for w,v in vLst:
indegree[v] = indegree[v]+1
sortedVertices = []
#add all vertices with indegree 0 to the stack
stack = [i for i in range(N) if indegree[i]==0]
while stack:
u = stack.pop()
sortedVertices.append(u)
for w,v in g.adjLst[u]:
indegree[v] = indegree[v]-1
LPT[v] = max(LPT[v], LPT[u]+w)
if indegree[v] == 0:
stack.append(v)
if len(sortedVertices) == N:
return sortedVertices, LPT
print 'Contains Cycle'
return False
N = 6
g = weightedGraph(N)
g.addEdge(0,2,3)
g.addEdge(0,1,5)
g.addEdge(1,3,6)
g.addEdge(2,3,7)
g.addEdge(2,5,2)
g.addEdge(3,4,-1)
g.addEdge(3,5,1)
g.addEdge(2,4,4)
g.addEdge(4,5,-2)
print topologicalSort(g)
from graph import weightedGraph
import heapq
def djikstra(a,S):
N = len(a.adjLst)
Visited = [False for i in xrange(N)]
Distance = [float('inf') for i in xrange(N)]
Distance[S] = 0
heap = []
heapq.heappush(heap,(0,S))
for i in xrange(N):
if heap:
while(True):
_,u = heapq.heappop(heap)
if not Visited[u]:
break
Visited[u] = True
for weight_uv,v in a.adjLst[u]:
if not Visited[v]:
if Distance[v] > Distance[u] + weight_uv:
Distance[v] = Distance[u] + weight_uv
heapq.heappush(heap, (Distance[v],v))
print Distance
return Distance
g = weightedGraph(4)
g.addEdge(0,1,1)
g.addEdge(1,2,2)
g.addEdge(2,3,3)
g.addEdge(3,0,4)
djikstra(g,0)
