docs: def get_ngram_counts(self):
          ''' Returns a list of n-gram counts
              Array of classes counts and last item is for corpus
          '''
          ngram_counts = {
              'classes': [],
              'corpus': 0
          }
          doc_ids = self.term_count_n.keys()
          doc_ids.sort()
          for doc_id in doc_ids:
              print self.term_count_n[doc_id]
              class_ngrams = len(self.term_count_n[doc_id]['ngrams'])
              ngram_counts['classes'].append(class_ngrams)
          corpus_ngrams = len(self.corpus_count_n['ngrams'])
          ngram_counts['corpus'] = corpus_ngrams
          return ngram_counts