写一个使用sklearn生成TF-IDF词向量的模板函数：

from sklearn import feature_extraction # 导入sklearn库, 以获取文本的tf-idf值
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.feature_extraction.text import CountVectorizer

def getVector(get_texts):
    mat = CountVectorizer()
    tf = TfidfTransformer()
    tfidf = tf.fit_transform(mat.fit_transform(get_texts))
    word = mat.get_feature_names() # 单词的名称
    weight=tfidf.toarray() # 权重矩阵, 在此示范中矩阵为(1, n)
    return weight