for x in range(0, 3000):
alert = []
for y in range(0, 6):
alert.append(repr(randint(0, 8 - 1)) + "test")
for c in hcombinations:
label = []
key = alert[:]
for x in range(2):
key[c[x]] = "*"
label.append(alert[c[x]])
hyperkey = tuple(key)
hlabel = tuple(label)
if hyperkey in hyper_dict:
hyper_dict[hyperkey].nalerts += 1
result = hyper_dict[hyperkey].get_alert(hlabel)
if result is not None:
hyper_dict[hyperkey].insert_alert(hlabel, result + 1)
else:
hyper_dict[hyperkey].insert_alert(hlabel, 1)
else:
hyper_dict[hyperkey] = Hyperedge(key, c, hlabel)
for hyperedge in hyper_dict.values():
hypersize_list.insert((hyperedge.nalerts, hyperedge.hyperkey), hyperedge)
while not hypersize_list.is_empty():
(key, hyperedge) = hypersize_list.pop_max()
hyperedge.foreach_alert(treeloop)
print("Completed iteration %d of 10" % z)
alert = []
for y in range(0, 6):
alert.append(repr(randint(0, 8 - 1)) + "test")
for c in hcombinations:
label = []
key = alert[:]
for x in range(2):
key[c[x]] = '*'
label.append(alert[c[x]])
hyperkey = tuple(key)
hlabel = tuple(label)
if hyperkey in hyper_dict:
hyper_dict[hyperkey].nalerts += 1
result = hyper_dict[hyperkey].get_alert(hlabel)
if result is not None:
hyper_dict[hyperkey].insert_alert(hlabel, result + 1)
else:
hyper_dict[hyperkey].insert_alert(hlabel, 1)
else:
hyper_dict[hyperkey] = Hyperedge(key, c, hlabel)
for hyperedge in hyper_dict.values():
hypersize_list.insert((hyperedge.nalerts, hyperedge.hyperkey),
hyperedge)
while not hypersize_list.is_empty():
(key, hyperedge) = hypersize_list.pop_max()
hyperedge.foreach_alert(treeloop)
print("Completed iteration %d of 10" % z)
class MINPolicy(object):
def __init__(self, cache_size_limit, trace, csv_suffix=".csv"):
self.cache_size_limit = cache_size_limit
self.cache = {}
self.hits = 0.0
self.requests = 0.0
self.ts_order = ['row', 'hit']
self.ts_datapoint = {key: None for key in self.ts_order}
self.ts_datapoint['row'] = 0
self.ts_file = open("csv/min" + csv_suffix, "w")
self.ts_writer = csv.writer(self.ts_file)
self.ts_writer.writerow(self.ts_order)
self.clairvoyance = FastRBTree()
self.precog = FastRBTree()
last_time = time.time()
for i, page_opcode in enumerate(trace):
if time.time() > last_time + 0.1:
last_time = time.time()
print '1', i, '\r',
sys.stdout.flush()
page, _ = page_opcode
try:
self.precog[page].append(i)
except KeyError:
self.precog[page] = collections.deque()
self.precog[page].append(i)
known_max = i
known_max += 2
for times in self.precog.values():
times.append(known_max)
known_max += 1
print
print 'Done loading.'
def hit_rate(self):
return self.hits / self.requests
def request(self, page):
self.requests += 1
if page in self.cache:
was_hit = True
self.hits += 1
else:
was_hit = False
self.cache[page] = self.precog[page].popleft()
# This happens on startup.
if self.cache[page] < self.requests:
self.cache[page] = self.precog[page].popleft()
self.clairvoyance[self.cache[page]] = page
self.ts_datapoint['row'] += 1
if was_hit:
self.ts_datapoint['hit'] = 1
else:
self.ts_datapoint['hit'] = 0
self.ts_writer.writerow(
[self.ts_datapoint[key] for key in self.ts_order])
self.ts_file.flush()
if len(self.cache) > self.cache_size_limit:
next_use, page = self.clairvoyance.pop_max()
del self.cache[page]
