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")