def show_topic(self, topicid, topn=10):
        topic = self.state.get_lambda()[topicid]
        topic = topic / topic.sum() # normalize to probability dist
        bestn = numpy.argsort(topic)[::-1][:topn]
        beststr = [(topic[id], self.id2word[id]) for id in bestn]
        return beststr
dataset/ETHPy150Open largelymfs/topical_word_embeddings/TWE-1/gensim/models/ldamodel.py/LdaModel.show_topic/original