find the error in this code to display the required output from collections import deque def shortest_path(graph, start, goal): # keep track of explored nodes explored = [] # keep track of all the paths to be checked queue = deque([[start]]) if start == goal: print("Start and goal are the same") return # returns path if found while queue: # gets the first path from the queue path = queue.popleft() # gets the last node from the path node = path[-1] if node not in explored: neighbours = graph[node] # goes through all neighbour nodes, constructing a new path and # pushing it into the queue for neighbour in neighbours: new_path = list(path) new_path.append(neighbour) queue.append(new_path) # returns path if neighbour is goal if neighbour == goal: print("Shortest path found: ", *new_path) return new_path # marks node as explored explored.append(node) # returns None if goal not reached print("So sorry, but a connecting path does not exist :(") return # define the graph graph = { 1: [2,3], 2: [1,3], 3: [1,2,5, 4], 4: [6,11,3,5], 5: [7,4,3], 6: [8,4], 7: [5,9], 8: [6], 9: [7,10], 10: [9,12], 11: [12,4], 12: [10,11] } # modify the dfs function to return the charge when it reaches the charging station def dfs(graph, start, visited, charge): # current node as visited visited.add(start) # Check the Roomba needs to enter the charging station if charge <= 6: print(f" {start} (Charging, {charge} Wh) -> ") charge = 12 return charge else: print(f"{start} (Cleaning, {charge} Wh) ->") charge -= 1 # Take the list of adjacent nodes adj_nodes = graph[start] # Visit the unvisited adjacent nodes for node in adj_nodes: if node not in visited: charge = dfs(graph, node, visited, charge) return charge # ask the user to enter the starting node start_node = int(input("Enter starting node: ")) # perform depth-first search starting from the starting node visited = set() charge = dfs(graph, start_node, visited, 12) # keep looping until the Roomba has enough charge to reach the charging station while charge <= 6: # find the shortest path from the current node to the charging station shortest_path(graph, start_node, 12) # update the start node to be the current node start_node = shortest # Sample output Enter starting node: 1 1 (Cleaning, 12 Wh) -> 2 (Cleaning, 11 Wh) -> 3 (Cleaning, 10 Wh) -> 4 (Cleaning, 9 Wh)-> 6 (Cleaning, 8 Wh)-> 8 (Cleaning, 7 Wh)-> 6 (Charging, 6 Wh)-> 4 (Charging, 5 Wh)-> 11 (Charging, 4 Wh)-> 12 (Cleaning, 12 Wh)-> 10 (Cleaning, 11 Wh)-> 9 (Cleaning, 10 Wh)-> 7 (Cleaning, 9 Wh)-> 5 (Cleaning, 8 Wh)

find the error in this code to display the required output from collections import deque def shortest_path(graph, start, goal): # keep track of explored nodes explored = [] # keep track of all the paths to be checked queue = deque([[start]]) if start == goal: print("Start and goal are the same") return # returns path if found while queue: # gets the first path from the queue path = queue.popleft() # gets the last node from the path node = path[-1] if node not in explored: neighbours = graph[node] # goes through all neighbour nodes, constructing a new path and # pushing it into the queue for neighbour in neighbours: new_path = list(path) new_path.append(neighbour) queue.append(new_path) # returns path if neighbour is goal if neighbour == goal: print("Shortest path found: ", *new_path) return new_path # marks node as explored explored.append(node) # returns None if goal not reached print("So sorry, but a connecting path does not exist :(") return # define the graph graph = { 1: [2,3], 2: [1,3], 3: [1,2,5, 4], 4: [6,11,3,5], 5: [7,4,3], 6: [8,4], 7: [5,9], 8: [6], 9: [7,10], 10: [9,12], 11: [12,4], 12: [10,11] } # modify the dfs function to return the charge when it reaches the charging station def dfs(graph, start, visited, charge): # current node as visited visited.add(start) # Check the Roomba needs to enter the charging station if charge <= 6: print(f" {start} (Charging, {charge} Wh) -> ") charge = 12 return charge else: print(f"{start} (Cleaning, {charge} Wh) ->") charge -= 1 # Take the list of adjacent nodes adj_nodes = graph[start] # Visit the unvisited adjacent nodes for node in adj_nodes: if node not in visited: charge = dfs(graph, node, visited, charge) return charge # ask the user to enter the starting node start_node = int(input("Enter starting node: ")) # perform depth-first search starting from the starting node visited = set() charge = dfs(graph, start_node, visited, 12) # keep looping until the Roomba has enough charge to reach the charging station while charge <= 6: # find the shortest path from the current node to the charging station shortest_path(graph, start_node, 12) # update the start node to be the current node start_node = shortest # Sample output Enter starting node: 1 1 (Cleaning, 12 Wh) -> 2 (Cleaning, 11 Wh) -> 3 (Cleaning, 10 Wh) -> 4 (Cleaning, 9 Wh)-> 6 (Cleaning, 8 Wh)-> 8 (Cleaning, 7 Wh)-> 6 (Charging, 6 Wh)-> 4 (Charging, 5 Wh)-> 11 (Charging, 4 Wh)-> 12 (Cleaning, 12 Wh)-> 10 (Cleaning, 11 Wh)-> 9 (Cleaning, 10 Wh)-> 7 (Cleaning, 9 Wh)-> 5 (Cleaning, 8 Wh)

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

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Question

find the error in this code to display the required output

from collections import deque

def shortest_path(graph, start, goal):

# keep track of explored nodes

explored = []

# keep track of all the paths to be checked

queue = deque([[start]])

if start == goal:

print("Start and goal are the same")

return

# returns path if found

while queue:

# gets the first path from the queue

path = queue.popleft()

# gets the last node from the path

node = path[-1]

if node not in explored:

neighbours = graph[node]

# goes through all neighbour nodes, constructing a new path and

# pushing it into the queue

for neighbour in neighbours:

new_path = list(path)

new_path.append(neighbour)

queue.append(new_path)

# returns path if neighbour is goal

if neighbour == goal:

print("Shortest path found: ", *new_path)

return new_path

# marks node as explored

explored.append(node)

# returns None if goal not reached

print("So sorry, but a connecting path does not exist :(")

return

# define the graph

graph = {

1: [2,3],

2: [1,3],

3: [1,2,5, 4],

4: [6,11,3,5],

5: [7,4,3],

6: [8,4],

7: [5,9],

8: [6],

9: [7,10],

10: [9,12],

11: [12,4],

12: [10,11]

}

# modify the dfs function to return the charge when it reaches the charging station

def dfs(graph, start, visited, charge):

# current node as visited

visited.add(start)

# Check the Roomba needs to enter the charging station

if charge <= 6:

print(f" {start} (Charging, {charge} Wh) -> ")

charge = 12

return charge

else:

print(f"{start} (Cleaning, {charge} Wh) ->")

charge -= 1

# Take the list of adjacent nodes

adj_nodes = graph[start]

# Visit the unvisited adjacent nodes

for node in adj_nodes:

if node not in visited:

charge = dfs(graph, node, visited, charge)

return charge

# ask the user to enter the starting node

start_node = int(input("Enter starting node: "))

# perform depth-first search starting from the starting node

visited = set()

charge = dfs(graph, start_node, visited, 12)

# keep looping until the Roomba has enough charge to reach the charging station

while charge <= 6:

# find the shortest path from the current node to the charging station

shortest_path(graph, start_node, 12)

# update the start node to be the current node

start_node = shortest

# Sample output
Enter starting node: 1
1 (Cleaning, 12 Wh) ->
2 (Cleaning, 11 Wh) ->
3 (Cleaning, 10 Wh) ->
4 (Cleaning, 9 Wh)->
6 (Cleaning, 8 Wh)->
8 (Cleaning, 7 Wh)->
6 (Charging, 6 Wh)->
4 (Charging, 5 Wh)->
11 (Charging, 4 Wh)->
12 (Cleaning, 12 Wh)->
10 (Cleaning, 11 Wh)->
9 (Cleaning, 10 Wh)->
7 (Cleaning, 9 Wh)->
5 (Cleaning, 8 Wh)

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