def test_execute(self):
adjacencyMatrix = getUnitDiskGraph(200)
network = Network(adjacencyMatrix)
alg = SlowMIS()
alg.network = network
alg.execute()
# sprawdzenie wlasnosci wyliczonego MIS
for node in network.ndList:
# stany wszystkich sasiadow
states = [network.ndList[neigh].memory["state"] for neigh in node.neighbors]
if node.memory["state"] == "not_in_MIS":
# fail jesli wszystkie wezly tez nie sa w MIS
self.failIf(all([state == "not_in_MIS" for state in states]))
elif node.memory["state"] == "in_MIS":
self.failIf(any([state == "in_MIS" for state in states]))
else:
self.fail("nieprawidlowy stan")
def compute():
MIN = 50
MAX =5000
step = 500
repetitions = 100
adjMatrix = []
alg = None
network = None
tempCommSum = 0
commTimes = []
tempAlgSum = 0
algTimes = []
for n in range(MIN, MAX, step):
tempCommSum = 0
tempAlgSum = 0
for k in range(repetitions):
adjMatrix = getPlanarGraph(n)
network = Network(adjMatrix)
alg = SlowMIS(network)
alg.execute()
print k
tempCommSum += network.algCommRoundCounter
tempAlgSum += alg.roundCounter
print n, 'time: ', datetime.now()
commTimes.append(tempCommSum/float(repetitions))
algTimes.append(tempAlgSum/float(repetitions))
# print times
fileName = '/home/julka/100_reps/slow_MIS_planar_graph_comm.txt'
save(commTimes, fileName)
fileName = '/home/julka/100_reps/slow_MIS_planar_graph_alg.txt'
save(algTimes, fileName)