Predicting full spectrum when Modelling Spectroscopy + Photometry at the same time

[elmiio]

I am attempting to model some spectroscopic and photometric data using a simple stellar population model template. In the past, I have only done modelling where I had one or the other, but not both. I am wondering, is there a way to generate a MAP spectrum that spans the wavelengths of both the photometric and spectroscopic data at once? If this is not possible, is there then a way to generate a MAP spectrum that can be separately compared to the photometry and spectroscopy?

[bd-j]

Hi @elmiio the easiest way is to create a new 'empty' observation dictionary, and then ask for the model prediction with that data. By default if no spectrum is to be fit, the code will output the full model spectrum (similar to if you fit photometry only)

from prospect.utils.obsutils import rectify_obs
empty_obs = dict(wavelengths=None, spectrum=None, filters=None)
spec, phot, x = model.predict(theta_map, sps=sps, obs=obs)
fullspec, _, _ = model.predict(theta_map, sps=sps, obs=empty_obs)
ax.plot(sps.wavelengths * (1 + model.params["zred"]) , fullspec)

[elmiio]

I see. This seems to do exactly what I was looking for, thank you. Can I re-open this issue if I have any further questions?

[bd-j]

yes, please do re-open if there are further issues with this.

[YourVoicee]

Hello! I apologize if my question is obvious, but I wanted to join in and ask about the prediction of parameters (e.g., mass, metallicity) using both photometric and spectroscopic data. Is it possible to combine these two types of information to obtain more accurate estimates of the parameters, or will the parameters be determined only from the part of the spectrum that is used for the input?