input: Write a function to determine whether a given sentence is an 'affirmative' sentence or a 'negative' sentence by checking for negation words. The function should use NLTK to tokenize the sentence and look for negation words in a predefined list. If the sentence contains any negation word, it should return "Negative", otherwise "Affirmative".
  assert isAffirmativeorNegative("He always comes late but I don't mind.") == "Negative"
  assert isAffirmativeorNegative("I am happy today.") == "Affirmative"
  assert isAffirmativeorNegative("Nobody is here.") == "Negative"
  assert isAffirmativeorNegative("I have no idea.") == "Negative"
  assert isAffirmativeorNegative("Everyone is here.") == "Affirmative"
output: def isAffirmativeorNegative(sentence):
      negation_words = ["not", "no", "never", "none", "nobody", "nothing", "neither", "nowhere", "hardly", "scarcely", "barely", "don't", "doesn't", "didn't", "isn't", "aren't", "wasn't", "weren't", "can't", "couldn't", "shouldn't", "wouldn't", "won't", "shan't"]
      tokens = nltk.word_tokenize(sentence.lower())
      for word in tokens:
          if word in negation_words:
              return "Negative"
      return "Affirmative"