code: def gen_bag_feats(self, e_set):
          
          if(hasattr(self, '_stem_dict')):
              sfeats = self._stem_dict.transform(e_set._clean_stem_text)
              nfeats = self._normal_dict.transform(e_set._text)
              bag_feats = numpy.concatenate((sfeats.toarray(), nfeats.toarray()), axis=1)
          else:
              raise util_functions.InputError(self, "Dictionaries must be initialized prior to generating bag features.")
          return bag_feats.copy()
docs: Generates bag of words features from an input essay set and trained FeatureExtractor
          Generally called by gen_feats
          Returns an array of features
          e_set - EssaySet object