def test_ncp_localmin():
G = load_example_graph()
ncp = lgc.NCPData(G)
func = lgc.partialfunc(lgc.spectral_clustering,alpha=0.01,rho=1.0e-4,method="acl")
ncp.default_method = func
ncp.add_localmin_samples(ratio=1)
print(ncp.as_data_frame())
G = lgc.GraphLocal()
G.list_to_gl([0,1],[1,0],[1,1])
ncp = lgc.NCPData(G)
func = lgc.partialfunc(lgc.spectral_clustering,alpha=0.01,rho=1.0e-4,method="acl")
ncp.default_method = func
ncp.add_localmin_samples(ratio=1)
def test_apr_refine():
G = load_example_graph()
df = lgc.NCPData(G).approxPageRank(ratio=1,
gamma=0.1,
rholist=[1e-2, 1e-3],
random_neighborhoods=False,
localmins=False,
spectral_args={
'refine':
lgc.partialfunc(lgc.flow_clustering,
method="mqi")
})
def test_ncp():
G = load_example_graph()
ncp = lgc.NCPData(G)
df = ncp.as_data_frame()
assert len(df) == 0
ncp.mqi(nthreads=1,ratio=1.0)
df = ncp.as_data_frame()
assert len(df) == G._num_vertices
#func = lambda G,R: lgc.flow_clustering(G,R,method="mqi")[0]
func = lgc.partialfunc(lgc.flow_clustering, method="mqi")
ncp = lgc.NCPData(G)
ncp.add_set_samples([[1]],nthreads=1,method=func,methodname="mqi")
ncp.add_random_neighborhood_samples(ratio=2,nthreads=1,method=func,methodname="mqi")