code: def test_normalized_words_frequencies_with_smoothing_term():
      words = "a b c d e c b d c e e d e d e".split()
      model = TfDocumentModel(tuple(words))
  
      assert model.normalized_term_frequency("a", 0.5) == pytest.approx(
          0.5 + 1 / 10
      )
      assert model.normalized_term_frequency("b", 0.5) == pytest.approx(
          0.5 + 2 / 10
      )
      assert model.normalized_term_frequency("c", 0.5) == pytest.approx(
          0.5 + 3 / 10
      )
      assert model.normalized_term_frequency("d", 0.5) == pytest.approx(
          0.5 + 4 / 10
      )
      assert model.normalized_term_frequency("e", 0.5) == pytest.approx(
          0.5 + 5 / 10
      )
      assert model.normalized_term_frequency("z", 0.5) == pytest.approx(
          0.5
      )
  
      assert model.most_frequent_terms() == ("e", "d", "c", "b", "a")
  
file_path: sumy/tests/test_models/test_tf.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import pytest
  from sumy.models import TfDocumentModel
  from sumy.nlp.tokenizers import Tokenizer
label_desc: Use image node_id 11 for calling a global function with example usage: test_normalized_words_frequencies_with_smoothing_term() without return types