def get_results(rgg, eA, dRange):
G = rgg.generate_graph()
A = Embed.adjacency_matrix(G)
n = G.number_of_nodes()
m = max(int(np.sqrt(n)), 50)
rhoBS = np.array([get_subgraph_density(A, random_integers(0, n - 1, m)) for _ in xrange(1000)])
rhoHat = np.sort(0.5 - np.abs(0.5 - rhoBS))[950]
sval = eA.embed(G).sval
mcr = [mclust(rggk.label, eA.get_scaled(d)) for d in dRange]
return (sval, mcr, rhoHat)
