code: def fit_bristow_campbell_params(tmin, tmax, pot_rad_daily, obs_rad_daily):
      
      def bc_absbias(ac):
          return np.abs(np.mean(bristow_campbell(df.tmin, df.tmax, df.pot, ac[0], ac[1]) - df.obs))
  
      df = pd.DataFrame(data=dict(tmin=tmin, tmax=tmax, pot=pot_rad_daily, obs=obs_rad_daily)).dropna(how='any')
      res = scipy.optimize.minimize(bc_absbias, [0.75, 2.4])  # i.e. we minimize the absolute bias
  
      return res.x
docs: Fit the A and C parameters for the Bristow & Campbell (1984) model using observed daily
      minimum and maximum temperature and mean daily (e.g. aggregated from hourly values) solar
      radiation.
  
      Parameters
      ----------
      tmin : Series
          Observed daily minimum temperature.
  
      tmax : Series
          Observed daily maximum temperature.
  
      pot_rad_daily : Series
          Mean potential daily solar radiation.
  
      obs_rad_daily : Series
          Mean observed daily solar radiation.