Replication of SWIR model in ER networks

Install graph-tool in linux with Anaconda using this tutorial: https://medium.com/@ronie/installing-graph-tool-for-python-3-on-anaconda-3f76d9004979

• nodes: 1M -> N
• samples: 3k -> n
• name: "results/{0}_{1}_rho_sub_critical.p".format(n,N)

max_new = 0.115+0.003
min_new = 0.115-0.003
kappa_range = (kappa_range-kappa_range.min()) * (max_new - min_new) / 2 + min_new

• nodes: 1M -> N
• samples: 3k -> n
• name: "results/{0}_{1}_rho_critical.p".format(n,N)

max_new = 0.108021+0.003
min_new = 0.108021-0.003
kappa_range = (kappa_range-kappa_range.min()) * (max_new - min_new) / 2 + min_new

• nodes: 50k -> N
• samples: 20k -> n
• name: "results/{0}_{1}_rho_critical.p".format(n,N)

max_new = 0.108021+0.003
min_new = 0.108021-0.003
kappa_range = (kappa_range-kappa_range.min()) * (max_new - min_new) / 2 + min_new

• samples: 6k -> n
• name: "results/{0}_fig7_rho_sub_critical.p".format(n) N_range = [int(n) for n in np.geomspace(1e5, 3e6, 10)]

• samples: 65k -> n
• name: "results/{0}_fig7_rho_sub_critical.p".format(n) N_range = [ 100000, 145923, 212936, 310723]

• samples: 32k -> n
• name: "results/{0}_fig10_rho_critical.p".format(n) N_range = [ 100000, 145923, 212936, 310723]

• samples: 1000 -> n (for each N)
• nodes: 100000, 145923, 212936, 310723 -> N
• name: './results/{0}_{0}_fig10_rho_critical.p'.format(num_ensamble, N)