def fireAlarm(self):
self._getFiftenMiniutesPhotos() #get current_value
cur_hour = datetime.utcfromtimestamp(float(self.cur_time)).hour
#print 'cur_hour = ',cur_hour, 'time = ',self.cur_time
mu = self.means[cur_hour] / 4.0
std = self.stds[cur_hour] / 4.0
#print 'mu is ',mu, 'std is ',std, 'cur_value = ',self.current_value
zscore = (self.current_value - mu) * 1.0 / std
if zscore > 3 and self.current_value >= 8:
e = Event()
e.setPredictedValues(mu, std)
e.setZscore(zscore)
e.setRegion(self.region)
e.setCreatedTime(self.cur_time)
e.setActualValue(self.current_value)
for p in self.photos:
e.addPhoto(p)
ei = EventInterface()
ei.setCollection(self.candidate_collection)
#print datetime.utcfromtimestamp(float(e.getEarliestPhotoTime())), datetime.utcfromtimestamp(float(e.getLatestPhotoTime()))
#print e.getEarliestPhotoTime(),e.getLatestPhotoTime()
#print e.toJSON()['region']
ei.addEvent(e)
def fireAlarm(self):
prediction = self.getNearestPrediction()
self._getFiftenMiniutesPhotos()
if prediction is None:
print "None data for this region: details as follow"
self.region.display()
print "time:", self.cur_time
return
mu = float(prediction["mu"]) / 4.0
std = float(prediction["std"]) / 4.0
time_stamp = prediction["time"]
zscore = (self.current_value - mu) * 1.0 / std
if zscore > 3:
e = Event()
e.setPredictedValues(mu, std)
e.setZscore(zscore)
e.setRegion(self.region)
e.setCreatedTime(self.cur_time)
e.setActualValue(self.current_value)
for p in self.photos:
e.addPhoto(p)
# print 'current value ',4.0*self.current_value, ' predict = ',mu*4.0,' std = ',std*4.0
ei = EventInterface()
ei.setCollection(self.candidate_collection)
print e.getEarliestPhotoTime(), e.getLatestPhotoTime()
# print e.toJSON()['region']
# ei.addEvent(e)
ei.addEventWithoutMerge(e)
def fireAlarm(self):
prediction = self.getNearestPrediction()
self._getFiftenMiniutesPhotos()
if prediction is None:
print 'None data for this region: details as follow'
self.region.display()
print 'time:', self.cur_time
return
mu = float(prediction['mu']) / 4.0
std = float(prediction['std']) / 4.0
time_stamp = prediction['time']
zscore = (self.current_value - mu) * 1.0 / std
if zscore > 3:
e = Event()
e.setPredictedValues(mu, std)
e.setZscore(zscore)
e.setRegion(self.region)
e.setCreatedTime(self.cur_time)
e.setActualValue(self.current_value)
for p in self.photos:
e.addPhoto(p)
#print 'current value ',4.0*self.current_value, ' predict = ',mu*4.0,' std = ',std*4.0
ei = EventInterface()
ei.setCollection(self.candidate_collection)
print e.getEarliestPhotoTime(), e.getLatestPhotoTime()
#print e.toJSON()['region']
#ei.addEvent(e)
ei.addEventWithoutMerge(e)
def fireAlarm(self):
self._getFiftenMiniutesPhotos() #get current_value
cur_hour = datetime.utcfromtimestamp(float(self.cur_time)).hour
#print 'cur_hour = ',cur_hour, 'time = ',self.cur_time
mu = self.means[cur_hour]/4.0
std = self.stds[cur_hour]/4.0
#print 'mu is ',mu, 'std is ',std, 'cur_value = ',self.current_value
zscore = (self.current_value - mu)*1.0/std
if zscore > 3 and self.current_value>=8:
e = Event()
e.setPredictedValues(mu, std)
e.setZscore(zscore)
e.setRegion(self.region)
e.setCreatedTime(self.cur_time)
e.setActualValue(self.current_value)
for p in self.photos:
e.addPhoto(p)
ei = EventInterface( )
ei.setCollection(self.candidate_collection)
#print datetime.utcfromtimestamp(float(e.getEarliestPhotoTime())), datetime.utcfromtimestamp(float(e.getLatestPhotoTime()))
#print e.getEarliestPhotoTime(),e.getLatestPhotoTime()
#print e.toJSON()['region']
ei.addEvent(e)
