[MRG] flake8 + pimp example figures by agramfort · Pull Request #13 · PythonOT/POT
full flake8 valid is awesome !
:)
you did no change all pl to plt, probably because we did no concrge with
@ncourty. Sp we need to do it quickly I suppose. yes I used pl so you're still in your confort zone :)
Regarding your remarks: CG here stands for conditional gradient and not conjugate gradient as
implemented in scipy. arfff good point. What it tells you is that cg is probably not explicit enough. Maybe conditional_gradient is not that long to type :)
OK for switch to make but all examples and notebooks have to be updated
also. arfff. But I thought you were using sphinx-gallery. WIth sphinx-gallery you should not ship notebooks. They are produced when you build the doc.
Example do not have a proper description yet and I agree we need to
complete it with
I always thought this choice (params in init) in sklearn was weird since
it make it more complicated to perform warm start with a slightly different regularization (in a reg path for instance) value which is common practice in ML. for this we use the warm_start parameter clf = Classifier(..., warm_start=True) clf.fit(X, y) clf.set_param(C=C_new) # or just clf.C = C_new clf.fit(X, y)
I'm sure you have good reasons for it though. my problem here is that it
breaks the code for people who already use the toolbox and I'd like to keep the young and still small community.. Maybe do both for a while with a Deprecated Warning? yes you need deprecation cycles. But the earlier you do it the better. If it's too painful just deprecate a full class and create a new one with a better name.
I agree we should stick to Camel or snake but i personally prefer snake
and most of the toolbox is in snake, do you suggest the change for Classes only?, is it a common thing to do ? it's not a matter of preference but conventions :) yes you should use CamelCase for classes and snake_case for functions and methods.
I agree that the choice for cudamat is probably not the best. We were
planing with Nico to switch to a more future proof code with pycuda. pycuda is old and not that maintained anymore. cupy is much more used these days and more actively maintained.
I'll work on the test next week when I don't have NIPS review to write.
:)