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