code: def _compute_mean(self, C, mag, rjb):
          
          d1 = np.sqrt(50. ** 2 + 6. ** 2)
          d = np.sqrt(rjb ** 2 + 6 ** 2)
  
          mean = np.zeros_like(rjb)
  
          mean += (
              C['a1'] + C['a2'] * (mag - 6.4) +
              C['a7'] * (8.5 - mag) ** 2
          )
  
          idx = rjb < 50.
          mean[idx] += (
              C['a3'] * np.log(d[idx]) +
              C['a4'] * (mag - 6.4) * np.log(d[idx]) +
              C['a5'] * rjb[idx]
          )
  
          idx = rjb >=50.
          mean[idx] += (
              C['a3'] * np.log(d1) +
              C['a4'] * (mag - 6.4) * np.log(d[idx]) +
              C['a5'] * rjb[idx] + C['a6'] * (np.log(d[idx]) - np.log(d1))
          )
  
          return mean
docs: Compute and return mean value (table 8, page 8)