def old_caida():
ROOT = '/home/wangjing/LocalResearch/CyberData/caida-data/'
T = 4.33
dur_set = np.linspace(0.1, T * 0.9, 20)
lk_list = []
for dur in dur_set:
dat = load(ROOT + 'passive-2013-sigs-%f/sigs.pk' % (dur))
sigs, nodes = old_pk_to_coo(dat, True)
print('len sigs', len(sigs))
# model, para, debug_ret = select_model(len(nodes), sigs, min([40, len(sigs)]), 200, True)
model, para, debug_ret = select_model(len(nodes), sigs, len(sigs), 200,
True)
lk_list.append(debug_ret['ER'][2])
print('log likelihood value', debug_ret['ER'][2])
print('para', para)
print('model', model)
dump({
'x': dur_set,
'y': lk_list,
'x_name': 'dur_set',
'y_name': 'lk_list'
}, './caida-backbone-er-different-window-size-large-sample.pk')
P.plot(dur_set, lk_list)
# P.plot(sdd)
P.show()
import ipdb
ipdb.set_trace()
def plotv(name):
dat = load(name)
lk1, lk2, lk3 = release(dat, ['CHJ', 'BA', 'ER'], 2)
P.subplot(211)
P.plot(lk1, 'o--', lw=2, ms=15)
P.plot(lk2, '>g', lw=2, ms=15)
P.plot(lk3, 'xr-', lw=2, ms=15)
P.legend(['CHJ', 'BA', 'ER'], loc=4)
# P.title('log likelihood vs. n for BA(n, %i)' % (m))
P.subplot(212)
p1, p2, p3 = release(dat, ['CHJ', 'BA', 'ER'], 1)
P.plot(p1, 'o--', lw=2, ms=15)
P.plot(p2, '>g', lw=2, ms=15)
P.plot(p3, 'xr-', lw=2, ms=15)
P.legend(['CHJ', 'BA', 'ER'], loc=4)
# P.title('parameters vs. n for BA(n, %i)' % (m))
P.show()
def plotv(name):
dat = load(name)
lk1, lk2, lk3 = release(dat, ['CHJ', 'BA', 'ER'], 2)
P.subplot(211)
P.plot(lk1, 'o--', lw=2, ms=15)
P.plot(lk2, '>g', lw=2, ms=15)
P.plot(lk3, 'xr-', lw=2, ms=15)
P.legend(['CHJ', 'BA', 'ER'], loc=4)
# P.title('log likelihood vs. n for BA(n, %i)' % (m))
P.subplot(212)
p1, p2, p3 = release(dat, ['CHJ', 'BA', 'ER'], 1)
P.plot(p1, 'o--', lw=2, ms=15)
P.plot(p2, '>g', lw=2, ms=15)
P.plot(p3, 'xr-', lw=2, ms=15)
P.legend(['CHJ', 'BA', 'ER'], loc=4)
# P.title('parameters vs. n for BA(n, %i)' % (m))
P.show()
def old_caida():
ROOT = '/home/wangjing/LocalResearch/CyberData/caida-data/'
T = 4.33
dur_set = np.linspace(0.1, T*0.9, 20)
lk_list = []
for dur in dur_set:
dat = load(ROOT+'passive-2013-sigs-%f/sigs.pk' % (dur))
sigs, nodes = old_pk_to_coo(dat, True)
print('len sigs', len(sigs))
# model, para, debug_ret = select_model(len(nodes), sigs, min([40, len(sigs)]), 200, True)
model, para, debug_ret = select_model(len(nodes), sigs, len(sigs), 200, True)
lk_list.append(debug_ret['ER'][2])
print('log likelihood value', debug_ret['ER'][2])
print('para', para)
print('model', model)
dump({'x':dur_set, 'y':lk_list, 'x_name':'dur_set', 'y_name':'lk_list'},
'./caida-backbone-er-different-window-size-large-sample.pk')
P.plot(dur_set, lk_list)
# P.plot(sdd)
P.show()
import ipdb;ipdb.set_trace()