On Fri, Oct 19, 2018 at 10:28 PM Ralf Gommers <ralf.gomm...@gmail.com> wrote:
> > > On Fri, Oct 19, 2018 at 4:15 PM Hameer Abbasi <einstein.edi...@gmail.com> > wrote: > >> Hi! >> >> On Friday, Oct 19, 2018 at 6:09 PM, Stephan Hoyer <sho...@gmail.com> >> wrote: >> I don't think it makes much sense to change NumPy's existing usage of >> asarray() to asanyarray() unless we add subok=True arguments (which default >> to False). But this ends up cluttering NumPy's public API, which is also >> undesirable. >> >> Agreed so far. >> > > I'm not sure I agree. "subok" is very unpythonic; the average numpy > library function should work fine for a well-behaved subclass (i.e. most > things out there except np.matrix). > >> >> The preferred way to override NumPy functions going forward should be >> __array_function__. >> >> >> I think we should “soft support” i.e. allow but consider unsupported, the >> case where one of NumPy’s functions is implemented in terms of others and >> “passing through” an array results in the correct behaviour for that array. >> > > I don't think we have or want such a concept as "soft support". We intend > to not break anything that now has asanyarray, i.e. it's supported and > ideally we have regression tests for all such functions. For anything we > transition over from asarray to asanyarray, PRs should come with new tests. > > >> >> On Fri, Oct 19, 2018 at 8:13 AM Marten van Kerkwijk < >> m.h.vankerkw...@gmail.com> wrote: >> >>> There are exceptions for `matrix` in quite a few places, and there now >>> is warning for `maxtrix` - it might not be bad to use `asanyarray` and add >>> an exception for `maxtrix`. Indeed, I quite like the suggestion by Eric >>> Wieser to just add the exception to `asanyarray` itself - that way when >>> matrix is truly deprecated, it will be a very easy change. >>> >> I don't quite understand this. Adding exceptions is not deprecation - we > then may as well just rip np.matrix out straight away. > > What I suggested in the call about this issue is that it's not very > effective to treat functions like percentile/quantile one by one without an > overarching strategy. A way forward could be for someone to write an > overview of which sets of functions now have asanyarray (and actually work > with subclasses), which ones we can and want to change now, and which ones > we can and want to change after np.matrix is gone. Also, some guidelines > for new functions that we add to numpy would be handy. I suspect we've been > adding new functions that use asarray rather than asanyarray, which is > probably undesired. > Thanks Nathaniel and Stephan. Your comments on my other two points are both clear and correct (and have been made a number of times before). I think the "write an overview so we can stop making ad-hoc decisions and having these discussions" is the most important point I was trying to make though. If we had such a doc and it concluded "hence we don't change anything, __array_function__ is the only way to go" then we can just close PRs like https://github.com/numpy/numpy/pull/11162 straight away. Cheers, Ralf
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