def testCommunity_leading_eigenvector(self):
alg = community_leading_eigenvector()
print(sys._getframe().f_code.co_name)
print (alg.run(self.graph_unweighted_undirect).get_result())
print (clustering.load_result(self.graph_unweighted_undirect.name, alg.name))
alg = community_leading_eigenvector()
print (alg.run(self.graph_weighted_undirect).get_result())
print (clustering.load_result(self.graph_unweighted_undirect.name, alg.name))
def test_community_multilevel(self):
alg = community_multilevel()
print(sys._getframe().f_code.co_name)
print (alg.run(self.graph_unweighted_undirect).get_result())
print (clustering.load_result(self.graph_unweighted_undirect.name, alg.name))
alg = community_multilevel()
print (alg.run(self.graph_weighted_undirect).get_result())
print (clustering.load_result(self.graph_unweighted_undirect.name, alg.name))
def testMCL(self):
alg = MCL()
print("testMCL")
print(alg.run(self.graph_unweighted_undirect, I=2).get_result())
print(
clustering.load_result(self.graph_unweighted_undirect.name,
alg.name))
def test_dlplm(self):
alg = dlslm()
for data in self.graphs:
alg = dlplm()
print(sys._getframe().f_code.co_name)
print(alg.run(data).get_result())
print(clustering.load_result(data.name, alg.name))
def testCGGC(self):
alg = CGGC()
print("testCGGC")
print(alg.run(self.graph_unweighted_undirect).get_result())
print(
clustering.load_result(self.graph_unweighted_undirect.name,
alg.name))
def testBug6(self):
alg = 'oslom_Infohiermap'
dataname = 'EVAL2_LFR_ud_wu_N1024_mu0.3'
clu = clustering.load_result(dataname, alg)
data = dataset.load_local(dataname)
a = calc_clu_metrics(data, clu)
print(a)
self.assertTrue(not np.isnan(a['cluster_clustering_coefficient']))
def testBug5(self):
alg = 'cdc_MSCD_LFK2'
dataname = 'EVAL2_LFR_ud_wu_N1024_mu0.3'
clu = clustering.load_result(dataname, alg)
data = dataset.load_local(dataname)
calc_clu_metrics(data, clu)
gt = list(data.get_ground_truth().values())[0]
a = calc_clu_gt_attrib(gt, clu)
print(a)
def test_copra(self):
print(sys._getframe().f_code.co_name)
alg = copra()
print (alg.run(self.graph_weighted_direct).get_result())
print (clustering.load_result(self.graph_weighted_direct.name, alg.name))
alg = copra()
print (alg.run(self.graph_unweighted_direct).get_result())
print (clustering.load_result(self.graph_unweighted_direct.name, alg.name))
alg = copra()
print (alg.run(self.graph_unweighted_undirect).get_result())
print (clustering.load_result(self.graph_unweighted_undirect.name, alg.name))
alg = copra()
print (alg.run(self.graph_weighted_undirect).get_result())
print (clustering.load_result(self.graph_weighted_undirect.name, alg.name))
def test_oslom_with_louvain(self):
print(sys._getframe().f_code.co_name)
alg = OSLOM()
print (alg.run(self.graph_weighted_direct, fast=True, louvain=True).get_result())
print (clustering.load_result(self.graph_weighted_direct.name, alg.name))
alg = OSLOM()
print (alg.run(self.graph_unweighted_direct, fast=True, louvain=True).get_result())
print (clustering.load_result(self.graph_unweighted_direct.name, alg.name))
alg = OSLOM()
print (alg.run(self.graph_unweighted_undirect, fast=True, louvain=True).get_result())
print (clustering.load_result(self.graph_unweighted_undirect.name, alg.name))
alg = OSLOM()
print (alg.run(self.graph_weighted_undirect, fast=True, louvain=True).get_result())
print (clustering.load_result(self.graph_weighted_undirect.name, alg.name))
def testScanpp(self):
for data in self.graphs:
alg = Scanpp()
print(sys._getframe().f_code.co_name)
if data.is_weighted():
with self.assertRaises(Exception) as context:
print(alg.run(data).get_result())
else:
print(alg.run(data).get_result())
print(clustering.load_result(data.name, alg.name))
def testGirvan_Newman(self):
for data in self.graphs:
alg = Girvan_Newman()
print(sys._getframe().f_code.co_name, data.name)
if data.is_directed():
with self.assertRaises(UnsupportedException) as context:
print(alg.run(data).get_result())
else:
print(alg.run(data).get_result())
print(clustering.load_result(data.name, alg.name))
def testSCD(self):
for data in self.graphs:
if data.is_directed():
continue
try:
alg = SCD()
print(sys._getframe().f_code.co_name, data.name)
print(alg.run(data).get_result())
print(clustering.load_result(data.name, alg.name))
except:
traceback.print_exc()
def testPPScanSSE(self):
alg = pScan()
print(sys._getframe().f_code.co_name)
print(
alg.run(self.graph_unweighted_undirect,
mu=3,
epsilon=0.5,
prog='ppScanSSE').get_result())
print(
clustering.load_result(self.graph_unweighted_undirect.name,
alg.name))
def testCommunity_fastgreedy(self):
for data in self.graphs:
print("Testing", sys._getframe().f_code.co_name, data.name)
if data.is_directed():
with self.assertRaises(UnsupportedException):
alg = community_fastgreedy()
print (alg.run(data).get_result())
else:
alg = community_fastgreedy()
print (alg.run(data).get_result())
print (clustering.load_result(self.graph_unweighted_undirect.name, alg.name))
def testBug4(self):
alg = 'scan_pScan'
dataname = 'SIMPLE_ud_wu_nc128_cz8_in7_it4'
clu = clustering.load_result(dataname, alg)
data = dataset.load_local(dataname)
gt = list(data.get_ground_truth().values())[0]
a = calc_clu_metrics(data, gt)
print(a)
a = calc_clu_metrics(data, clu)
print(a)
a = calc_clu_gt_attrib(gt, clu)
print(a)
def testAnyScan(self):
alg = _AnyScan()
for i in range(1, 5):
print(sys._getframe().f_code.co_name, i)
print(
alg.run(self.graph_unweighted_undirect,
algorithm=i,
minpts=3,
epsilon=0.5).get_result())
print(
clustering.load_result(self.graph_unweighted_undirect.name,
alg.name))
def testPScan(self):
for data in self.graphs:
alg = pScan()
print("Testing", sys._getframe().f_code.co_name, data.name)
print(
alg.run(self.graph_unweighted_undirect,
mu=3,
epsilon=0.5,
prog='pScan').get_result())
print(
clustering.load_result(self.graph_unweighted_undirect.name,
alg.name))
def testPScan2(self):
name = sys._getframe().f_code.co_name
data = random_dataset.generate_undirected_unweighted_random_graph_LFR(name=name, \
N=128, k=16, maxk=32, mu=0.2, minc=32)
alg = pScan()
print("Testing", name, data.name)
print(
alg.run(self.graph_unweighted_undirect,
mu=3,
epsilon=0.5,
prog='pScan').get_result())
print(
clustering.load_result(self.graph_unweighted_undirect.name,
alg.name))
def test_label_propagation(self):
for data in self.graphs:
alg = pg_label_propagation()
print(sys._getframe().f_code.co_name)
print (alg.run(data,execution='sync',ncpus=4).get_result())
print (clustering.load_result(data.name, alg.name))
def make_cluter_if_not_exists():
alg = CGGC()
if not clustering.has_result(g.name, alg.name):
alg.run(g).get_result()
return clustering.load_result(g.name, alg.name)
def testLPDegreeOrdered(self):
for data in self.graphs:
alg = LPDegreeOrdered()
print(sys._getframe().f_code.co_name)
print(alg.run(data).get_result())
print(clustering.load_result(data.name, alg.name))
def testCutClustering(self):
for data in self.graphs:
alg = CutClustering()
print(sys._getframe().f_code.co_name)
print(alg.run(data, alpha=0.15).get_result())
print(clustering.load_result(data.name, alg.name))
def test_GANXiSw(self):
for data in self.graphs:
alg = GANXiSw()
print(sys._getframe().f_code.co_name)
print(alg.run(data).get_result())
print(clustering.load_result(data.name, alg.name))
def testLSOCluster_pmod(self):
for data in self.graphs:
alg = lso_cluster()
print(sys._getframe().f_code.co_name)
print(alg.run(data, loss='pmod', pmod=3).get_result())
print(clustering.load_result(data.name, alg.name))
def testBug2(self):
alg = 'cdc_MSCD_LFK2'
dataname = 'EVAL2_LFR_ud_wu_N1024_mu0.3'
clu = clustering.load_result(dataname, alg)
data = dataset.load_local(dataname)
calc_clu_metrics(data, clu)
def testBug3(self):
alg = 'karateclub_SCD'
dataname = 'EVAL2_LFR_ud_wu_N1024_mu0.3'
clu = clustering.load_result(dataname, alg)
data = dataset.load_local(dataname)
calc_clu_metrics(data, clu)