from sklearn.feature_extraction.text import CountVectorizer, TfidfTransformer
import pandas as pd

from spacy.lang.en.stop_words import STOP_WORDS as en_stop


class VectorizerTf:

    def __init__(self, corpus):
        vectorizer = CountVectorizer(stop_words=en_stop)
        self.tf_matrix = vectorizer.fit_transform(corpus)
        self.vectorizer = vectorizer
        self.feature_names = self.vectorizer.get_feature_names()

    def get_tf_for_document(self, term):
        return self.vectorizer.transform([term]).toarray()