (BFS) to traverse the following graph. Start your...
In Python 3 please
Apply Breadth First Search (BFS) to traverse the following graph. Start your traversal from vertex 0, and write down the order in which vertices will be visited during the traversal. 1 8 6 7 2 9 5 4 3
from collections import defaultdict # This class represents a directed graph using # adjacency list...
from collections import defaultdict # This class represents a directed graph using # adjacency list representation class Graph: # Constructor def __init__(self): # default dictionary to store graph self.graph = defaultdict(list) # function to add an edge to graph def addEdge(self,u,v): self.graph[u].append(v) # Function to print a BFS of graph def BFS(self, s): # Mark all the vertices as not visited visited = [False] * (len(self.graph)) # Create a queue for BFS queue...
In the breadth first traversal procedure BFS, each vertex v has an attribute v.color. Modify BFS...
In the breadth first traversal procedure BFS, each vertex
v has an attribute v.color. Modify BFS
so that instead of x.color, each vertex
x has a Boolean attribute called x.mark,
whose value is either TRUE or FALSE. The attribute
x.mark must be FALSE if x has never been
visited. It must be TRUE if x has been visited, but will
not be visited again.
Thank you!!!
BFS(G, s) 1 for each vertex u e G.V-(s 11, color WHITE 4 5...
Previous code: class BinarySearchTree: def __init__(self, data): self.data = data self.left = None self.right = None de...
Previous code:
class BinarySearchTree:
def __init__(self, data):
self.data = data
self.left = None
self.right = None
def search(self, find_data):
if self.data == find_data:
return self
elif find_data < self.data and self.left != None:
return self.left.search(find_data)
elif find_data > self.data and self.right != None:
return self.right.search(find_data)
else:
return None
def get_left(self):
return self.left
def get_right(self):
return self.right
def set_left(self, tree):
self.left = tree
def set_right(self, tree):
self.right = tree
def set_data(self, data):
self.data = data
def get_data(self):
return self.data
def traverse(root,order):...
Please answer all three parts. And show step-by-step answers for each part. Draw anything if necessary....
Please answer all three parts. And show step-by-step
answers for each part. Draw anything if necessary. And
please don't copy other answers to be at risk being downvoted.
Thank you.
Question 1 (50 POINTS): Given a graph G and the Breadth First Search (BFS) and Depth First Search (DFS) traversal algorithms as follows: BFSG) 1 for each vertex u € G.V – {3} 1 2 u.color = WHITE 3 u.d = 0 4 un = NIL 3 5 S.color =...
The following is an adjacency matrix of a directed graph. Start from vertex D, write down...
The following is an adjacency matrix of a directed graph. Start from vertex D, write down the order of node visited in Breadth-First- Search (BFS) traversal. (Enter the nodes in order in the following format: [A B C D E F G]) Adjacenc y Matrix ABCDEFG A 1111 000 BO00 0101 C0111010 DO 0 1 0 0 1 1 E 0 1 0 1 000 F 100 1 100 G0000100
# Problem 3 def printexp(tree): sVal = "" if tree: sVal = '(' + printexp(tree.getLeftChild()) sVal = sV...
# Problem 3
def printexp(tree):
sVal = ""
if tree:
sVal = '(' + printexp(tree.getLeftChild())
sVal = sVal + str(tree.getRootVal())
sVal = sVal + printexp(tree.getRightChild())+')'
return sVal
#### Functions and classes to help with Homework 6
#### You should not make any changes to the functions and
classes in this file,
#### but you should understand what they do and how they work.
import sys
### This function will be re-defined in hw6.py. However, it is
needed for ExpTree,
###...
(5 marks) a. The pseudo-code for breadth-first search, modified slightly from Drozdek,1 is as follows: void...
(5 marks) a. The pseudo-code for breadth-first search, modified slightly from Drozdek,1 is as follows: void breadthFirstSearch (vertex w) for all vertices u num (u) 0 null edges i=1; num (w) i++ enqueue (w) while queue is not empty dequeue ( V= for all vertices u adjacent to v if num(u) is 0 num (u) = i++; enqueue (u) attach edge (vu) to edges; output edges; Now consider the following graph. Give the breadth-first traversal of the graph, starting from...
1. Code a breadth First traversal. 2. Code a depth First traversal. Note, your traversals should return a string listing...
1. Code a breadth First traversal. 2. Code a depth First traversal. Note, your traversals should return a string listing the nodes added to the min spanning tree and the order they are added. Using Python. Starter code: from collections import deque class Edge: def __init__(self, endIndex, next = None): self.endIndex = endIndex self.next = next class Node: def __init__(self, name): self.name = name self.visited = False self.connects = None class Graph: def __init__(self): self.nodeList = [] self.size = 20...
Consider the simple graph G, given the following: (assume A=0,B=1, C=2, D=3, E=4, F=5, G=6) A...
Consider the simple graph G, given the following: (assume A=0,B=1, C=2, D=3, E=4, F=5, G=6) A 3 3 8 B D 5 ho 5 8 E F G 4 3 a) Use the Breadth-First Search algorithm to traverse G and give the traverse sequence, starting from A. Assume you always choose the candidate with the SMALLEST index among the candidates at each step. b) Use the Depth-First Search algorithm to traverse G and give the traverse sequence, starting from A....
In Python 3 please
Apply Breadth First Search (BFS) to traverse the following graph. Start your traversal from vertex 0, and write down the order in which vertices will be visited during the traversal. 1 8 6 7 2 9 5 4 3
In the breadth first traversal procedure BFS, each vertex
v has an attribute v.color. Modify BFS
so that instead of x.color, each vertex
x has a Boolean attribute called x.mark,
whose value is either TRUE or FALSE. The attribute
x.mark must be FALSE if x has never been
visited. It must be TRUE if x has been visited, but will
not be visited again.
Thank you!!!
BFS(G, s) 1 for each vertex u e G.V-(s 11, color WHITE 4 5...
Previous code:
class BinarySearchTree:
def __init__(self, data):
self.data = data
self.left = None
self.right = None
def search(self, find_data):
if self.data == find_data:
return self
elif find_data < self.data and self.left != None:
return self.left.search(find_data)
elif find_data > self.data and self.right != None:
return self.right.search(find_data)
else:
return None
def get_left(self):
return self.left
def get_right(self):
return self.right
def set_left(self, tree):
self.left = tree
def set_right(self, tree):
self.right = tree
def set_data(self, data):
self.data = data
def get_data(self):
return self.data
def traverse(root,order):...
Please answer all three parts. And show step-by-step
answers for each part. Draw anything if necessary. And
please don't copy other answers to be at risk being downvoted.
Thank you.
Question 1 (50 POINTS): Given a graph G and the Breadth First Search (BFS) and Depth First Search (DFS) traversal algorithms as follows: BFSG) 1 for each vertex u € G.V – {3} 1 2 u.color = WHITE 3 u.d = 0 4 un = NIL 3 5 S.color =...
The following is an adjacency matrix of a directed graph. Start from vertex D, write down the order of node visited in Breadth-First- Search (BFS) traversal. (Enter the nodes in order in the following format: [A B C D E F G]) Adjacenc y Matrix ABCDEFG A 1111 000 BO00 0101 C0111010 DO 0 1 0 0 1 1 E 0 1 0 1 000 F 100 1 100 G0000100
# Problem 3
def printexp(tree):
sVal = ""
if tree:
sVal = '(' + printexp(tree.getLeftChild())
sVal = sVal + str(tree.getRootVal())
sVal = sVal + printexp(tree.getRightChild())+')'
return sVal
#### Functions and classes to help with Homework 6
#### You should not make any changes to the functions and
classes in this file,
#### but you should understand what they do and how they work.
import sys
### This function will be re-defined in hw6.py. However, it is
needed for ExpTree,
###...
(5 marks) a. The pseudo-code for breadth-first search, modified slightly from Drozdek,1 is as follows: void breadthFirstSearch (vertex w) for all vertices u num (u) 0 null edges i=1; num (w) i++ enqueue (w) while queue is not empty dequeue ( V= for all vertices u adjacent to v if num(u) is 0 num (u) = i++; enqueue (u) attach edge (vu) to edges; output edges; Now consider the following graph. Give the breadth-first traversal of the graph, starting from...
Consider the simple graph G, given the following: (assume A=0,B=1, C=2, D=3, E=4, F=5, G=6) A 3 3 8 B D 5 ho 5 8 E F G 4 3 a) Use the Breadth-First Search algorithm to traverse G and give the traverse sequence, starting from A. Assume you always choose the candidate with the SMALLEST index among the candidates at each step. b) Use the Depth-First Search algorithm to traverse G and give the traverse sequence, starting from A....
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