def process(source):
"""
Simple processing
"""
s = CDRStream(asterisk_like, source)
s.start()
for st in s:
cdr = csv_to_cdr(list(csv.reader(StringIO(st), delimiter=','))[0])
if not users.get(cdr.src):
users[cdr.src] = Pattern(cdr.src)
pattern = users[cdr.src]
if pattern.is_converged() and not pattern.is_conform(cdr):
pattern.alarm(cdr)
pattern.maintain(cdr)
def process_2(source):
s = CDRStream(asterisk_like, source)
s.start()
recalculate.km_time = 0
for st in s:
cdr = csv_to_cdr(list(csv.reader(StringIO(st), delimiter=','))[0])
if not users.get(cdr.src):
users[cdr.src] = Pattern(cdr.src)
pattern = users[cdr.src]
if pattern.is_converged() and not pattern.is_conform(cdr):
pattern.alarm(cdr)
pattern.maintain(cdr)
if cdr.start - recalculate.km_time >= 24*60*60*7:
# Once a week recalculate clusters
recalculate(cdr.start)
recalculate(cdr.start)
def test(source):
s = CDRStream(asterisk_like, source)
s.start()
hours = np.zeros(24)
l = []
days = 1
prev = 0
pattern = None
for st in s:
cdr = csv_to_cdr(list(csv.reader(StringIO(st), delimiter=','))[0])
if time_of_day(cdr.start) < prev:
days += 1
if days > 14 and pattern is None:
pattern = hours/days
hours = np.zeros(24)
if days > 14 and days%7 == 0:
print(np.linalg.norm(hours/(days-14) - pattern))
h = time_of_day(cdr.start)//60//60
hours[h] += 1
prev = time_of_day(cdr.start)
#l.append(h)
fingerprint = hours/days
print(fingerprint)
