def generateData2():
# if sparse:
#rep = Representor()
all_corpus = buildAllCorpus(time_interval_length=14, debug=True)
true_event_list, false_event_list = loadUnbalancedData()
BaseFeatureProduction.GenerateArffFileHeader()
for event in true_event_list + false_event_list:
r = Region(event['region'])
corpus = all_corpus[r.getKey()]
BaseFeatureProduction(event, corpus, None).printFeatures()
def testWithTweet():
cnt = 0
corpus_all = buildAllCorpus(element_type='tweets', debug=False)
ei = EventInterface()
ei.setDB('citybeat_experiment')
ei.setCollection('twitter_candidate_events')
cur = ei.getAllDocuments()
print TwitterFeature.GenerateArffFileHeader()
for event in cur:
region = Region(event['region'])
event = TwitterFeature(event, corpus=corpus_all[region.getKey()])
if event.getActualValue() < 8:
print '< 8'
continue
cnt += 1
print event.extractFeatures()
print cnt, cur.count()
def _getEventWordCorpus(self, event):
region = Region(Event(event).toDict()["region"])
return self._corpus_dicts_word[region.getKey()]
def _getEventCharCorpus(self, event):
region = Region(Event(event).toDict()["region"])
return self._corpus_dicts_char[region.getKey()]
