code: def mu_score(y, loc, scale, shape):
      try:
          return (
              ((shape + 1.0) * power(y - loc, 2))
              / float(shape * exp(scale) + power(y - loc, 2))
          ) - 1.0
      except:
          return -1.0
  
imports: from numpy import abs, exp, power, array, sqrt, pi
  from scipy.special import gamma
label_desc: Use image node_id 2 for calling the BetatScore obj's underlying member method code with example usage: obj.mu_score(y, loc, scale, shape) and returns: unknown, unknown