def getdf_from(items):
df = {}
for item in items:
feat = extractd.getngram(item['text'])
for w in feat:
try:
df[w].add(item["id"])
except KeyError:
df[w] = set([ item['id'] ])
#return [ (w, len(f)) for w, f in df.items() ]
return df
def feature(t_begin, t_end, screen_names):
ngram = {}
table = {}
for j, u in enumerate(screen_names):
query = { 'created_at': { '$gt': t_begin, '$lt': t_end }, 'screen_name': u }
for item in db.find(query):
text = item['text']
id = item['id']
try:
replied_id = item['in_reply_to_status_id']
if replied_id:
for ii in db.find({ 'id': replied_id }):
text += u'。%s' % ii['text']
except KeyError:
pass
"""
feats = bow.bagofwords(text)
for f in feats:
print(' '.join(f))
continue
"""
feat = extractd.getngram(text)
for w in set(feat):
if len(unicode(w)) < 2:
continue
if len(patterns.hiragana.findall(unicode(w))[0]) == len(unicode(w)):
continue
if w in patterns.english_words:
continue
if not w in ngram: ngram[w] = {}
utils.count(ngram[w], u)
try:
#table[w].append(text)
table[w].add(id)
except KeyError:
#table[w] = [ text ]
table[w] = set([ id ])
tags = extractd.gethashtags(item)
for t in set(tags):
if not t in ngram: ngram[t] = {}
utils.count(ngram[t], u)
try:
#table[t].append(text)
table[t].add(id)
except KeyError:
#table[t] = [ text ]
table[t] = set([ id ])
urls = extractd.geturls(item)
for l in set(urls):
if not l in ngram: ngram[l] = {}
utils.count(ngram[l], u)
try:
#table[l].append(text)
table[l].add(id)
except KeyError:
#table[l] = [ text ]
table[l] = set([ id ])
print('%d/%d' % (j, len(screen_names)))
return ngram, table