code: def predict(self, a, b, sig=[-1, -1], maxpnt=500):
          
          a = (a - np.mean(a)) / np.std(a)
          b = (b - np.mean(b)) / np.std(b)
  
          return FastHsicTestGamma(a, b, sig, maxpnt)
docs: Compute the test statistic
  
          Args:
              a (array-like): Variable 1
              b (array-like): Variable 2
              sig (list): [0] (resp [1]) is kernel size for a(resp b) (set to median distance if -1)
              maxpnt (int): maximum number of points used, for computational time
  
          Returns:
              float: test statistic