def dijkstra(self, start_label, end_label):
start_vertex = self.find_vertex_by_label(start_label)
start_vertex.weight = 0
pq = PriorityQueue()
pq.build_heap(self.vertices)
while not pq.isEmpty():
min_vertex = pq.getMin() # return Vertex object
for neighbour_vertex in self.adjacencyList[min_vertex.label]:
tmp_vertex = self.find_vertex_by_label(
neighbour_vertex.label) # vertex object from self.vertices
if min_vertex.weight + neighbour_vertex.weight < tmp_vertex.weight:
tmp_vertex.parent = min_vertex.label
tmp_vertex.weight = min_vertex.weight + neighbour_vertex.weight
pq.deleteMin()
print(self.print_path(end_label))
def prim(G, start):
pq = PriorityQueue()
for v in G:
v.setDistance(sys.maxsize)
v.setPred(None)
start.setDisatance(0)
pq.build_heap([(v.getDistance(), v) for v in G])
while not pq.is_empty():
currentVert = pq.del_min()
for nextVert in currentVert.getConnections():
newCost = currentVert.getWeight(nextVert)
if nextVert in pq and newCost < nextVert.getDistance():
nextVert.setPred(currentVert)
nextVert.setDisatance(newCost)
pq.decrease_key(nextVert, newCost)
def prim(self, start_label):
start_vertex = self.find_vertex_by_label(start_label)
start_vertex.weight = 0
pq = PriorityQueue()
#for vertex in self.vertices:
# pq.insert(vertex)
pq.build_heap(self.vertices)
while not pq.isEmpty():
min_vertex = pq.getMin() # return Vertex object
if min_vertex.parent is not None:
self.path += (min_vertex.parent + " -> " + min_vertex.label +
", ")
for neighbour_vertex in self.adjacencyList[min_vertex.label]:
tmp_vertex = self.find_vertex_by_label(
neighbour_vertex.label) # vertex object from self.vertices
if neighbour_vertex.weight < tmp_vertex.weight:
tmp_vertex.parent = min_vertex.label
tmp_vertex.weight = neighbour_vertex.weight
pq.deleteMin()
print(self.path)
def dijkstra(aGraph, start):
# Actually, it is a priority queue.
pq = PriorityQueue()
start.setDistance(0)
# :meth:`biuld_heap` is O(logV)
pq.build_heap([(v.getDistance(), v) for v in aGraph])
while not pq.is_empty():
# :meth:`del_min()` is O(logV), within the `while` loop, it is O(Vlog(V))
currentVert = pq.del_min()
# The `for` loop is O(E)
for nextVert in currentVert.getConnections():
newDist = currentVert.getDistance() + currentVert.getWeight(
nextVert)
if newDist < nextVert.getDistance():
nextVert.setDistance(newDist)
nextVert.setPred(currentVert)
# :meth:`decrease_key` is within `for` loop, it is O(Elog(V))
pq.decrease_key(nextVert, newDist)