def ReadAlarmsFromFile(fileName):
file = open(fileName)
adi = AlarmDataInterface('grande', 27017, 'historic_alarm', 'raw_event')
mdbi = MongoDBInterface('grande', 27017)
mdbi.SetDB('historic_alarm')
mdbi.SetCollection('raw_event')
event = []
for line in file:
if not line == '\n':
event.append(line)
else:
if not event == []:
print 'find an event'
# in json
processedEvent = ProcessRawEvents(event)
merged = adi.MergeEvent(processedEvent)
if not merged:
mdbi.SaveItem(processedEvent)
event = []
def main():
# inintialize the database for storing the alarms
myDB = MongoDBInterface('grande', 27017)
myDB.SetDB('alarm_filter')
myDB.SetCollection('photos')
adi = AlarmDataInterface()
regions = read_regions()
for region in regions:
to_save = {
'mid_lat': region[0],
'mid_lng': region[1],
'valid': False,
'real_count': -1,
'mu': -1,
'std': -1,
'photos': [],
'zscore': -1
}
photos = []
try:
ts, photos = find_photos_given_region(region[0], region[1],
'15Min', 'tmp_citybeat',
True)
except Exception as e:
save_to_mongo(to_save)
continue
sz = len(ts)
cur_value = 0
if sz > 0:
cur_time = ts.index[len(ts.index) - 1]
if isnull(ts.values[len(ts.values) - 1]):
cur_value = -1
else:
cur_value = ts.values[len(ts.values) - 1]
else:
save_to_mongo(to_save)
continue
if total_seconds(datetime.utcnow() - cur_time) > 900:
# there's no latest photo at this region
save_to_mongo(to_save)
continue
try:
predictions = get_prediction(str(region[0]), str(region[1]))
except Exception as e:
save_to_mongo(to_save)
continue
predict = -1
for p in predictions:
seconds = total_seconds(p['time'] - cur_time)
if (seconds <= 3600 and seconds >= 0):
#print 'p time is ',p['time'], 'cur_time is ',cur_time
predict = p
if predict == -1:
save_to_mongo(to_save)
continue
mu = float(predict['mu']) / 4.0
std = sqrt(float(predict['var'])) / 4.0
zscore = (cur_value - mu) / std
within_range = float(predict['mu']) / 4.0 + 3 * sqrt(
float(predict['var'])) / 4.0
photos_to_save = []
for photo in photos:
delta = total_seconds(
cur_time -
datetime.utcfromtimestamp(float(photo['created_time'])))
if delta >= 0 and delta <= 900:
photo['label'] = 'unlabeled'
photos_to_save.append(photo)
to_save['photos'] = photos_to_save
to_save['real_count'] = cur_value
to_save['valid'] = True
to_save['std'] = sqrt(float(predict['var'])) / 4.0
to_save['mu'] = float(predict['mu']) / 4.0
to_save['zscore'] = zscore
save_to_mongo(to_save)
if zscore >= 2.0 and cur_value >= 3:
print datetime.utcnow()
print region[0], ",", region[1]
print float(predict['mu']) / 4.0, sqrt(
float(predict['var']
)) / 4.0, 'range ', within_range, 'real-> ', cur_value
for photo in photos_to_save:
print 'printing photos: ', photo['link'], photo[
'created_time'], photo['id'], datetime.utcfromtimestamp(
float(photo['created_time']))
#group photos into an unlabeled event and save it to the db
predicted_mu = float(predict['mu']) / 4.0
predicted_std = sqrt(float(predict['var'])) / 4.0
newEvent = {
'created_time': datetime.utcnow(),
'mid_lat': region[0],
'mid_lng': region[1],
'predicted_mu': predicted_mu,
'predicted_std': predicted_std,
'actual_value': cur_value,
'zscore': zscore,
'photos': photos_to_save,
'label': 'unlabeled'
}
if not adi.MergeEvent(newEvent):
print 'created an event'
myDB.SaveItem(newEvent)
else:
print 'merged an event'
print '\n'