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)