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 ]