composite models with degeneracy fail to expose uncertainties

[Jdaviz-Triage-Bot]

Reporter: Kyle Conroy

running a model on linear+polynomial does run and expose values, but does not expose uncertainties.  Should this combination (and other combinations of constant, linear, polynomial of various orders) even be allowed?  If so, we should at least expose a warning as its confusing as a user that uncertainties suddenly disappear.

script to reproduce:

from jdaviz import Specviz
specviz = Specviz(verbosity='error', history_verbosity='debug')

import tempfile
from astroquery.mast import Observations
data_dir = tempfile.gettempdir()
fn = "jw02732-o004_t004_miri_ch1-shortmediumlong_x1d.fits"
result = Observations.download_file(f"mast:JWST/product/\{fn}", local_path=f'\{data_dir}/\{fn}')
specviz.load_spectrum(f'\{data_dir}/\{fn}', "myfile")

specviz.get_data('myfile').uncertainty # are populated and non-zero

mf = specviz.plugins['Model Fitting']

mf.create_model_component('Linear1D')
mf.create_model_component('Polynomial1D')
model = mf.calculate_fit(add_data=True)

specviz.get_models()['model'].stds # is None

---

DISCLAIMER: This issue was autocreated by the Jdaviz Issue Creation Bot on behalf of the reporter. If any information is incorrect, please contact Duy Nguyen

[pllim]

specviz.get_models()['model'].stds. -> specviz.get_models()['model'].stds?

[kecnry]

that's just jira auto-formatting being annoying, fixed in the description, thanks