code: def test_normalized_words_frequencies():
      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") == pytest.approx(
          1 / 5
      )
      assert model.normalized_term_frequency("b") == pytest.approx(
          2 / 5
      )
      assert model.normalized_term_frequency("c") == pytest.approx(
          3 / 5
      )
      assert model.normalized_term_frequency("d") == pytest.approx(
          4 / 5
      )
      assert model.normalized_term_frequency("e") == pytest.approx(
          5 / 5
      )
      assert model.normalized_term_frequency("z") == pytest.approx(0.0)
  
      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 10 for calling a global function with example usage: test_normalized_words_frequencies() without return types