code: def logL(self, kwargs_lens, kwargs_ps, kwargs_cosmo):
          
          x_pos, y_pos = self._pointSource.image_position(kwargs_ps=kwargs_ps, kwargs_lens=kwargs_lens)
          x_pos, y_pos = self._param.real_image_positions(x_pos[0], y_pos[0], kwargs_cosmo)
          x_source, y_source = self._lensModel.ray_shooting(x_pos, y_pos, kwargs_lens)
          delay_arcsec = self._lensModel.fermat_potential(x_pos, y_pos, x_source, y_source, kwargs_lens)
          D_dt_model = kwargs_cosmo['D_dt']
          delay_days = const.delay_arcsec2days(delay_arcsec, D_dt_model)
          logL = self._logL_delays(delay_days, self._delays_measured, self._delays_errors)
          return logL
docs: routine to compute the log likelihood of the time delay distance
          :param kwargs_lens: lens model kwargs list
          :param kwargs_ps: point source kwargs list
          :param kwargs_cosmo: cosmology and other kwargs
          :return: log likelihood of the model given the time delay data