input: Write a function to analyze the sentiment of a given text using tokenization, stemming, and polarity scoring. The function should return the sentiment polarity score.
  
  assert sentiment_analyzer("This is a great day!")=={'neg': 0.0, 'neu': 0.318, 'pos': 0.682, 'compound': 0.7579}
  assert sentiment_analyzer("I am feeling extremely bad.")=={'neg': 0.669, 'neu': 0.331, 'pos': 0.0, 'compound': -0.7184}
  assert sentiment_analyzer("The movie was okay.")=={'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0}
  assert sentiment_analyzer("What a wonderful experience!")=={'neg': 0.0, 'neu': 0.323, 'pos': 0.677, 'compound': 0.8858}
  assert sentiment_analyzer("")=={'neg': 0.0, 'neu': 0.0, 'pos': 0.0, 'compound': 0.0}
output: from nltk.sentiment import SentimentIntensityAnalyzer
  
  def sentiment_analyzer(text):
      sia = SentimentIntensityAnalyzer()
      return sia.polarity_scores(text)