def prim(graph, start_node):
queue = PriorityQueue()
parent = {}
mst = []
mst_sum = 0
for node in graph.get_nodes():
queue.add_task(task=node, priority=float('Inf'))
parent[node] = None
# put first node in the queue
queue.add_task(task=start_node, priority=0)
while queue.not_empty():
cheapest_node = queue.pop_task()
if parent[cheapest_node] is not None:
temp_weight = float(graph.get_default_weights((cheapest_node, parent[cheapest_node]))[0])
mst.append((temp_weight, (cheapest_node, parent[cheapest_node])))
mst_sum += temp_weight
for adj_node in graph.get_node_neighbours(cheapest_node):
edge_weight = float(graph.get_default_weights((cheapest_node, adj_node))[0])
if queue.contains_task(adj_node) and edge_weight < queue.get_priority(adj_node):
parent[adj_node] = cheapest_node
queue.add_task(task=adj_node, priority=edge_weight)
print "Prim Weight: ", mst_sum
return mst
def dijkstra(graph, start, end=None):
nodes = graph.get_nodes()
# initialize distance dictionary
dist = {node: float('Inf') for node in nodes}
dist[start] = 0
# initialize predecessor dictionary
pred = {node: None for node in nodes}
# initialize prio queue for "unvisited nodes
nodes_nonfinal = PriorityQueue()
for node in nodes:
nodes_nonfinal.add_task(task=node, priority=dist[node])
# main computation loop
while nodes_nonfinal.not_empty():
u = nodes_nonfinal.pop_task()
for adj in graph.get_node_neighbours(u):
if nodes_nonfinal.contains_task(adj):
temp = dist[u] + float(graph.get_default_weights((u, adj))[0])
if temp < dist[adj]:
pred[adj] = u
nodes_nonfinal.add_task(task=adj, priority=temp)
# if an end node was specified, the corresponding shortest path shall be
# computed and displayed
if end is not None:
path, path_sum = shortest_path(graph, pred, end)
#print '#' * 50
#print 'Path: ', path
#print 'Weight: ', path_sum
return path
else:
get_shortest_path_tree(graph, pred, start)