Hi Stefan! PyData/Sparse is pretty far along, by January or so we should have a CSR/CSC replacement that is ND. It needs optimisation in a lot of cases but the API is compatible with NumPy and works pretty well already IMO.
PyData/Sparse is pretty much independent of any changes to scipy.sparse at this point. We build on top of NumPy, not scipy.sparse. Feel free to use any or all of my code for sparray, although I think Ralf Gommers, Matthew Rocklin and others were of the opinion that the data structure should stay in PyData/Sparse and linear algebra and csgraph etc should go into SciPy. Best Regards, Hameer Abbasi > On Friday, Oct 26, 2018 at 7:03 PM, Stefan van der Walt <stef...@berkeley.edu > (mailto:stef...@berkeley.edu)> wrote: > Hi Hameer, > > On Fri, 26 Oct 2018 10:47:09 +0200, Hameer Abbasi wrote: > > The only core functionality dependent on scipy.sparse is matrix > > multiplication and the like. Everything else is for inter-operability. > > Thank you for commenting here. > > As you know, I am enthusiastic about seeing an `sparray` equivalent to > `spmatrix`. When we last spoke, my recollection was that it would be > beneficial to `pydata/sparse`. Is this still correct? > > If not, are we now in a situation where it would be more helpful to > build `sparray` based on `pydata/sparse`. > > If we can have a good sparse array API in place in SciPy, it may > significantly simplify code in various other libraries (I'm thinking of > scikit-learn, e.g.). > > Best regards, > Stéfan > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion
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