How would the community handle the scipy.sparse matrix subclasses? These
are still in common use.
Somewhat related: https://github.com/scipy/scipy/issues/8162
On Thu, Nov 30, 2017 at 1:13 PM,
On Thu, Nov 30, 2017 at 9:23 AM, Marten van Kerkwijk < m.h.vankerkwijk@gmail.com> wrote:
Hi All,
I wondered if the move to python3-only starting with numpy 1.17 would be a good reason to act on what we all seem to agree: that the matrix class was a bad idea, with its overriding of multiplication and lack of support for stacks of matrices.
I don't think the matrix class was a bad idea at the time.
numpy was the underdog, I came from GAUSS and Matlab and numpy arrays were just weird, especially loosing a dimension all the time and the heavy required use of np.newaxis. I guess nowadays kids don't learn `matrix` languages first anymore.
recarrays are another half-hearted feature in numpy that is mostly obsolete with pandas and pandas_like DataFrames in other packages.
(I don't mind the changes, but the deprecation cycle is often short, especially for users like me that update numpy only about every 3 main versions.)
Josef
For 1.17, minimum python supposedly is >=3.5, so we will be guaranteed to have the matrix multiply operator @ available, and hence there is arguably even less of a case for keeping the matrix class; removing it would allow taking out quite a bit of accumulated special-casing (the immediate reasons for writing this were gh-10123 and 10132).
What do people think? If we do go in this direction, we might want to add PendingDeprecationWarning for 1.15 (maybe DeprecationWarning for python3; for python2 matrix would never disappear).
All the best,
Marten _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
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