def main(): A, _X_obs, _z_obs = utils.load_npz('data/cora_ml.npz') A = A + A.T A[A > 1] = 1 scores, tg_sum = fit(A) sampled_graph = gen(scores, tg_sum) print(sampled_graph) np.savetxt('wew2.dat', sampled_graph, fmt='%d')
num_disc_iters = sys.argv[1] walk_type = sys.argv[2] wstate = sys.argv[3] netgan_seed = str(netgan_seed) params = [netgan_seed, num_disc_iters, walk_type, wstate] with open('netgan/plots/netgan_params.txt', 'w') as f: for item in params: f.write("%s\n" % item) f.close() num_disc_iters = int(num_disc_iters) wstate = int(wstate) netgan_seed = int(netgan_seed) _A_obs, _X_obs, _z_obs = utils.load_npz('data/cora_ml.npz') _A_obs = _A_obs + _A_obs.T _A_obs[_A_obs > 1] = 1 lcc = utils.largest_connected_components(_A_obs) _A_obs = _A_obs[lcc, :][:, lcc] _N = _A_obs.shape[0] A = _A_obs.todense() # clusters = [] # G = nx.Graph() # for i in range(5): # H = nx.gnp_random_graph(20,.7) # H = nx.relabel_nodes(H,dict(zip(range(20),range(i*20,(i+1)*20)))) # G = nx.union(H,G) # print(G.nodes()) #0-19