class TestSearch(unittest.TestCase):
def setUp(self):
self.randG = RandomGraph()
def testBidirectional(self):
for i in range(50):
adjList = self.randG.randomGnmGraph(n=50,
M=1000,
isWeighted=False,
isDirected=False)
src = random.choice(adjList.keys())
dest = random.choice(adjList.keys())
dist1, prev1 = bfs(adjList, src)
dist2, prev2 = bidirectional(adjList, src, dest)
self.assertEqual(dist1[dest], dist2)
def testIterativeDeepening(self):
for i in range(50):
adjList = self.randG.randomGnmGraph(n=50,
M=1000,
isWeighted=False,
isDirected=False)
src = random.choice(adjList.keys())
dest = random.choice(adjList.keys())
dist1, prev1 = bfs(adjList, src)
dist2, prev2 = iterative_deepening(adjList, src, dest)
self.assertEqual(dist1[dest], dist2[dest])
def main(script, n='10', *args):
# create n Vertices
n = int(n)
labels = string.ascii_lowercase + string.ascii_uppercase
vs = [Vertex(c) for c in labels[:n]]
# Create complete graph
# g = Graph(vs)
# g.add_all_edges()
# Create regular graph
# g = Graph(vs)
# g.add_regular_edges(4)
# Create random graph
g = RandomGraph(vs)
g.add_random_edges(0.5)
layout = CircleLayout(g)
# draw the graph
gw = GraphWorld()
gw.show_graph(g, layout)
gw.mainloop()
class TestShortest(unittest.TestCase):
def setUp(self):
self.randG = RandomGraph()
def testUnweighted(self):
for i in range(50):
adjList = self.randG.randomGnmGraph(n=50,
M=1000,
isWeighted=False,
isDirected=False)
src = random.choice(list(adjList.keys()))
dist1, prev1 = bfs(adjList, src)
adjList = self.randG.toWeighted(adjList)
dist3, prev3 = dijkstra(adjList, src)
self.assertEqual(dist1, dist3)
def testWeighted(self):
for i in range(50):
adjList = self.randG.randomGnmGraph(n=50, M=1000, isWeighted=True)
nodes, edges = self.randG.toNodeEdges(adjList)
src = random.choice(list(adjList.keys()))
dist1, prev1 = dijkstra(adjList, src)
dist2, prev2 = bellman_ford(nodes, edges, src)
dist3, prev3 = shortest_path_faster(adjList, src)
self.assertEqual(dist1, dist2)
self.assertEqual(dist2, dist3)
def testFloydWarshall(self):
for i in range(50):
adjList = self.randG.randomGnmGraph(n=50, M=1000, isWeighted=True)
nodes, edges = self.randG.toNodeEdges(adjList)
src = random.choice(list(adjList.keys()))
dist1, prev1 = dijkstra(adjList, src)
dist2, prev2 = floyd_warshall(nodes, edges)
self.assertEqual(dist1, dist2[src])
def testAllPairs(self):
for i in range(50):
adjList = self.randG.randomGnmGraph(n=50, M=1000, isWeighted=True)
nodes, edges = self.randG.toNodeEdges(adjList)
src = random.choice(list(adjList.keys()))
dist1, prev1 = floyd_warshall(nodes, edges)
dist2, prev2 = johnson(nodes, edges)
self.assertEqual(dist1, dist2)
default=50,
type=int,
help="Number of nodes in Erdos-Renyi Graph")
parser.add_argument(
"--p",
default=0.25,
type=float,
help="Probability of edge being present in Erdos-Renyl Graph")
parser.add_argument("--n_iter",
default=1000,
type=int,
help="Number of iterations for simulation to run")
args = parser.parse_args()
if __name__ == "__main__":
randomGraph = RandomGraph(n_nodes=args.nodes, p=args.p)
randomGraph.gen_RandomPartitions()
randomGraph.calculateSpectrum()
randomGraph.showPartitions(args.savefigures)
randomGraph.SwapNodes(getSwapNodes(randomGraph))
fig, [[axis1, axis2], [axis3, axis4]] = plt.subplots(2,
2,
figsize=(16, 16))
history = np.array(randomGraph.history, dtype=np.float)
axis1.plot(history[1:, 1], ":r*", label='Component 0')
axis1.axhline(y=history[0][1],
color='r',
label='Initial value(Component 0)',
linestyle="-")
axis1.plot(history[1:, 2], ":g^", label='Component 1')
def setUp(self):
self.randG = RandomGraph()