def filter(g,
traceroutes,
filters=['sh', 'loop', 'ex', 'vf', 'lp'],
first_edge=True):
logger.info('Traceroutes: %d', len(traceroutes))
# remove empty traces
traceroutes = [x for x in traceroutes if len(x) > 0]
logger.info('Non empty traceroutes: %d', (len(traceroutes)))
traceroutes = [x for x in traceroutes if len(x) > 1]
logger.info('Larger than one hop traceroutes: %d', (len(traceroutes)))
# remove traces with unknown nodes
traceroutes, _ = vft.trace_clean(g, traceroutes)
logger.info('Ignored: %d', _)
traceroutes = vft.trace_in_vertex_id(g, traceroutes)
logger.info('Trace count: %d', len(traceroutes))
progress = progressbar1.AnimatedProgressBar(end=len(traceroutes), width=15)
good_traceroutes = traceroutes[:]
if 'sh' in filters:
logger.debug('Remove short traces')
good_traceroutes = [x for x in good_traceroutes if len(x) >= 3]
logger.debug('Remained: %d', len(good_traceroutes))
if 'loop' in filters:
logger.debug('Remove traces with loops')
good_traceroutes = [
x for x in good_traceroutes if len(set(x)) == len(x)
]
logger.debug('Remained: %d' % len(good_traceroutes))
if 'ex' in filters:
logger.debug('Remove non existent traces')
good_traceroutes = [
x for x in good_traceroutes if vft.trace_exists(g, x)
]
logger.debug('Remained: %d', len(good_traceroutes))
if 'vf' in filters:
logger.debug('Remove non vf traces')
good_traceroutes = [
x for x in good_traceroutes if vft.is_valley_free(g, x)
]
logger.debug('Remained: %d' % len(good_traceroutes))
if 'lp' in filters:
logger.debug('Remove non lp traces')
good_traceroutes = [
x for x in good_traceroutes
if vft.is_local_preferenced(g, x, first_edge=first_edge)
]
logger.debug('Remained: %d' % len(good_traceroutes))
# convert back node ids to node names
good_traceroutes = [[g.vs[id]["name"] for id in trace]
for trace in good_traceroutes]
logger.debug(len(good_traceroutes))
return good_traceroutes
def vf_attributes(g, trace, vfmode, get_lp_soft, get_lp_hard, vf_g=None):
is_vf = int(vft.is_valley_free(g, trace, vfmode))
is_lp_soft = -1
is_lp_hard = -1
if is_vf:
if get_lp_soft:
lp_soft = vft.is_local_preferenced(g, trace,
vf_g=vf_g,
first_edge=True,
vfmode=vfmode)
is_lp_soft = int(lp_soft)
else:
is_lp_prelabeled_soft = -1
if get_lp_hard:
lp_hard = vft.is_local_preferenced(g, trace,
vf_g=vf_g,
first_edge=False,
vfmode=vfmode)
is_lp_hard = int(lp_hard)
else:
is_lp_hard = -1
return (is_vf, is_lp_soft, is_lp_hard)
def ba_generator(ba_graph, sh_paths, stretch, vf_g, progressbar=False):
vf_count = 0
trace_count = 0
lp_count = 0
progress = progressbar1.DummyProgressBar(end=10, width=15)
if progressbar:
progress = progressbar1.AnimatedProgressBar(end=len(sh_paths),
width=15)
for (s, t), shl in sh_paths:
progress += 1
progress.show_progress()
logger.debug('SH from %s to %s is %d' % (s, t, shl))
random_route = helpers.random_route_walk(ba_graph, s, t, shl + stretch)
logger.debug('Random route: %s' % random_route)
real_stretch = len(random_route) - shl
if real_stretch != stretch:
continue
trace_count += 1
is_vf = vft.is_valley_free(ba_graph,
random_route,
vfmode=vft.CLOSENESS)
logger.debug(
'Trace edge dir: %s' %
vft.trace_to_string(ba_graph, random_route, vfmode=vft.CLOSENESS))
logger.debug('Is VF: %s' % is_vf)
if is_vf:
is_lp = vft.is_local_preferenced(ba_graph,
random_route,
first_edge=True,
vfmode=vft.CLOSENESS,
vf_g=vf_g)
else:
is_lp = 0
logger.debug('Is LP: %s' % is_lp)
vf_count += int(is_vf)
lp_count += int(is_lp)
logger.info('Stretch %d' % stretch)
logger.info('Trace count: %d' % trace_count)
logger.info('VF count: %d' % vf_count)
logger.info('LP count: %d' % lp_count)
return (stretch, trace_count, vf_count, lp_count)
def purify(g,
meta_original,
out,
count=1000,
try_per_race=1,
show_progress=False,
with_lp=True):
empty = 0
# remove traces with already calculated random paths
logger.warn('[r]ONLY NOT FILLED PATHS[/]')
meta_filled = [
x for x in meta_original if helpers.RANDOM_WALK_RUN_COUNT not in x
]
# Filter if interested only in routes of stretch 1
# meta_filled = [x for x in meta_original
# if x[helpers.TRACE_LEN]-x[helpers.SH_LEN] == 1]
## traces with a maximum stretch
# logger.warn('[r]!!!ONLY WITH STRETCH[/]')
# meta = [x for x in meta if x[helpers.STRETCH] > -1]
# # shorter meta records
# logger.warn('[r]!!!ONLY SHORT TRACES[/]')
# meta = [x for x in meta if len(x[helpers.TRACE]) < 5]
# meta_map = {tuple(x[helpers.TRACE]): x for x in meta_filled}
logger.info('All trace count: %d' % len(meta_filled))
tr_count = min(len(meta_filled), count)
meta_random = random.sample(meta_filled, tr_count)
logger.info('Chosen subset count: %d' % len(meta_random))
# real_vf_degree = [x for x in meta_random if x[helpers.IS_VF_DEGREE] == 1]
# real_nonvf_degree = [x for x in meta_random if x[helpers.IS_VF_DEGREE] == 0]
# assert len(real_nonvf_degree) == tr_count - len(real_vf_degree)
# real_vf_prelabeled = [x for x in meta_random if x[helpers.IS_VF_PRELABELED] == 1]
# real_nonvf_prelabeled = [x for x in meta_random if x[helpers.IS_VF_PRELABELED] == 0]
# assert len(real_nonvf_prelabeled) == tr_count - len(real_vf_prelabeled)
# real_vf_closeness = [x for x in meta_random if x[helpers.IS_VF_CLOSENESS] == 1]
# real_nonvf_closeness = [x for x in meta_random if x[helpers.IS_VF_CLOSENESS] == 0]
# assert len(real_nonvf_closeness) == tr_count - len(real_vf_closeness)
# logger.info('Real vf degree: %f[%d]' % ((len(real_vf_degree) / float(tr_count),
# len(real_vf_degree))))
# logger.info('Real nonvf degree: %f[%d]' % ((len(real_nonvf_degree) / float(tr_count),
# len(real_nonvf_degree))))
# logger.info('Real vf prelabeled: %f[%d]' % ((len(real_vf_prelabeled) / float(tr_count),
# len(real_vf_prelabeled))))
# logger.info('Real nonvf prelabeled: %f[%d]' % ((len(real_nonvf_prelabeled) / float(tr_count),
# len(real_nonvf_prelabeled))))
# logger.info('Real vf closeness: %f[%d]' % ((len(real_vf_closeness)/float(tr_count), len(real_vf_closeness))))
# logger.info('Real nonvf closeness: %f[%d]' % ((len(real_nonvf_closeness)/float(tr_count), len(real_nonvf_closeness))))
# traceroutes = [x[helpers.TRACE] for x in meta_random]
# traceroutes = vft.trace_in_vertex_id(g, traceroutes)
try:
meta_random[0][helpers.TRACE]
except Exception:
meta_random = [{helpers.TRACE: x} for x in meta_random]
progress = progressbar1.DummyProgressBar(end=10, width=15)
if show_progress:
progress = progressbar1.AnimatedProgressBar(end=len(meta_random),
width=15)
stretch_list = []
max_stretch = max(
[x[helpers.TRACE_LEN] - x[helpers.SH_LEN] for x in meta_random])
for stretch in range(0, max_stretch + 1):
metas = [
x for x in meta_random
if x[helpers.TRACE_LEN] - x[helpers.SH_LEN] == stretch
]
stretch_list.extend(list(repeat(stretch, len(metas))))
# print(stretch_list)
lenghts = random.shuffle(stretch_list)
strx_array = []
for idx, trace_meta in enumerate(meta_random):
progress += 1
progress.show_progress()
# print(trace_meta[helpers.TRACE])
shl = trace_meta[helpers.SH_LEN]
trace = vft.trace_in_vertex_id(g, [
trace_meta[helpers.TRACE],
])
if len(trace) != 1:
print 'PROBLEM'
print trace_meta
continue
trace = trace[0]
# print(trace)
random_walk_closeness_route_vf = 0
random_walk_closeness_route_lp_soft = 0
random_walk_closeness_route_lp_hard = 0
random_walk_degree_route_vf = 0
random_walk_degree_route_lp_soft = 0
random_walk_degree_route_lp_hard = 0
random_walk_prelabeled_route_vf = 0
random_walk_prelabeled_route_lp_soft = 0
random_walk_prelabeled_route_lp_hard = 0
s, t = trace[0], trace[-1]
for counter in xrange(0, try_per_race):
# random_path = helpers.random_route_walk(g, s, t, len(trace)) # Modified
random_path = helpers.random_route_walk(
g, s, t, shl + stretch_list[idx]) # Modified
if len(random_path) == 0:
empty += 1
if vft.is_valley_free(g, random_path, vfmode=vft.CLOSENESS):
random_walk_closeness_route_vf += 1
if (len(random_path) == shl + 1):
strx_array.append(1)
if with_lp:
lp_soft = vft.is_local_preferenced(g,
random_path,
first_edge=True,
vfmode=vft.CLOSENESS)
lp_hard = vft.is_local_preferenced(g,
random_path,
first_edge=False,
vfmode=vft.CLOSENESS)
if lp_soft:
random_walk_closeness_route_lp_soft += 1
if lp_hard:
random_walk_closeness_route_lp_hard += 1
else:
if (len(random_path) == shl + 1):
strx_array.append(0)
# if vft.is_valley_free(g, random_path, vfmode=vft.DEGREE):
# random_walk_degree_route_vf += 1
# if with_lp:
# lp_soft = vft.is_local_preferenced(g, random_path,
# first_edge=True,
# vfmode=vft.DEGREE)
# lp_hard = vft.is_local_preferenced(g, random_path,
# first_edge=False,
# vfmode=vft.DEGREE)
# if lp_soft:
# random_walk_degree_route_lp_soft += 1
# if lp_hard:
# random_walk_degree_route_lp_hard += 1
# if vft.is_valley_free(g, random_path, vfmode=vft.PRELABELED):
# random_walk_prelabeled_route_vf += 1
# if with_lp:
# lp_soft = vft.is_local_preferenced(g, random_path,
# first_edge=True,
# vfmode=vft.PRELABELED)
# lp_hard = vft.is_local_preferenced(g, random_path,
# first_edge=False,
# vfmode=vft.PRELABELED)
# if lp_soft:
# random_walk_prelabeled_route_lp_soft += 1
# if lp_hard:
# random_walk_prelabeled_route_lp_hard += 1
# sanity check
# if random_path[0] != s or random_path[-1] != t:
# logger.error('ALERT')
if len(random_path) != len(set(random_path)):
logger.error('LENGTH ERROR')
extra_meta = {
helpers.RANDOM_WALK_RUN_COUNT:
try_per_race,
helpers.RANDOM_WALK_VF_CLOSENESS_ROUTE:
random_walk_closeness_route_vf,
helpers.RANDOM_WALK_VF_DEGREE_ROUTE:
random_walk_degree_route_vf,
helpers.RANDOM_WALK_VF_PRELABELED_ROUTE:
random_walk_prelabeled_route_vf,
}
if with_lp:
extra_meta.update({
helpers.RANDOM_WALK_LP_SOFT_CLOSENESS_ROUTE:
random_walk_closeness_route_lp_soft,
helpers.RANDOM_WALK_LP_HARD_CLOSENESS_ROUTE:
random_walk_closeness_route_lp_hard,
helpers.RANDOM_WALK_LP_SOFT_DEGREE_ROUTE:
random_walk_degree_route_lp_soft,
helpers.RANDOM_WALK_LP_HARD_DEGREE_ROUTE:
random_walk_degree_route_lp_hard,
helpers.RANDOM_WALK_LP_SOFT_PRELABELED_ROUTE:
random_walk_prelabeled_route_lp_soft,
helpers.RANDOM_WALK_LP_HARD_PRELABELED_ROUTE:
random_walk_prelabeled_route_lp_hard
})
trace_meta.update(extra_meta)
## save modified meta
# all meta_* get only references from meta_original
helpers.save_to_json(out, meta_random)
# meta_mod = [x for x in meta_map.itervalues()]
# helpers.save_to_json(out, meta_mod)
# calculate results
# real_vf = [x[helpers.IS_VF_CLOSENESS] for x in meta_random]
# real_vf_ratio = np.mean(real_vf)
random_walk_vf_ratio_per_element = [
x[helpers.RANDOM_WALK_VF_CLOSENESS_ROUTE] /
x[helpers.RANDOM_WALK_RUN_COUNT] for x in meta_random
]
random_walk_vf_ratio = np.mean(random_walk_vf_ratio_per_element)
# print results
logger.info('')
logger.info('Empty: %d' % empty)
logger.info('Tested trace count: %d' % len(meta_random))
# logger.info('VF ratio in tested traces: %f' % real_vf_ratio)
logger.info('VF ratio in random walks: %f' % random_walk_vf_ratio)
logger.info('VF ratio in random walks for path stretch 1: %f' %
np.mean(strx_array))
def purify(g, traceroutes, flags, show_progress=False):
results = list()
# remove traces with unknown nodes
traceroutes = vft.trace_in_vertex_id(g, traceroutes)
# generate valley-free graph
if flags[FLAG_PRELABELED]:
logger.info('Generate VF_G_PRE')
vf_g_pre = vft.convert_to_vf(g, vfmode=vft.PRELABELED)
else:
logger.info('Skip prelabeled graph')
if flags[FLAG_DEGREE]:
logger.info('Generate VF_G_DEGREE')
vf_g_degree = vft.convert_to_vf(g, vfmode=vft.DEGREE)
else:
logger.info('Skip degree graph')
if flags[FLAG_CLOSENESS]:
logger.info('Generate VF_G_CLOSENESS')
vf_g_closeness = vft.convert_to_vf(g, vfmode=vft.CLOSENESS)
else:
logger.info('Skip closeness graph')
progress = progressbar1.DummyProgressBar(end=10, width=15)
if show_progress:
progress = progressbar1.AnimatedProgressBar(end=len(traceroutes),
width=15)
for trace in traceroutes:
progress += 1
progress.show_progress()
logger.debug('Current trace: %s' % ([g.vs[x]['name'] for x in trace]))
if len(trace) == 1: continue
s, t = trace[0], trace[-1]
is_vf_prelabeled = -1
is_lp_prelabeled_hard = -1
is_lp_prelabeled_soft = -1
is_vf_degree = -1
is_lp_degree_hard = -1
is_lp_degree_soft = -1
is_vf_closeness = -1
is_lp_closeness_hard = -1
is_lp_closeness_soft = -1
trace_len = len(trace)
sh_len = g.shortest_paths(s, t, mode=i.OUT)[0][0]
sh_len += 1 # convert hop count to node Counter
if flags[FLAG_PRELABELED]:
is_vf_prelabeled = vft.is_valley_free(g, trace, vft.PRELABELED)
is_vf_prelabeled = int(is_vf_prelabeled)
if is_vf_prelabeled:
if flags[FLAG_LP_SOFT]:
lp_soft = vft.is_local_preferenced(g,
trace,
vf_g=vf_g_pre,
first_edge=True,
vfmode=vft.PRELABELED)
is_lp_prelabeled_soft = 1 if lp_soft else 0
else:
is_lp_prelabeled_soft = -1
if flags[FLAG_LP_HARD]:
lp_hard = vft.is_local_preferenced(g,
trace,
vf_g=vf_g_pre,
first_edge=False,
vfmode=vft.PRELABELED)
is_lp_prelabeled_hard = 1 if lp_hard else 0
else:
is_lp_prelabeled_hard = -1
if flags[FLAG_DEGREE]:
is_vf_degree = vft.is_valley_free(g, trace, vft.DEGREE)
is_vf_degree = int(is_vf_degree)
if is_vf_degree:
if flags[FLAG_LP_SOFT]:
lp_soft = vft.is_local_preferenced(g,
trace,
vf_g=vf_g_degree,
first_edge=True,
vfmode=vft.DEGREE)
is_lp_degree_soft = 1 if lp_soft else 0
else:
is_lp_degree_soft = -1
if flags[FLAG_LP_HARD]:
lp_hard = vft.is_local_preferenced(g,
trace,
vf_g=vf_g_degree,
first_edge=False,
vfmode=vft.DEGREE)
is_lp_degree_hard = 1 if lp_hard else 0
else:
is_lp_degree_hard = -1
if flags[FLAG_CLOSENESS]:
is_vf_closeness = vft.is_valley_free(g, trace, vft.CLOSENESS)
is_vf_closeness = int(is_vf_closeness)
if is_vf_closeness:
if flags[FLAG_LP_SOFT]:
lp_soft = vft.is_local_preferenced(g,
trace,
vf_g=vf_g_closeness,
first_edge=True,
vfmode=vft.CLOSENESS)
is_lp_closeness_soft = 1 if lp_soft else 0
else:
is_lp_closeness_soft = -1
if flags[FLAG_LP_HARD]:
lp_hard = vft.is_local_preferenced(g,
trace,
vf_g=vf_g_closeness,
first_edge=False,
vfmode=vft.CLOSENESS)
is_lp_closeness_hard = 1 if lp_hard else 0
else:
is_lp_closeness_hard = -1
if False:
sh_vf_len = vft.get_shortest_vf_route(g,
s,
t,
mode='vf',
vf_g=vf_g_pre,
_all=True,
vfmode=vft.PRELABELED)
# ugy tunik, mintha nem mindig lenne pontos? fentartassal kezelendo
# ez az ertek azert is kerult bele, hogy ellenorizzuk
in_vf_prediction = 1 if sh_vf_len and trace in sh_vf_len else 0
else:
sh_vf_len = -1
in_vf_prediction = -1
sh_vf_len = len(sh_vf_len[0]) if isinstance(sh_vf_len, list) else -1
percentage_stretch = trace_len / float(sh_len)
named_trace = [g.vs[_id]["name"] for _id in trace]
result = {
helpers.TRACE: named_trace,
helpers.TRACE_LEN: trace_len,
helpers.SH_LEN: sh_len,
helpers.SH_VF_LEN: sh_vf_len,
helpers.IS_VF_PRELABELED: is_vf_prelabeled,
helpers.IS_VF_DEGREE: is_vf_degree,
helpers.IS_VF_CLOSENESS: is_vf_closeness,
helpers.HOP_STRETCH: trace_len - sh_len,
helpers.PERC_STRETCH: percentage_stretch,
helpers.IN_VF_PRED: in_vf_prediction,
helpers.IS_LP_SOFT_PRELABELED: is_lp_prelabeled_soft,
helpers.IS_LP_HARD_PRELABELED: is_lp_prelabeled_hard,
helpers.IS_LP_SOFT_DEGREE: is_lp_degree_soft,
helpers.IS_LP_HARD_DEGREE: is_lp_degree_hard,
helpers.IS_LP_SOFT_CLOSENESS: is_lp_closeness_soft,
helpers.IS_LP_HARD_CLOSENESS: is_lp_closeness_hard,
}
results.append(result)
# print >> sys.stderr, ('TRACE\tTRACE_LEN\tSH_LEN\tSH_VF_LEN\tIS_VF',
# '\tSTRETCH\tIN_VF_PREDICTION\tIS_LP_F\tIS_LP_ALL')
# for result in results:
# result = [str(r) for r in result]
# print >> sys.stderr, '\t'.join(result)
# statistic = statistics.purify(g, results,
# 'nc+ec+tc+rt+vf+vf_closeness+pred+lp_soft_prelabeled+lp_hard_prelabeled+lp_soft_degree+lp_hard_degree+lp_soft_closeness+lp_hard_closeness'.split('+'))
# statistics.stat_printer(statistic)
return results
def test_soft_lp_check(self):
self.sample_graph.add_vertices([
'N8',
])
self.prelabeled[8] = 0.5
self.closenesses[8] = 0.5
self.sample_graph.add_edges([['N5', 'N7'], ['N3', 'N7'], ['N8', 'N5'],
['N6', 'N8'], ['N7', 'N4']])
lp_hard_routes = [['N0', 'N5', 'N6', 'N2'], ['N5', 'N6'],
['N4', 'N6', 'N2'], ['N7', 'N4', 'N6', 'N3']]
# Az egyetlen kulonbseg a soft es hard lp kozott
# csak akkor johet elo, mikor U ellel kezdunk, es
# a kov. hopnal lehet fel vagy le/peer elen menni
# A soft ekkor mehet tovabb fel, a hard csak peer/le
# elet valaszthat.
lp_soft_routes = [['N0', 'N5', 'N4', 'N6', 'N2'],
['N1', 'N5', 'N6', 'N8']]
non_lp = [['N5', 'N4', 'N6'], ['N5', 'N6', 'N8'],
['N5', 'N4', 'N6', 'N2']]
vf_g = vft.convert_to_vf(self.sample_graph, vfmode=vft.CLOSENESS)
for trace in lp_hard_routes:
is_lp_hard = vft.is_local_preferenced(self.sample_graph,
trace,
vf_g=vf_g,
first_edge=False,
vfmode=vft.CLOSENESS)
is_lp_soft = vft.is_local_preferenced(self.sample_graph,
trace,
vf_g=vf_g,
first_edge=True,
vfmode=vft.CLOSENESS)
self.assertTrue(is_lp_hard)
self.assertTrue(is_lp_soft)
for trace in lp_soft_routes:
is_lp_hard = vft.is_local_preferenced(self.sample_graph,
trace,
vf_g=vf_g,
first_edge=False,
vfmode=vft.CLOSENESS)
is_lp_soft = vft.is_local_preferenced(self.sample_graph,
trace,
vf_g=vf_g,
first_edge=True,
vfmode=vft.CLOSENESS)
self.assertFalse(is_lp_hard)
self.assertTrue(is_lp_soft)
for trace in non_lp:
is_lp_hard = vft.is_local_preferenced(self.sample_graph,
trace,
vf_g=vf_g,
first_edge=False,
vfmode=vft.CLOSENESS)
is_lp_soft = vft.is_local_preferenced(self.sample_graph,
trace,
vf_g=vf_g,
first_edge=True,
vfmode=vft.CLOSENESS)
self.assertFalse(is_lp_hard)
self.assertFalse(is_lp_soft)
def purify(g,
meta_original,
out,
count=1000,
try_per_race=1,
show_progress=False):
empty = 0
# remove traces with already calculated random paths
logger.warn('[r]ONLY NOT FILLED PATHS[/]')
meta_filled = [
x for x in meta_original
if helpers.RANDOM_NONVF_WALK_RUN_COUNT not in x
]
logger.info('All trace count: %d' % len(meta_filled))
tr_count = min(len(meta_filled), count)
meta_random = random.sample(meta_filled, tr_count)
logger.info('Chosen subset count: %d' % len(meta_random))
real_vf_degree = [x for x in meta_random if x[helpers.IS_VF_DEGREE] == 1]
real_nonvf_degree = [
x for x in meta_random if x[helpers.IS_VF_DEGREE] == 0
]
assert len(real_nonvf_degree) == tr_count - len(real_vf_degree)
real_vf_prelabeled = [
x for x in meta_random if x[helpers.IS_VF_PRELABELED] == 1
]
real_nonvf_prelabeled = [
x for x in meta_random if x[helpers.IS_VF_PRELABELED] == 0
]
assert len(real_nonvf_prelabeled) == tr_count - len(real_vf_prelabeled)
real_vf_closeness = [
x for x in meta_random if x[helpers.IS_VF_CLOSENESS] == 1
]
real_nonvf_closeness = [
x for x in meta_random if x[helpers.IS_VF_CLOSENESS] == 0
]
assert len(real_nonvf_closeness) == tr_count - len(real_vf_closeness)
logger.info('Real vf degree: %f[%d]' %
((len(real_vf_degree) / float(tr_count), len(real_vf_degree))))
logger.info(
'Real nonvf degree: %f[%d]' %
((len(real_nonvf_degree) / float(tr_count), len(real_nonvf_degree))))
logger.info(
'Real vf prelabeled: %f[%d]' %
((len(real_vf_prelabeled) / float(tr_count), len(real_vf_prelabeled))))
logger.info('Real nonvf prelabeled: %f[%d]' %
((len(real_nonvf_prelabeled) / float(tr_count),
len(real_nonvf_prelabeled))))
logger.info(
'Real vf closeness: %f[%d]' %
((len(real_vf_closeness) / float(tr_count), len(real_vf_closeness))))
logger.info('Real nonvf closeness: %f[%d]' %
((len(real_nonvf_closeness) / float(tr_count),
len(real_nonvf_closeness))))
progress = progressbar1.DummyProgressBar(end=10, width=15)
if show_progress:
progress = progressbar1.AnimatedProgressBar(end=len(meta_random),
width=15)
for trace_meta in meta_random:
progress += 1
progress.show_progress()
trace = vft.trace_in_vertex_id(g, [
trace_meta[helpers.TRACE],
])
if len(trace) != 1:
logger.error('PROBLEM')
logger.error('%s' % trace_meta)
continue
trace = trace[0]
random_nonvf_walk_closeness_route_count = 0
random_nonvf_walk_closeness_route_len = []
random_nonvf_walk_degree_route_count = 0
random_nonvf_walk_degree_route_len = []
random_nonvf_walk_prelabeled_route_count = 0
random_nonvf_walk_prelabeled_route_len = []
random_nonvf_walk_lp_soft_closeness_route_count = 0
random_nonvf_walk_lp_soft_degree_route_count = 0
random_nonvf_walk_lp_soft_prelabeled_route_count = 0
random_nonvf_walk_lp_hard_closeness_route_count = 0
random_nonvf_walk_lp_hard_degree_route_count = 0
random_nonvf_walk_lp_hard_prelabeled_route_count = 0
s, t = trace[0], trace[-1]
for counter in xrange(0, try_per_race):
isvf, random_path = helpers.random_nonvf_route(
g, s, t, len(trace), vfmode=vft.CLOSENESS)
assert len(random_path) > 0
if isvf:
random_nonvf_walk_closeness_route_count += 1
lp_soft = vft.is_local_preferenced(g,
trace,
first_edge=True,
vfmode=vft.CLOSENESS)
lp_hard = vft.is_local_preferenced(g,
trace,
first_edge=False,
vfmode=vft.CLOSENESS)
if lp_soft:
random_nonvf_walk_lp_soft_closeness_route_count += 1
if lp_hard:
random_nonvf_walk_lp_hard_closeness_route_count += 1
random_nonvf_walk_closeness_route_len.append(len(random_path))
isvf, random_path = helpers.random_nonvf_route(g,
s,
t,
len(trace),
vfmode=vft.DEGREE)
assert len(random_path) > 0
if isvf:
random_nonvf_walk_degree_route_count += 1
lp_soft = vft.is_local_preferenced(g,
trace,
first_edge=True,
vfmode=vft.DEGREE)
lp_hard = vft.is_local_preferenced(g,
trace,
first_edge=False,
vfmode=vft.DEGREE)
if lp_soft:
random_nonvf_walk_lp_soft_degree_route_count += 1
if lp_hard:
random_nonvf_walk_lp_hard_degree_route_count += 1
random_nonvf_walk_degree_route_len.append(len(random_path))
isvf, random_path = helpers.random_nonvf_route(
g, s, t, len(trace), vfmode=vft.PRELABELED)
assert len(random_path) > 0
if isvf:
random_nonvf_walk_prelabeled_route_count += 1
lp_soft = vft.is_local_preferenced(g,
trace,
first_edge=True,
vfmode=vft.PRELABELED)
lp_hard = vft.is_local_preferenced(g,
trace,
first_edge=False,
vfmode=vft.PRELABELED)
if lp_soft:
random_nonvf_walk_lp_soft_prelabeled_route_count += 1
if lp_hard:
random_nonvf_walk_lp_hard_prelabeled_route_count += 1
random_nonvf_walk_prelabeled_route_len.append(len(random_path))
# sanity check
# if random_path[0] != s or random_path[-1] != t:
# logger.error('ALERT')
if len(random_path) != len(set(random_path)):
logger.error('LENGTH ERROR')
extra_meta = {
helpers.RANDOM_NONVF_WALK_RUN_COUNT:
try_per_race,
helpers.RANDOM_NONVF_WALK_VF_CLOSENESS_ROUTE:
random_nonvf_walk_closeness_route_count,
helpers.RANDOM_NONVF_WALK_VF_CLOSENESS_ROUTE_LEN:
random_nonvf_walk_closeness_route_len,
helpers.RANDOM_NONVF_WALK_VF_DEGREE_ROUTE:
random_nonvf_walk_degree_route_count,
helpers.RANDOM_NONVF_WALK_VF_DEGREE_ROUTE_LEN:
random_nonvf_walk_degree_route_len,
helpers.RANDOM_NONVF_WALK_VF_PRELABELED_ROUTE:
random_nonvf_walk_prelabeled_route_count,
helpers.RANDOM_NONVF_WALK_VF_PRELABELED_ROUTE_LEN:
random_nonvf_walk_prelabeled_route_len,
helpers.RANDOM_NONVF_WALK_LP_SOFT_DEGREE_ROUTE:
random_nonvf_walk_lp_soft_degree_route_count,
helpers.RANDOM_NONVF_WALK_LP_SOFT_CLOSENESS_ROUTE:
random_nonvf_walk_lp_soft_closeness_route_count,
helpers.RANDOM_NONVF_WALK_LP_SOFT_PRELABELED_ROUTE:
random_nonvf_walk_lp_soft_prelabeled_route_count,
helpers.RANDOM_NONVF_WALK_LP_HARD_DEGREE_ROUTE:
random_nonvf_walk_lp_hard_degree_route_count,
helpers.RANDOM_NONVF_WALK_LP_HARD_CLOSENESS_ROUTE:
random_nonvf_walk_lp_hard_closeness_route_count,
helpers.RANDOM_NONVF_WALK_LP_HARD_PRELABELED_ROUTE:
random_nonvf_walk_lp_hard_prelabeled_route_count
}
trace_meta.update(extra_meta)
## save modified meta
# all meta_* get only references from meta_original
helpers.save_to_json(out, meta_original)
# calculate results
real_vf = [x[helpers.IS_VF_CLOSENESS] for x in meta_random]
real_vf_ratio = np.mean(real_vf)
random_nonvf_walk_vf_ratio_per_element = [
x[helpers.RANDOM_NONVF_WALK_VF_CLOSENESS_ROUTE] /
x[helpers.RANDOM_NONVF_WALK_RUN_COUNT] for x in meta_random
]
random_nonvf_walk_vf_ratio = np.mean(
random_nonvf_walk_vf_ratio_per_element)
# print results
logger.info('')
logger.info('Empty: %d' % empty)
logger.info('Tested trace count: %d' % len(meta_random))
logger.info('VF ratio in tested traces: %f' % real_vf_ratio)
logger.info('VF ratio in random walks: %f' % random_nonvf_walk_vf_ratio)