def setUp(self):
self.graph_unweighted_undirect = random_dataset.generate_ovp_LFR(
"test_LFR_unw_und",
N=128,
k=16,
maxk=16,
muw=0.1,
minc=32,
beta=1,
a=0)
assert not self.graph_unweighted_undirect.is_directed()
assert not self.graph_unweighted_undirect.is_weighted()
self.graph_weighted_undirect = random_dataset.generate_ovp_LFR(
"test_LFR_w_und",
N=128,
k=16,
maxk=16,
muw=0.1,
minc=32,
beta=1,
weighted=True,
a=0)
assert not self.graph_weighted_undirect.is_directed()
assert self.graph_weighted_undirect.is_weighted()
self.graph_weighted_direct = random_dataset.generate_ovp_LFR(
"test_LFR_w_dir",
N=128,
k=16,
maxk=16,
muw=0.1,
minc=32,
beta=1,
weighted=True,
a=1)
assert self.graph_weighted_direct.is_directed()
assert self.graph_weighted_direct.is_weighted()
self.graph_unweighted_direct = random_dataset.generate_ovp_LFR(
"test_LFR_unw_dir",
N=128,
k=16,
maxk=16,
muw=0.1,
minc=32,
beta=1,
weighted=False,
a=1)
assert self.graph_unweighted_direct.is_directed()
assert not self.graph_unweighted_direct.is_weighted()
self.graphs = [
self.graph_unweighted_undirect, self.graph_weighted_undirect,
self.graph_weighted_direct, self.graph_unweighted_direct
]
def f2(name):
return random_dataset.generate_ovp_LFR("test_LFR_w_und",
N=128,
k=16,
maxk=16,
muw=0.1,
minc=32,
beta=1,
weighted=True,
a=0,
overide=overide)
def f(name):
overide = False
return random_dataset.generate_ovp_LFR(name,
N=128,
k=16,
maxk=16,
muw=0.1,
minc=32,
beta=1,
a=0,
overide=overide)
def testRandomDataset0(self):
ds = random_dataset.generate_ovp_LFR("testRandomDataset0",
N=128,
k=16,
maxk=16,
muw=0.1,
minc=32,
beta=1,
a=0,
overide=True)
print(ds)
def setUp(self):
overide=True
self.graph_unweighted_undirect = random_dataset.generate_ovp_LFR("test_LFR_unw_und_small", N=32, k=4, maxk=4, muw=0.1, minc=4, beta=1, a=0, overide=overide)
assert not self.graph_unweighted_undirect.is_directed()
assert not self.graph_unweighted_undirect.is_weighted()
self.graph_weighted_undirect = random_dataset.generate_ovp_LFR("test_LFR_w_und_small", N=32, k=4, maxk=4, muw=0.1, minc=4, beta=1, weighted=True, a=0, overide=overide)
assert not self.graph_weighted_undirect.is_directed()
assert self.graph_weighted_undirect.is_weighted()
self.graph_weighted_direct = random_dataset.generate_ovp_LFR("test_LFR_w_dir_small", N=32, k=4, maxk=4, muw=0.1, minc=4, beta=1, weighted=True, a=1, overide=overide)
assert self.graph_weighted_direct.is_directed()
assert self.graph_weighted_direct.is_weighted()
self.graph_unweighted_direct = random_dataset.generate_ovp_LFR("test_LFR_unw_dir_small", N=32, k=4, maxk=4, muw=0.1, minc=4, beta=1, weighted=False, a=1, overide=overide)
assert self.graph_unweighted_direct.is_directed()
assert not self.graph_unweighted_direct.is_weighted()
self.graphs = [self.graph_unweighted_undirect, self.graph_weighted_undirect,
self.graph_weighted_direct, self.graph_unweighted_direct]
def setUp(self):
overide = False
def f(name):
overide = False
return random_dataset.generate_ovp_LFR(name,
N=128,
k=16,
maxk=16,
muw=0.1,
minc=32,
beta=1,
a=0,
overide=overide)
name = "test_LFR_unw_und"
self.graph_unweighted_undirect = self.get_dataset(name, f)
assert not self.graph_unweighted_undirect.is_directed()
assert not self.graph_unweighted_undirect.is_weighted()
def f2(name):
return random_dataset.generate_ovp_LFR("test_LFR_w_und",
N=128,
k=16,
maxk=16,
muw=0.1,
minc=32,
beta=1,
weighted=True,
a=0,
overide=overide)
name = "test_LFR_w_und"
self.graph_weighted_undirect = self.get_dataset(name, f)
assert not self.graph_weighted_undirect.is_directed()
assert self.graph_weighted_undirect.is_weighted()
name = "test_LFR_w_dir"
if dataset.local_exists(name):
self.graph_weighted_direct = dataset.load_local(name)
else:
self.graph_weighted_direct = random_dataset.generate_ovp_LFR(
name,
N=128,
k=16,
maxk=16,
muw=0.1,
minc=32,
beta=1,
weighted=True,
a=1,
overide=overide)
assert self.graph_weighted_direct.is_directed()
assert self.graph_weighted_direct.is_weighted()
name = "test_LFR_unw_dir"
if dataset.local_exists(name):
self.graph_unweighted_direct = dataset.load_local(name)
else:
self.graph_unweighted_direct = random_dataset.generate_ovp_LFR(
name,
N=128,
k=16,
maxk=16,
muw=0.1,
minc=32,
beta=1,
weighted=False,
a=1,
overide=overide)
assert self.graph_unweighted_direct.is_directed()
assert not self.graph_unweighted_direct.is_weighted()
self.graphs = [
self.graph_unweighted_undirect, self.graph_weighted_undirect,
self.graph_weighted_direct, self.graph_unweighted_direct
]