Closed sybenzvi closed 8 months ago
Thanks for working on this!
Initial comments:
I’m currently at NNN, but will try to take a closer look at this once I’m back.
Thanks @JostMigenda , I am pretty swamped the next two days but it shouldn't be hard to complete the tests and checks you requested.
@JostMigenda , in reply to your suggestions:
filename
argument and deprecation warnings: done.fornax-2022-data
branch of the snewpy-models-ccsn repo and everything looks reasonable.For example, here is luminosity vs. time for 5 models:
And here are corresponding energy spectra:
After the comments by Jost implemented, my only comment is that all other models have a jupyer notebook with an example on how to initialise and use the model, which is missing for Fornax_2022 now. However, as we are going to avoid having the model data in snewpy/models (where the notebooks are) as of now, I am not sure it is really needed.
@mcolomermolla , I actually put the demo notebook in the new snewpy-models-ccsn project that we're using to store the model files.
We can and probably should have all the notebooks moved out of that project and the corresponding deprecated models folder in this project, but I'd like to keep that issue separate from this PR.
After the comments by Jost implemented, my only comment is that all other models have a jupyer notebook with an example on how to initialise and use the model, which is missing for Fornax_2022 now. However, as we are going to avoid having the model data in snewpy/models (where the notebooks are) as of now, I am not sure it is really needed.
@mcolomermolla , I actually put the demo notebook in the new snewpy-models-ccsn project that we're using to store the model files.
We can and probably should have all the notebooks moved out of that project and the corresponding deprecated models folder in this project, but I'd like to keep that issue separate from this PR.
I agree, we can move all data files and the corresponding notebooks there. Then, I see no stop point to merge this PR!
New model class and loader for the 100 axisymmetric (2D) simulations produced by the Princeton group using the Fornax code. Includes a notebook that tests I/O for the models.
The model data live in the fornax-2022-data branch of snewpy-models-ccsn.