def demo():
pkfile = open('ustcpassages_503.pkl', 'r')
passages = pickle.load(pkfile)
pkfile.close()
print len(passages)
passages.sort(cmp=lambda x, y: cmp(x.score, y.score), reverse=True)
model = EssayModel()
model.train(passages)
print model.triGramDicts
for p in passages:
c = model.wordCombScore(p)
print p.score, len(p.trigrams), c, c * 1.0 / len(p.trigrams)
extractor = FeatherExtractor(model)
extractor.extractLangFeather(passages[-1])
extractor.extractContentFeather(passages[-1])
extractor.extractStructureFeather(passages[-1])
def demo():
pkfile = open('ustcpassages_503.pkl', 'r')
passages = pickle.load(pkfile)
pkfile.close()
print len(passages)
passages.sort(cmp=lambda x,y: cmp(x.score, y.score), reverse=True)
model = EssayModel()
model.train(passages)
print model.triGramDicts
for p in passages:
c = model.wordCombScore(p)
print p.score, len(p.trigrams), c, c*1.0/len(p.trigrams)
extractor = FeatherExtractor(model)
extractor.extractLangFeather(passages[-1])
extractor.extractContentFeather(passages[-1])
extractor.extractStructureFeather(passages[-1])
