Closed RoyStegeman closed 2 years ago
I'm wondering if we should first invert the covmat before splitting it (pretty sure that's what's done in n3fit)
Also, the chi2 is calculated per experiment during the fit. This is the thing I pointed out in the other PR, but then thought that I was wrong because it looked like you were dividing by the total number of point in all datasets (you're not though)
We should also decide whether we want to use callbacks or your for
loop. I'm happy with either, but if we go with the latter callbacks.py
can be removed.
We should also decide whether we want to use callbacks or your
for
loop. I'm happy with either, but if we go with the lattercallbacks.py
can be removed.
I am also happy with both. But maybe for the flexibility in presenting the output logs we can lean towards the for loo
approach? We can just write a nice function that controls the stopping.
I am also happy with both. But maybe for the flexibility in presenting the output logs we can lean towards the for loo approach? We can just write a nice function that controls the stopping.
Yes I agree. As long as there's as little functionality added as we have now I think the for
loop is more readable. Feel free to remove the callbacks.
@Radonirinaunimi I think everything is here now, right? Shall I review and then we can merge? Other smaller updates we can do in separate PRs.
@Radonirinaunimi I think everything is here now, right? Shall I review and then we can merge? Other smaller updates we can do in separate PRs.
Yes! We definitely should, I was exactly thinking about asking you this. Sot, let's merge this PR.
Okay, I followed your commits one-by-one, but allow me a little time to go over it in detail again.
@Radonirinaunimi can I run black
and merge?
@Radonirinaunimi can I run
black
and merge?
Yes, please do so! (I already ran black
before but there are indeed surely parts that I missed)
This builds on #10. It adds early stopping, saving of the model and merges updates to main.