def setUp(self):
self.sentence=[]
self.itemlist=["A","B","C","C","D","A","B","B","A","D","C","B","C","A","D","A","C","D","B","D","A","A","D"]
with codecs.open("strarf_serif.txt",'rb','utf-8') as f:
for line in f:
self.sentence.append(line)
self.sentence.append(u"EOS")
self.itemlistsentence=mecabCaller.parse(self.sentence)
def judge(self, text):
sum = 0
esc = [u'…', u'・', u'.', u',', u'、', u'。', u'!', u'?', u'！', u'？']
words = mecabCaller.parse(text)
for word in words:
if word in esc:
pass
elif word in self.freq:
sum = self.freq[word]
print words
print 'sum=' + str(sum)
weightedsum = sum / len(words)
print 'weightedsum=' + str(weightedsum)
if weightedsum >= 8:
return True
else:
return False
def generate_unigram_model(favs):
try:
freqfav = cpickler.frompickle(filename='favs_model_unigram.dump')
except:
freqfav = {}
esc = [u'…', u'・', u'.', u',', u'、', u'。', u'!', u'?', u'！', u'？']
for favlist in favs:
for fav in favlist:
itemlist = mecabCaller.parse(fav.text)
for itemraw in itemlist:
item = [x for x in itemraw if x in esc]
if item in freqfav:
freqfav[item] += 1
else:
freqfav[item] = 1
cpickler.topickle(freqfav, filename='favs_model_unigram.dump')
return freqfav
