def testGetYaoGraph(self):
# prosty test na stwierdzenie czy macierz wyglada tak jak trzeba
n = 200
k = 8
matrix = getYaoGraph(n, k)
for row in matrix:
print row
for row in matrix:
self.failIf(all([el == 0 for el in row]))
# drugi test - sprawdzamy czy wszystkie wierzcholki sa dostepne
reachable = [0]
# teraz dla kazdego obiektu z listy patrzymy na wezly z nim sasiadujace
for v in reachable:
neighbors = [i for i in matrix[v]]
neighbors = [i for i in range(n) if (neighbors[i] > 0)]
neighbors = [i for i in neighbors if (i not in reachable)]
reachable.extend(neighbors)
# sprawdzenie czego brakuje:
# jesli wszystkie wezly sa osiagalne
print reachable
self.failUnless(len(reachable) == n)
def testGetYaoGraph(self):
# test algorytmu log star MIS dla grafu Yao
n = 200
k = 10
matrix = getYaoGraph(n, k)
# tworzenie sieci
network = Network(matrix)
alg = LogStar(network)
nodes = network.ndList
for node in nodes:
alg.initiateNode(node)
alg.execute()
# sprawdzanie faili
for node in nodes:
# sprawdzanie mozliwosci faila #1
neighIndices = node.neighbors
if node.memory['state'] == 'dominator':
for neighIndex in neighIndices:
self.failIf(nodes[neighIndex].memory['state'] == 'dominator')
elif node.memory['state'] == 'dominated':
dominatedList = [nodes[n].memory['state'] == 'dominated' for n in neighIndices]
self.failIf(all(dominatedList))
else:
self.fail(''.join(['incorrect state after algorithm execution:', node.memory['state']]))
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 = getYaoGraph(n, 8)
network = Network(adjMatrix)
alg = LogStar(network)
for node in network.ndList:
alg.initiateNode(node)
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/log_star_MIS_yao_graph_comm.txt'
save(commTimes, fileName)
fileName = '/home/julka/100_reps/log_star_MIS_yao_graph_alg.txt'
save(algTimes, fileName)
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.log_star_MIS import LogStar
from network.network import Network
from graph_tool.all import *
from graph_generators.n_yao_graph import getYaoGraph
adjacencyMatrix = getYaoGraph(15, 6)
# tworzenie sieci
network = Network(adjacencyMatrix)
alg = LogStar()
network.algorithm = alg
alg.network = network
nodes = network.ndList
for node in nodes:
alg.initiateNode(node)
network.executeAlgorithm()
# 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
