sk.py 文件源码

def _bootstraped():
  def worker(n=1000,
             mu1=10, sigma1=1,
             mu2=10.2, sigma2=1):
    def g(mu, sigma):
      return random.gauss(mu, sigma)
    x = [g(mu1, sigma1) for i in range(n)]
    y = [g(mu2, sigma2) for i in range(n)]
    return n, mu1, sigma1, mu2, sigma2, \
        'different' if bootstrap(x, y) else 'same'
  # very different means, same std
  print worker(mu1=10, sigma1=10,
               mu2=100, sigma2=10)
  # similar means and std
  print worker(mu1=10.1, sigma1=1,
               mu2=10.2, sigma2=1)
  # slightly different means, same std
  print worker(mu1=10.1, sigma1=1,
               mu2=10.8, sigma2=1)
  # different in mu eater by large std
  print worker(mu1=10.1, sigma1=10,
               mu2=10.8, sigma2=1)