input: Write a python function to analyze sentiment of a given text using nltk's SentimentIntensityAnalyzer.
  assert sentiment_calculator('I love this product!') == 'positive'
  assert sentiment_calculator('This is the worst service ever.') == 'negative'
  assert sentiment_calculator('The movie was okay, not great but not terrible.') == 'neutral'
output: def sentiment_calculator(text):
      from nltk.sentiment import SentimentIntensityAnalyzer
      sia = SentimentIntensityAnalyzer()
      sentiment = sia.polarity_scores(text)
      
      if sentiment['compound'] >= 0.05:
          return 'positive'
      elif sentiment['compound'] <= -0.05:
          return 'negative'
      else:
          return 'neutral'