The function _get_ylim_for_best_model_plot() has a condition y_err < 0., but y_err there is scaled flux uncertainty. I think it can be negative only if either data_source_flux or source_flux in FitData.scale_fluxes() is negative. In that case we should probably:
add a warning in FitData.scale_fluxes() for negative output of flux uncertainty (because users don't expect that),
add a check in UlensModelFit._get_ylim_for_best_model_plot(): if np.sum(mask) == 0: continue; also handle above warning properly.
Jen - can you do the first change?
The function
_get_ylim_for_best_model_plot()has a conditiony_err < 0., buty_errthere is scaled flux uncertainty. I think it can be negative only if eitherdata_source_fluxorsource_fluxinFitData.scale_fluxes()is negative. In that case we should probably:FitData.scale_fluxes()for negative output of flux uncertainty (because users don't expect that),UlensModelFit._get_ylim_for_best_model_plot():if np.sum(mask) == 0: continue; also handle above warning properly. Jen - can you do the first change?