Closed dfm closed 7 years ago
Hi @dfm
Thanks for your useful comments. Several improvements have been made:
tutorials
folder to help new users get started.examples
folder have been briefly commented.requirements
file, so installation is as easy as pip install pyGPGO
Let me know if something else needs to be addressed.
This looks great! Two comments:
:class:`pyGPGO.surrogates.GaussianProcess `
instead of the <pyGPGO.surrogates.GaussianProcess>
that you're using now (e.g. http://pygpgo.readthedocs.io/en/latest/features.html#surrogate-models-pygpgo-surrogates)Hi @dfm !
Link to the documentation is now more visible in the repository, both in the header and in the README.md
file.
Internal documentation links are now fixed. Thanks for noticing.
Let me know again if further changes are required.
Looks great! One last issue with the links. I think that you're still using the markdown style for citations, but it would be good to switch to the correct RST syntax: http://docutils.sourceforge.net/docs/user/rst/quickref.html#citations
Thanks for noticing. The correct RST citation syntax is used in the docs.
Hi @dfm!
Is there something else that needs to be addressed or can I close this? :)
Oops. Nope. Looks good now!
I'm reviewing the JOSS submission at openjournals/joss-reviews#41 and most things are looking good, but I'll open a few issues here.
To be consistent with the JOSS requirements, the docs are going to need some work. At the moment, the documentation has a brief statement of need, a single example, and then API docs. More discussion should be included on the readthedocs page to make it easier to get started. This should include things like one or two tutorials (the
examples
directory is not sufficient - these examples don't even include any comments!), a page outlining the installation procedure, and a more detailed description of the available options.Another thing that might be good to include is a comparison to some of the other existing Bayesian optimization packages that are already available in Python: fmfn/BayesianOptimization, GPyOpt, and skopt to name a few.