code: def test_cosine_similarity_sentences_with_no_common_word_should_be_zero():
      """
      We compute similarity of the sentences without single common word.
      These are considered dissimilar so have similarity close to 0.0.
      see https://github.com/miso-belica/sumy/issues/58
      """
      sentence1 = ["this", "sentence", "is", "simple", "sentence"]
      tf1 = {
          "this": 1 / 2,
          "sentence": 1.0,
          "is": 1 / 2,
          "simple": 1 / 2,
      }
      sentence2 = ["that", "paragraph", "has", "some", "words"]
      tf2 = {
          "that": 1.0,
          "paragraph": 1.0,
          "has": 1.0,
          "some": 1.0,
          "words": 1.0,
      }
      idf = {
          "this": 2 / 1,
          "sentence": 2 / 1,
          "is": 2 / 1,
          "simple": 2 / 1,
          "that": 2 / 1,
          "paragraph": 2 / 1,
          "has": 2 / 1,
          "some": 2 / 1,
          "words": 2 / 1,
      }
  
      summarizer = LexRankSummarizer()
      cosine = summarizer.cosine_similarity(
          sentence1, sentence2, tf1, tf2, idf
      )
  
      assert abs(0.0 - cosine) < 0.00001
  
imports: from __future__ import absolute_import
  from __future__ import division, print_function, unicode_literals
  import math
  import numpy
  import pytest
  import sumy.summarizers.lex_rank
  from sumy.nlp.stemmers.czech import stem_word
  from sumy.nlp.tokenizers import Tokenizer
  from sumy.parsers.plaintext import PlaintextParser
  from sumy.summarizers.lex_rank import LexRankSummarizer
  from sumy.utils import get_stop_words
  from ..utils import build_document, load_resource
label_desc: Use image node_id 5 for calling a global function with example usage: test_cosine_similarity_sentences_with_no_common_word_should_be_zero() without return types