Sheshuk/fix model notebooks

[Sheshuk]

Closes #392 , #223

Trying to fix the remaining issues with building the notebooks:

• Errors in most PinchedModel-derived model classes, because the flux.Container failed to initialize with a scalar time (shape mismatch)
• Errors in Fornax_* models - caused by extra parameters interpolation, phi and theta. We need to discuss how to handle this in Make signature for SupernovaModel.get_*_spectra uniform for all models/subclasses #223
• Error in Fornax_2019 model: Fornax_2019 initial spectra unit is different from other models #403
• Errors in SNOwGLoBES_models nb - it needs updating, it uses path to already created tar.gz file.
• Errors in AnalyticFluence - it's incompatible with our ccsn_loaders.

Also, currently building the notebooks in the docs is not very informative: if one fails, we don't get any additional information. I'm adding a separate step, calling the pytest on notebooks, so we can see exctly which ones of them are failed, instead of exit on first failure.

[JostMigenda]

[ ] Errors in AnalyticFluence - it's incompatible with our ccsn_loaders.

In #404, @jpkneller suggested (among other things) moving that class from ccsn.py to base.py. So we could leave this particular issue for that PR and don’t have to deal with it here.

[JostMigenda]

From discussion in the telecon just now:

• Fornax_2019 requires more work to ensure units are correct, but that can happen outside of this PR here.
• The other open issues will be tackled by @jpkneller in separate PRs

So I think we can turn this one from draft into a reviewable PR?
If you agree, I’ll try to review it later this week and merge it. (I’ll try to look at the following PRs by Jim as well, but can’t promise I’ll get to that before next week’s conference.)

[JostMigenda]

Sorry for the delay! I didn’t get to this before the conference, then spent most of last week ill with some conference virus … 🤒

Aside from the separate discussion about nbsphinx_allow_errors above, I think there’s one more open issue here: In addition to the more exotic model notebooks, which we’ll leave for separate PRs, we also have FlavorTransformation.ipynb failing in the integration tests, with the following error:

TypeError                                 Traceback (most recent call last)
Cell In[6], line 1
----> 1 fig = plot_total_flux(model, AdiabaticMSW(MixingParameters()), AdiabaticMSW(MixingParameters('INVERTED')))
      2 fig.show()
      3 # fig.savefig('flux_adiabaticmsw.pdf')

Cell In[4], line 37
     35 for flavor in Flavor:
     36     for j, E in enumerate(energies):
---> 37         ispec[flavor][j] /= (4.*np.pi*d**2)
     38         ospec_nmo[flavor][j] /= (4.*np.pi*d**2)
     39         ospec_imo[flavor][j] /= (4.*np.pi*d**2)

TypeError: unsupported operand type(s) for /: 'd2NdEdT' and 'float'

This looks like it could be related to the container changes in this PR?

[jpkneller]

Sorry for the delay! I didn’t get to this before the conference, then spent most of last week ill with some conference virus … 🤒

Aside from the separate discussion about nbsphinx_allow_errors above, I think there’s one more open issue here: In addition to the more exotic model notebooks, which we’ll leave for separate PRs, we also have FlavorTransformation.ipynb failing in the integration tests, with the following error:

TypeError                                 Traceback (most recent call last)
Cell In[6], line 1
----> 1 fig = plot_total_flux(model, AdiabaticMSW(MixingParameters()), AdiabaticMSW(MixingParameters('INVERTED')))
      2 fig.show()
      3 # fig.savefig('flux_adiabaticmsw.pdf')

Cell In[4], line 37
     35 for flavor in Flavor:
     36     for j, E in enumerate(energies):
---> 37         ispec[flavor][j] /= (4.*np.pi*d**2)
     38         ospec_nmo[flavor][j] /= (4.*np.pi*d**2)
     39         ospec_imo[flavor][j] /= (4.*np.pi*d**2)

TypeError: unsupported operand type(s) for /: 'd2NdEdT' and 'float'

This looks like it could be related to the container changes in this PR?

This is an easy fix: look in #408. Change it to

ispec = model.get_flux(times, energies, d)
ospec_nmo = model.get_flux(times, energies, d, xform_nmo)
ospec_imo = model.get_flux(times, energies, d, xform_imo)

[JostMigenda]

Looks good to me now; many thanks!

Some of the unit test runs have failed due to what looks like a one-off network issue. I just re-started them and will merge this PR as soon as they turn green.