def testGetPlanarGraph(self):
n = 200
matrix = getPlanarGraph(n)
# for row in matrix:
# print row
# 1 - sprawdzanie czy wszystkie punkty sa osiagalne
reachable = [0]
# teraz dla kazdego obiektu z listy patrzymy na wezly z nim sasiadujace
for v in reachable:
row = matrix[v]
neigh = [i for i in range(n) if (row[i] > 0) and (i not in reachable)]
# print 'neigh:'
# print neigh
reachable.extend(neigh)
# print reachable
# sprawdzenie czego brakuje:
# jesli wszystkie wezly sa osiagalne
# print 'pod koniec testu'
# print reachable
self.failUnless(len(reachable) == n)
def test_execute(self):
n = 50
adjacencyMatrix = getPlanarGraph(n)
network = Network(adjacencyMatrix)
# sprawdzenie metody
alg = PlanarMIS(network)
alg.execute()
# sprawdzanie:
# standardowo jak w MIS
for node in network.ndList:
if node.memory['is_in_final_MIS'] == True:
for neigh in node.neighbors:
self.failIf(network.ndList[neigh].memory['is_in_final_MIS'] == True)
# jesli wezel jest zdominowany, to fail jesli ma w swoim otoczeniu same zdominowane wezly
elif node.memory['is_in_final_MIS'] == False:
neigh_states = [network.ndList[neigh].memory['is_in_final_MIS'] for neigh in node.neighbors]
self.failIf(all([state == False for state in neigh_states]))
# jesli wezel nie jest ani dominatorem ani zdominownay, to fail
else:
self.fail("nieprawidlowy stan wezla")
def test_executeWithoutJoiningSubgraphs(self):
n = 10
adjacencyMatrix = getPlanarGraph(n)
network = Network(adjacencyMatrix)
# sprawdzenie metody
alg = PlanarMIS(network)
alg._executeWithoutJoiningSubgraphs()
# sprawdzanie:
# po kolei dla kazdego poddrzewa
# poddrzew bedzie mniej niz n/2
for i in range(n/2):
for node in network.ndList:
# fail jesli wezel nie ma nadal przydzielonego poddrzewa
self.failIf(not node.memory.has_key('tree_num'))
# wybieranie tylko wezlow z podgrafu nr i
if node.memory['tree_num'] != i:
continue
# fail jesli sasiedzi wezla sa z innego poddrzewa
neighbors = node.memory['neighbors_cp']
for neigh in neighbors:
sub = network.ndList[neigh].memory['tree_num']
if sub != i:
print 'wezel: ', node.ID, 'sasiad:', neigh
self.drawGraph(network.ndList, adjacencyMatrix)
self.fail('podgraf mial byc nr ' + str(i)+ ' a jest '+ str(sub))
# self.failIf(sub != i)
# jesli wezel jest dominatorem, to fail jesli jego sasiad tez jest
if node.memory['state_subgraph'] == 'dominator':
for neigh in neighbors:
self.failIf(network.ndList[neigh].memory['state_subgraph'] == 'dominator')
# jesli wezel jest zdominowany, to fail jesli ma w swoim otoczeniu same zdominowane wezly
elif node.memory['state_subgraph'] == 'dominated':
neigh_states = [network.ndList[neigh].memory['state_subgraph'] for neigh in neighbors]
self.failIf(all([state == 'dominated' for state in neigh_states]))
# jesli wezel nie jest ani dominatorem ani zdominownay, to fail
else:
self.fail("nieprawidlowy stan wezla:", node.memory['state_subgraph'])
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 = FastMIS_v2(network)
alg.execute()
print k
tempAlgSum += alg.roundCounter
tempCommSum += network.algCommRoundCounter
print n, 'time: ', datetime.now()
algTimes.append(tempAlgSum/float(repetitions))
commTimes.append(tempCommSum/float(repetitions))
# print times
fileName = '/home/julka/100_reps/fast_MIS_v2_planar_graph_comm.txt'
save(commTimes, fileName)
fileName = '/home/julka/100_reps/fast_MIS_v2_planar_graph_alg.txt'
save(algTimes, fileName)
def test_divideIntoSubgraphsv2(self):
# 1 - tworzenie macierzy
adjacencyMatrix = getPlanarGraph(10)
network = Network(adjacencyMatrix)
# sprawdzenie metody
alg = PlanarMIS(network)
alg.divideIntoSubgraphs()
# wezly z podgrafu i musza miec jako sasiadow tylko inne wezly z podgrafu i - albo zadnych
for node in network.ndList:
if node.memory.has_key('tree_num'):
i = node.memory['tree_num']
neigh_cp = node.memory['neighbors_cp']
for neigh in neigh_cp:
if not network.ndList[neigh].memory.has_key('tree_num'):
self.fail("sasiad nie jest w tym zadnym podgrafie")
else:
self.failIf(network.ndList[neigh].memory['tree_num'] != i)
else:
# wszystkie wezly musza byc w jakims podgrafie
self.fail("sasiad nie jest w zadnym podgrafie")
# sprawdzanie ilosci sasiadow
for node in network.ndList:
neigh_len = len(node.memory['neighbors_cp'])
self.failIf(neigh_len > 6)
# wypisywanie pogrfaow
for i in range(7):
print 'wezly z podgrafu', i, ':'
for node in network.ndList:
if node.memory['tree_num'] == i:
print node.ID,
print ' '
def test_execute(self):
adjacencyMatrix = getUnitDiskGraph(200)
network = Network(adjacencyMatrix)
alg = FastMIS_v2(network)
alg.execute()
# self.drawGraph(network.ndList, adjacencyMatrix)
# sprawdzenie wlasnosci wyliczonego MIS
self.checkIfMISisCorrect(network.ndList)
#
# graf Yao
adjacencyMatrix = getYaoGraph(15, 6)
network = Network(adjacencyMatrix)
alg = FastMIS_v2(network)
alg.execute()
# self.drawGraph(network.ndList, adjacencyMatrix)
# sprawdzenie wlasnosci wyliczonego MIS
self.checkIfMISisCorrect(network.ndList)
# graf planarny
adjacencyMatrix = getPlanarGraph(10)
network = Network(adjacencyMatrix)
alg = FastMIS_v2(network)
alg.execute()
# self.drawGraph(network.ndList, adjacencyMatrix)
# sprawdzenie wlasnosci wyliczonego MIS
self.checkIfMISisCorrect(network.ndList)
from algorithm.MIS_for_planar_graphs import PlanarMIS
from network.network import Network
from graph_generators.n_planar_graph import getPlanarGraph
from graph_tool.all import *
adjacencyMatrix = getPlanarGraph(70)
# tworzenie sieci
network = Network(adjacencyMatrix)
alg = PlanarMIS()
network.algorithm = alg
alg.network = network
nodes = network.ndList
alg.divideIntoSubgraphs()
# czesc rysujaca
g = Graph(directed=False)
# dodawanie wezlow - indeksowanie bedzie sie zgadzalo
for node in nodes:
g.add_vertex()
# dodawanie krawedzi - tu trzeba isc po macierzy incydencji
# i - wiersze macierzy
# j - kolumny macierzy
