code: def predict_without_uncertainties(self, mjd, complain=True):
          
          import sys
  
          self.verify(complain=complain)
  
          planets, ts = load_skyfield_data() # might download stuff from the internet
          earth = planets['earth']
          t = ts.tdb(jd = mjd + 2400000.5)
  
          # "Best" position. The implementation here is a bit weird to keep
          # parallelism with predict().
  
          args = {
              'ra_hours': self.ra * R2H,
              'dec_degrees': self.dec * R2D,
          }
  
          if self.pos_epoch is not None:
              args['jd_of_position'] = self.pos_epoch + 2400000.5
  
          if self.promo_ra is not None:
              args['ra_mas_per_year'] = self.promo_ra
              args['dec_mas_per_year'] = self.promo_dec
          if self.parallax is not None:
              args['parallax_mas'] = self.parallax
          if self.vradial is not None:
              args['radial_km_per_s'] = self.vradial
  
          bestra, bestdec, _ = earth.at(t).observe(PromoEpochStar(**args)).radec()
          return bestra.radians, bestdec.radians
docs: Predict the object position at a given MJD.
  
          The return value is a tuple ``(ra, dec)``, in radians, giving the
          predicted position of the object at *mjd*. Unlike :meth:`predict`, the
          astrometric uncertainties are ignored. This function is therefore
          deterministic but potentially misleading.
  
          If *complain* is True, print out warnings for incomplete information.
  
          This function relies on the external :mod:`skyfield` package.