How would you solve this by using Python 3.8 version class Graph:    def __init__(self, num_nodes):        self.num_nodes = num_nodes        # Initialize a 2D matrix with zeros        self.adj_matrix = [[0] * num_nodes for _ in range(num_nodes)]     def add_edge(self, node1, node2):        # Add an undirected edge between node1 and node2        self.adj_matrix[node1][node2] = 1        self.adj_matrix[node2][node1] = 1     def remove_edge(self, node1, node2):        # Remove the edge between node1 and node2        self.adj_matrix[node1][node2] = 0        self.adj_matrix[node2][node1] = 0     def num_edges(self):        num_edges = 1        for i in range(self.num_nodes):            for j in range(i+1, self.num_nodes):                if self.adj_matrix[i][j] == 1:                    num_edges += 1        return num_edges     def num_edges_in_set(self, node, subset):        # count the number of edges joining the given node and nodes in subset.        # example input: 1, {0, 2}        num_edges = 0        for s in subset:            if self.adj_matrix[node][s] == 1:                num_edges += 1        return num_edges     def edges_between_sets(self, setX, setY):        # TODO: return the edges that have one end in setX, another end in setY        pass     def edge_cut(self, setX):        # TODO: return the edge cut of a given subset of vertices        pass     def is_even(self):        # TODO: return true is the graph is even, false otherwise        pass     def count_components(self):        # return the number of components in graph.        def dfs(node, visited):            visited[node] = True            for neighbor, is_edge in enumerate(self.adj_matrix[node]):                if is_edge and not visited[neighbor]:                    dfs(neighbor, visited)         visited = [False] * self.num_nodes        num_components = 0         for node in range(self.num_nodes):            if not visited[node]:                # If the node hasn't been visited, it's a new component                dfs(node, visited)                num_components += 1         return num_components     def is_connected(self):        # TODO: return true is the graph is connected, false otherwise        pass     def is_bridge(self, edge):        # TODO: return true if the given edge is an bridge, false otherwise        # edge is given as a python pair.        pass     def is_adjacent(self, node1, node2):        if self.adj_matrix[node1][node2] == 1:            return True        else:            return False     def print_graph(self):        # Print the adjacency matrix        for row in self.adj_matrix:            print(" ".join(map(str, row))) if __name__ == "__main__":    # use case    test_graph = Graph(3)    test_graph.add_edge(1,0)    test_graph.add_edge(1, 2)    print("Is even: ", test_graph.is_even())    x = {1}    print("Edge cut is ", test_graph.edge_cut(x))    print("Is connected: ", test_graph.is_connected())    print("Is bridge: ", test_graph.is_bridge((1, 2)))   from Graph import *import copy def Fleury(g, u):    # TODO: implement Fleury's algorithm.    # input: a graph and a vertex of the graph,    # return: an array of vertices representing the Euler tour.     # Return empty array if g is not even or not connected.    if not g.is_even() or not g.is_connected():        return []     # Run the algorithm when g is even and connected    W = [u]    x = u    F = copy.deepcopy(g)    edge_cut = F.edge_cut({x})    current_edge = (-1, -1)    pass # testtest_graph = Graph(5)test_graph.add_edge(0,3)test_graph.add_edge(0,2)test_graph.add_edge(1,3)test_graph.add_edge(1,2)test_graph.add_edge(2,3)test_graph.add_edge(2,4)test_graph.add_edge(3,4)print(Fleury(test_graph, 1))

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
icon
Related questions
Question

How would you solve this by using Python 3.8 version

class Graph:
    def __init__(self, num_nodes):
        self.num_nodes = num_nodes
        # Initialize a 2D matrix with zeros
        self.adj_matrix = [[0] * num_nodes for _ in range(num_nodes)]

    def add_edge(self, node1, node2):
        # Add an undirected edge between node1 and node2
        self.adj_matrix[node1][node2] = 1
        self.adj_matrix[node2][node1] = 1

    def remove_edge(self, node1, node2):
        # Remove the edge between node1 and node2
        self.adj_matrix[node1][node2] = 0
        self.adj_matrix[node2][node1] = 0

    def num_edges(self):
        num_edges = 1
        for i in range(self.num_nodes):
            for j in range(i+1, self.num_nodes):
                if self.adj_matrix[i][j] == 1:
                    num_edges += 1
        return num_edges

    def num_edges_in_set(self, node, subset):
        # count the number of edges joining the given node and nodes in subset.
        # example input: 1, {0, 2}
        num_edges = 0
        for s in subset:
            if self.adj_matrix[node][s] == 1:
                num_edges += 1
        return num_edges

    def edges_between_sets(self, setX, setY):
        # TODO: return the edges that have one end in setX, another end in setY
        pass

    def edge_cut(self, setX):
        # TODO: return the edge cut of a given subset of vertices
        pass

    def is_even(self):
        # TODO: return true is the graph is even, false otherwise
        pass

    def count_components(self):
        # return the number of components in graph.
        def dfs(node, visited):
            visited[node] = True
            for neighbor, is_edge in enumerate(self.adj_matrix[node]):
                if is_edge and not visited[neighbor]:
                    dfs(neighbor, visited)

        visited = [False] * self.num_nodes
        num_components = 0

        for node in range(self.num_nodes):
            if not visited[node]:
                # If the node hasn't been visited, it's a new component
                dfs(node, visited)
                num_components += 1

        return num_components

    def is_connected(self):
        # TODO: return true is the graph is connected, false otherwise
        pass

    def is_bridge(self, edge):
        # TODO: return true if the given edge is an bridge, false otherwise
        # edge is given as a python pair.
        pass

    def is_adjacent(self, node1, node2):
        if self.adj_matrix[node1][node2] == 1:
            return True
        else:
            return False

    def print_graph(self):
        # Print the adjacency matrix
        for row in self.adj_matrix:
            print(" ".join(map(str, row)))

if __name__ == "__main__":
    # use case
    test_graph = Graph(3)
    test_graph.add_edge(1,0)
    test_graph.add_edge(1, 2)
    print("Is even: ", test_graph.is_even())
    x = {1}
    print("Edge cut is ", test_graph.edge_cut(x))
    print("Is connected: ", test_graph.is_connected())
    print("Is bridge: ", test_graph.is_bridge((1, 2)))

 

from Graph import *
import copy

def Fleury(g, u):
    # TODO: implement Fleury's algorithm.
    # input: a graph and a vertex of the graph,
    # return: an array of vertices representing the Euler tour.

    # Return empty array if g is not even or not connected.
    if not g.is_even() or not g.is_connected():
        return []

    # Run the algorithm when g is even and connected
    W = [u]
    x = u
    F = copy.deepcopy(g)
    edge_cut = F.edge_cut({x})
    current_edge = (-1, -1)
    pass

# test
test_graph = Graph(5)
test_graph.add_edge(0,3)
test_graph.add_edge(0,2)
test_graph.add_edge(1,3)
test_graph.add_edge(1,2)
test_graph.add_edge(2,3)
test_graph.add_edge(2,4)
test_graph.add_edge(3,4)
print(Fleury(test_graph, 1))

Expert Solution
steps

Step by step

Solved in 2 steps

Blurred answer
Knowledge Booster
Operations of Linked List
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, computer-science and related others by exploring similar questions and additional content below.
Similar questions
Recommended textbooks for you
Database System Concepts
Database System Concepts
Computer Science
ISBN:
9780078022159
Author:
Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:
McGraw-Hill Education
Starting Out with Python (4th Edition)
Starting Out with Python (4th Edition)
Computer Science
ISBN:
9780134444321
Author:
Tony Gaddis
Publisher:
PEARSON
Digital Fundamentals (11th Edition)
Digital Fundamentals (11th Edition)
Computer Science
ISBN:
9780132737968
Author:
Thomas L. Floyd
Publisher:
PEARSON
C How to Program (8th Edition)
C How to Program (8th Edition)
Computer Science
ISBN:
9780133976892
Author:
Paul J. Deitel, Harvey Deitel
Publisher:
PEARSON
Database Systems: Design, Implementation, & Manag…
Database Systems: Design, Implementation, & Manag…
Computer Science
ISBN:
9781337627900
Author:
Carlos Coronel, Steven Morris
Publisher:
Cengage Learning
Programmable Logic Controllers
Programmable Logic Controllers
Computer Science
ISBN:
9780073373843
Author:
Frank D. Petruzella
Publisher:
McGraw-Hill Education