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Help in Python please Use the output from running the sample program (GraphClient.py) for graphs to perform the following: Draw the resulting undirected graph and

Help in Python please

Use the output from running the sample program (GraphClient.py) for graphs to perform the following:

  1. Draw the resulting undirected graph and label each vertex.
  2. Draw the resulting depth-first traversal tree starting at vertex 0.
  3. Draw the resulting breadth-first traversal tree starting at vertex 0.
  4. Draw the minimum spanning tree (MST) starting at vertex 0.
  5. Draw the resulting depth-first traversal tree starting at vertex 9.
  6. Draw the resulting breadth-first traversal tree starting at vertex 9.
  7. Draw the minimum spanning tree (MST) starting at vertex 9.

All the diagrams must match the output from the program. For depth-first and breadth-first traversals you should use same drawing technique from the textbook with dotted and solid arrows for edges being visited.

Graph.py

# Implement a nondirectional graph using classes for vertices and edges class Vertex(object): # A vertex in a graph def __init__(self, name): # Constructor: stores a vertex name self.name = name # Store the name def __str__(self): # Summarize vertex in a string return ''.format(self.name) class Graph(object): # A graph containing vertices and edges def __init__(self): # Constructor self._vertices = [] # A list/array of vertices self._adjMat = {} # A hash table mapping vertex pairs to 1 def nVertices(self): # Get the number of graph vertices, i.e. return len(self._vertices) # the length of the vertices list def nEdges(self): # Get the number of graph edges by return len(self._adjMat) // 2 # dividing the # of keys by 2 def __str__(self): # Summarize the graph in a string nVertices = self.nVertices() nEdges = self.nEdges() return ''.format( nVertices, 'ex' if nVertices == 1 else 'ices', nEdges, '' if nEdges == 1 else 's') def addVertex(self, vertex): # Add a new vertex to the graph self._vertices.append(vertex) # Place at end of vertex list def validIndex(self, n): # Check that n is a valid vertex index if n < 0 or self.nVertices() <= n: # If it lies outside the raise IndexError # valid range, raise an exception return True # Otherwise it's valid def getVertex(self, n): # Get the nth vertex in the graph if self.validIndex(n): # Check that n is a valid vertex index return self._vertices[n] # and return nth vertex def addEdge(self, A, B): # Add an edge between two vertices A & B self.validIndex(A) # Check that vertex A is valid self.validIndex(B) # Check that vertex B is valid if A == B: # If vertices are the same raise ValueError # raise exception self._adjMat[A, B] = 1 # Add edge in one direction and self._adjMat[B, A] = 1 # the reverse direction def hasEdge(self, A, B): # Check for edge between vertices A & B self.validIndex(A) # Check that vertex A is valid self.validIndex(B) # Check that vertex B is valid return self._adjMat.get( # Look in adjacency matrix hash table (A, B), False) # Return either the edge count or False def vertices(self): # Generate sequence of all vertex indices return range(self.nVertices()) # Same as range up to nVertices def adjacentVertices( # Generate a sequence of vertex indices self, n): # that are adjacent to vertex n self.validIndex(n) # Check that vertex n is valid for j in self.vertices(): # Loop over all other vertices if j != n and self.hasEdge(n, j): # If other vertex connects yield j # via edge, yield other vertex index def adjacentUnvisitedVertices( # Generate a sequence of vertex self, n, # indices adjacent to vertex n that do visited, # not already show up in the visited list markVisits=True): # and mark visits in list, if requested for j in self.adjacentVertices(n): # Loop through adjacent if not visited[j]: # vertices, check visited if markVisits: # flag, and if unvisited, optionally visited[j] = True # mark the visit yield j # and yield the vertex index def depthFirst( # Traverse the vertices in depth-first self, n): # order starting at vertex n self.validIndex(n) # Check that vertex n is valid visited = [False] * self.nVertices() # Nothing visited initially stack = Stack() # Start with an empty stack stack.push(n) # and push the starting vertex index on it visited[n] = True # Mark vertex n as visited yield (n, stack) # Yield initial vertex and initial path while not stack.isEmpty(): # Loop until nothing left on stack visit = stack.peek() # Top of stack is vertex being visited adj = None for j in self.adjacentUnvisitedVertices( # Loop over adjacent visit, visited): # vertices marking them as we visit them adj = j # Next vertex is first adjacent unvisited break # one, and the rest will be visited later if adj is not None: # If there's an adjacent unvisited vertex stack.push(adj) # Push it on stack and yield (adj, stack) # yield it with the path leading to it else: # Otherwise we're visiting a dead end so stack.pop() # pop the vertex off the stack def breadthFirst( # Traverse the vertices in breadth-first self, n): # order starting at vertex n self.validIndex(n) # Check that vertex n is valid visited = [False] * self.nVertices() # Nothing visited initially queue = Queue() # Start with an empty queue and queue.insert(n) # insert the starting vertex index on it visited[n] = True # and mark starting vertex as visited while not queue.isEmpty(): # Loop until nothing left on queue visit = queue.remove() # Visit vertex at front of queue yield visit # Yield vertex to visit it for j in self.adjacentUnvisitedVertices( # Loop over adjacent visit, visited): # unvisited vertices queue.insert(j) # and insert them in the queue def minimumSpanningTree( # Compute a minimum spanning tree self, n): # starting at vertex n self.validIndex(n) # Check that vertex n is valid tree = Graph() # Initial MST is an empty graph vMap = [None] * self.nVertices() # Array to map vertex indices for vertex, path in self.depthFirst(n): vMap[vertex] = tree.nVertices() # DF visited vertex will be tree.addVertex( # last vertex in MST as we add it self.getVertex(vertex)) if len(path) > 1: # If the path has more than one vertex, tree.addEdge( # add last edge in path to MST, mapping vMap[path[-2]], vMap[path[-1]]) # vertex indices return tree def print(self, # Print all the graph's vertices and edges prefix=''): # Prefix each line with the given string print('{}{}'.format(prefix, self)) # Print summary form of graph for vertex in self.vertices(): # Loop over all vertex indices print('{}{}:'.format(prefix, vertex), # Print vertex index self.getVertex(vertex)) # and string form of vertex for k in range(vertex + 1, self.nVertices()): # Loop over if self.hasEdge(vertex, k): # higher vertex indices, if print(prefix, # there's an edge to it, print edge self._vertices[vertex].name, '<->', self._vertices[k].name) class Stack(list): # Use list to define Stack class def push(self, item): self.append(item) # push == append def peek(self): return self[-1] # Last element is top of stack def isEmpty(self): return len(self) == 0 class Queue(list): # Use list to define Queue class def insert(self, j): self.append(j) # insert == append def peek(self): return self[0] # First element is front of queue def remove(self): return self.pop(0) # Remove first element def isEmpty(self): return len(self) == 0

GraphClient.py

from Graph import * import sys, random # Default vertex names verts = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J'] seed = 3.14159 if len(sys.argv) > 1: # Use command line args if present verts = sys.argv[1:] seed = hash(''.join(verts)) random.seed(seed) # Use consistent random seed maxEdges = len(verts) ** 2 // 4 # Upper limit on number of edges graph = Graph() print('Initial graph:', graph) nVerts = len(verts) for vert in verts: graph.addVertex(Vertex(vert)) print('After adding', nVerts, 'vertices, graph contains') graph.print() for i in range(maxEdges): j = random.randrange(nVerts - 1) k = random.randrange(j + 1, nVerts) if graph.hasEdge(j, k): print('Skipping duplicate edge from', j, 'to', k) else: print('Adding edge from', j, 'to', k) graph.addEdge(j, k) print('After adding edges, graph', graph, 'contains') graph.print() print('Checking some random potential edges') for i in range(10): j = random.randrange(nVerts - 1) k = random.randrange(j + 1, nVerts) print('Does graph have edge from', j, graph.getVertex(j).name, 'to', k, graph.getVertex(k).name, '?', 'yes' if graph.hasEdge(j, k) else 'no') for start in (0, nVerts - 1): print('Depth-first traversal of graph starting at', start, ':') for visit, path in graph.depthFirst(start): print('Visiting', graph.getVertex(visit).name, 'via', path, ''.join(graph.getVertex(j).name for j in path)) print('End depth-first traversal') print('Breadth-first traversal of graph starting at', start, ':') for visit in graph.breadthFirst(start): print('Visiting', graph.getVertex(visit).name) print('End breadth-first traversal') print('Minimuum-spanning tree graph starting at', start, ':') graph.minimumSpanningTree(start).print() print('Checking that bad indices cause exceptions') for j, k in ((0, 0), (-1, 0), (0, graph.nVertices())): try: print('Trying to create an edge from', j, 'to', k) graph.addEdge(j, k) except IndexError as e: print('IndexError was raised') except ValueError as e: print('ValueError was raised') print('All index tests passed')

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