path.append(p)
v = p
path.reverse()
return path
if __name__ == "__main__":
import graph_utils
def report_results(G, s, bf):
for v in range(G.V()):
sp = ' -> '.join([str(x) for x in bf.path_to(v)])
print "%d to %d (%.2f) %s" % (s, v, bf.path_length(v), sp)
source = 0
bf = BellmanFordShortestPath()
# test graph with negative edges
G = graph_utils.load_weighted_digraph('../data/tinyEWDNeg.txt', True)
bf.shortest_path(G, source)
report_results(G, source, bf)
# test graph with negative cycle
try:
G = graph_utils.load_weighted_digraph('../data/tinyEWDNegCyc.txt', True)
bf.shortest_path(G, source)
except AssertionError:
print 'Negative cycle exists'
def distance_to(self, v):
return self.distances[v]
def path_to(self, v):
path = []
p = v
while p is not None:
path.insert(0, p)
p = self.parentChain[p]
return path
if __name__ == "__main__":
import graph_utils
dag = graph_utils.load_weighted_digraph('../data/tinyEWDAG.txt', True)
dag_sp = DAGShortestPath(dag)
source = 5
dag_sp.shortest_path(source)
for i in range(dag.V()):
print "%d to %d (%f): " % (source, i, dag_sp.distance_to(i)), dag_sp.path_to(i)
dag_sp.longest_path(source)
for i in range(dag.V()):
print "%d to %d (%f): " % (source, i, dag_sp.distance_to(i)), dag_sp.path_to(i)
self.weights[i][j] = through_k
def shortest_shortest(self):
shortest_path = 1e100
for v in self.weights.values():
shortest_path = min(min(v), shortest_path)
return shortest_path
def has_negative_cycle(self):
for k in range(self.num_vertices):
if self.weights[k][k] < 0:
return True
return False
if __name__ == "__main__":
import graph_utils
G = graph_utils.load_weighted_digraph('../data/floy-warshall-negative_cycle.txt')
fw = FloydWarshall(G)
fw.all_shortest_paths()
assert fw.has_negative_cycle()
G = graph_utils.load_weighted_digraph('../data/floyd-warshall-1000.txt')
fw = FloydWarshall(G)
fw.all_shortest_paths()
assert not fw.has_negative_cycle()
print(fw.shortest_shortest())
