def DFS(self, g: Graph):
for u in g.vertices():
self._unexploredV.append(u)
for u in g.edges():
self._unexploredE.append(u)
print("Unexplored edge:")
for i in self._unexploredE:
print(i)
print("Unexplored vertex")
for i in self._unexploredV:
print(i)
for u in self._unexploredV:
self._DFS(g, u)
def kruskal(g: Graph):
q = HeapPriorityQueue()
clusters = []
T = []
for v in g.vertices():
clusters.append([v])
v.pos = len(clusters) - 1
for e in g.edges():
q.add(e._element, e)
while len(T) < g.num_vertices() - 1:
(w, e) = q.remove_min()
v1 = g.end_vertices(e)[0]
v2 = g.end_vertices(e)[1]
A = clusters[v1.pos]
B = clusters[v2.pos]
if A != B:
_merege(A, B)
T.append(e)
return T
def kruskal(g: Graph):
q = HeapPriorityQueue()
T = [] #Holder listen af edges med minimal vægt
trees = {}
union = unionFind()
for v in g.vertices():
trees[v] = union.makeset(v)
for e in g.edges():
q.add(e._element, e)
while len(T) < g.num_vertices() - 1:
(u, e) = q.remove_min()
v1 = g.end_vertices(e)[0]
v2 = g.end_vertices(e)[1]
leaderv1 = union.quickFind(trees[v1])
leaderv2 = union.quickFind(trees[v2])
if leaderv1._element != leaderv2._element:
union.quickUnion(leaderv1, leaderv2)
T.append(e)
return T