def select_caida_backbone(): ROOT = '/home/wangjing/LocalResearch/CyberData/CaidaData/' T = 4.33 dur_set = np.linspace(0.1, T*0.9, 20) tr = dict(alphav=[], lkav=[], betav=[], lkbv=[], dur=[]) for dur in dur_set: print('dur', dur) f_name = ROOT + 'passive-2013-sigs-%f/sigs.pk' % (dur) sigs = load(f_name) s_v = mg_sample(n=min([4, len(sigs['sig_edges'])]), k=200, **sigs) alpha, lka = mle(s_v, 'BA') beta, lkb = mle(s_v, 'ER') tr['dur'].append(dur) tr['alphav'].append(alpha) tr['betav'].append(beta) tr['lkav'].append(lka) tr['lkbv'].append(lkb) dump(tr, './model-select-caida-backbone.pk')
def select_caida_backbone(): ROOT = '/home/wangjing/LocalResearch/CyberData/CaidaData/' T = 4.33 dur_set = np.linspace(0.1, T * 0.9, 20) tr = dict(alphav=[], lkav=[], betav=[], lkbv=[], dur=[]) for dur in dur_set: print('dur', dur) f_name = ROOT + 'passive-2013-sigs-%f/sigs.pk' % (dur) sigs = load(f_name) s_v = mg_sample(n=min([4, len(sigs['sig_edges'])]), k=200, **sigs) alpha, lka = mle(s_v, 'BA') beta, lkb = mle(s_v, 'ER') tr['dur'].append(dur) tr['alphav'].append(alpha) tr['betav'].append(beta) tr['lkav'].append(lka) tr['lkbv'].append(lkb) dump(tr, './model-select-caida-backbone.pk')
def select_simple_pkt(): ROOT = '/home/wangjing/LocalResearch/CyberData/CaidaData/' T = 66095.977196 # msv = [] dur_set = np.linspace(10, T*0.9, 50) tr = dict(alphav=[], lkav=[], betav=[], lkbv=[], dur=[]) for dur in dur_set: print('dur', dur) f_name = ROOT+'sigs1/loc6-%i/sigs.pk' % (dur) sigs = load(f_name) s_v = mg_sample(n=min([4, len(sigs['sig_edges'])]), k=400, **sigs) alpha, lka = mle(s_v, 'BA') beta, lkb = mle(s_v, 'ER') tr['dur'].append(dur) tr['alphav'].append(alpha) tr['betav'].append(beta) tr['lkav'].append(lka) tr['lkbv'].append(lkb) dump(tr, './model-select-simple-pkt.pk')
def select_simple_pkt(): ROOT = '/home/wangjing/LocalResearch/CyberData/CaidaData/' T = 66095.977196 # msv = [] dur_set = np.linspace(10, T * 0.9, 50) tr = dict(alphav=[], lkav=[], betav=[], lkbv=[], dur=[]) for dur in dur_set: print('dur', dur) f_name = ROOT + 'sigs1/loc6-%i/sigs.pk' % (dur) sigs = load(f_name) s_v = mg_sample(n=min([4, len(sigs['sig_edges'])]), k=400, **sigs) alpha, lka = mle(s_v, 'BA') beta, lkb = mle(s_v, 'ER') tr['dur'].append(dur) tr['alphav'].append(alpha) tr['betav'].append(beta) tr['lkav'].append(lka) tr['lkbv'].append(lkb) dump(tr, './model-select-simple-pkt.pk')
from SBDet import * import pylab as P import networkx as nx from subprocess import check_call from SBDet.Util import load, zload def get_ips(data, format_=None): nnx = NetworkXGraph(data=data) if format_ is not None: return [format_(ip) for ip in nnx.get_vertices()] return nnx.get_vertices() ab_ids = range(200, 230) sigs = load('./Result/sigs_nx.pk') adj_mats = [nx.to_scipy_sparse_matrix(sigs[i]) for i in ab_ids] #### Identify the Pivot Nodes ###### tr = load('./Result/GCM_tr.pk') weights = tr['solution'] p_nodes = ident_pivot_nodes(adj_mats, weights, 0.8) #### Calculate interactions of nodes with pivot nodes #### inta = cal_inta_pnodes(adj_mats, tr['solution'], p_nodes) #### Calculate the correlation graph #### A, npcor = cal_cor_graph(adj_mats, p_nodes, 0.2) w2 = 0.01 P0, q0, W = com_det_reg(A, inta, w1=0, w2=w2, lamb=0, out='./prob.sdpb')
#!/usr/bin/env python from __future__ import print_function, division from SBDet import * import pylab as P import networkx as nx from subprocess import check_call from SBDet.Util import load, zload def get_ips(data, format_=None): nnx = NetworkXGraph(data=data) if format_ is not None: return [format_(ip) for ip in nnx.get_vertices()] return nnx.get_vertices() ab_ids = range(200, 230) sigs = load('./Result/sigs_nx.pk') adj_mats = [nx.to_scipy_sparse_matrix(sigs[i]) for i in ab_ids] #### Identify the Pivot Nodes ###### tr = load('./Result/GCM_tr.pk') weights = tr['solution'] p_nodes = ident_pivot_nodes(adj_mats, weights, 0.8) #### Calculate interactions of nodes with pivot nodes #### inta = cal_inta_pnodes(adj_mats, tr['solution'], p_nodes) #### Calculate the correlation graph #### A, npcor = cal_cor_graph(adj_mats, p_nodes, 0.2) w2 = 0.01 P0, q0, W = com_det_reg(A, inta, w1=0, w2=w2, lamb=0, out='./prob.sdpb')