def createRandomGraph(v,e):
randAdjList = [] # Keep track of edges alredy called. Should ultimately contain unique set of e edges
i = 0
# Add check for if num edges are possible
max_possible_e = (v*(v-1))/2
if(e>max_possible_e):
raise Exception("Error! Number of edges cannot exceed %d for %d edges" % (max_possible_e,v))
while(i<e):
# Generate a random pair of node ids (can't pick the same node twice)
randNodePair = np.random.choice(range(1,v+1), 2, replace=False).tolist()
randNodePairRev = list(randNodePair)
randNodePairRev.reverse()
# Since undirected graph, check that neither a->b nor b->a has been picked
if randNodePair not in randAdjList and randNodePairRev not in randAdjList:
randAdjList.append(randNodePair)
i+=1
# Create random graph using randAdjList created above
rGraph = Graph()
for i in range(1,v):
rGraph.addNode(i)
rGraph.createGraph(randAdjList)
return rGraph
def MST(graph, format="adjacency list"):
parent = {}
# Add all nodes in graph to list of unvisited nodes
unvisited = graph.getNodeList()
# Maintain weight dictionary. Initialize all node weights to infinity
weight_dict = dict({id, float("inf")} for id in graph.getNodeList())
# Initialize all nodes to not visited
for node in graph.getNodeList():
graph.getNodes()[node].visited = False
# Pick a random node as start node
startNode = int(np.random.choice(list(weight_dict.keys()), 1))
weight_dict[startNode] = 0 # Set weight of start node to 0
parent[startNode] = None # Start node has no parent node
g_nodes = graph.getNodes()
while(len(unvisited) != 0):
curr = getMinEdge(weight_dict, unvisited)
g_nodes[curr].visited = True
unvisited.remove(curr)
for edge in graph.getEdges(curr):
if g_nodes[edge].visited == False:
if weight_dict[curr] + getWeight(graph, curr, edge) < weight_dict[edge]:
weight_dict[edge] = weight_dict[curr] + getWeight(graph, curr, edge)
parent[edge] = curr
# Store edges of MST in adjacency list format
# Useful format for creating a graph out of it in the future
adjList_MST = [[parent[key], key] for key in parent if parent[key] != None]
# Choose return format
# Either graph or adjacency list
if format=="graph":
MinSpanTree = Graph()
MinSpanTree.createGraph(adjList_MST)
g_nodes = graph.getNodes()
for node in MinSpanTree.getNodes().values():
node.location = g_nodes[node.nodeid].location
else:
MinSpanTree = adjList_MST
return MinSpanTree
