Initialize the fitter with a least-squares guess for the calibration function(s)

[gbrammer]

• Figure out how the bagpipes calibration polynomial is defined and do an initial least-squares fit for the coefficients, assuming a continuum model that is itself a fairly flexible polynomial. Since you already know the redshift, you can use the msaexp.spectrum.make_templates function to generate polynomial continuum + emission line templates that you then fit to the spectrum and photometry.

• Perhaps also derive a best guess / prior for the "noise" uncertainty scaling with calc_uncertainty_scale.

[gbrammer]

Or actually you don't need any templates at all: just integrate the spectrum through the filter bandpasses and fit the calibration polynomial to the ratio phot_flux / spec_filter_flux.