def createRandomCompleteWeightedGraph(n: int) -> WeightedGraph:
graph = WeightedGraph()
for i in range(0, n):
graph.addNode(i)
for node in graph.getAllNodes():
for neighbor in graph.getAllNodes():
if node is not neighbor:
weight = random.randint(0, n)
graph.addWeightedEdge(node, neighbor, weight)
return graph
def createLinkedList(n): g = WeightedGraph() for i in range(1, n+1): g.addNode(createLabel(i)) nodes = g.getAllNodes() for i in range(len(nodes)-1): nodes[i].neighbors[nodes[i+1]] = 1 return g
def createLinkedList(n):
graph = WeightedGraph()
for newNode in range(0, n)
graph.addNode(newNode)
nodelist = graph.getAllNodes()
nodelistlength = len(nodelist)
for num in range(nodelistlength-1):
graph.addWeightedEdge(nodelist[num], nodelist[num+1], 1)
return graph
def createRandomCompleteWeightedGraph(n):
g = WeightedGraph()
for i in range(1, n + 1):
g.addNode(createLabel(i))
nodes = g.getAllNodes()
for i in nodes:
x = nodes.index(i)
suggested = nodes[:x] + nodes[x + 1:]
for j in suggested:
randomWeight = randint(1, 15)
g.addDirectedEdge(i, j, randomWeight)
return g
def createRandomCompleteWeightedGraph(n): g = WeightedGraph() for i in range(1,n+1): g.addNode(createLabel(i)) nodes = g.getAllNodes() for i in nodes: x = nodes.index(i) # Make a list including all values but the current suggestedList = nodes[:x]+nodes[x+1:] for j in suggestedList: randomWeight = randint(1, 15) g.addDirectedEdge(i, j, randomWeight) return g
def createRandomCompleteWeightedGraph(n):
graph = WeightedGraph()
lst = []
for num in range(n):
randomNum = random.randint(0, n);
if randomNum not in lst:
lst.append(randomNum)
graph.addNode(num)
nodelist = graph.getAllNodes()
for node in nodelist:
for node2 in range(n):
if node != node2:
randomWeight = random.randint(1, (n*n))
graph.addWeightedEdge(node, node2, randomWeight)
return graph
