On Sat, Nov 10, 2018 at 2:22 PM Hameer Abbasi <einstein.edi...@gmail.com> wrote:
> To summarize, I think these are our options: > > 1. Change the behavior of np.anyarray() to check for an __anyarray__() > protocol. Change np.matrix.__anyarray__() to return a base numpy array > (this is a minor backwards compatibility break, but probably for the best). > Start issuing a FutureWarning for any MaskedArray operations that violate > Liskov and add a skipna argument that in the future will default to > skipna=False. > > 2. Introduce a new coercion function, e.g., np.duckarray(). This is the > easiest option because we don't need to cleanup NumPy's existing ndarray > subclasses. > > > My vote is still for 1. I don’t have an issue for PyData/Sparse depending > on recent-ish NumPy versions — It’ll need a lot of the recent protocols > anyway, although I could be convinced otherwise if major package devs > (scikits, SciPy, Dask) were to weigh in and say they’ll jump on it (which > seems unlikely given SciPy’s policy to support old NumPy versions). > I agree that option (1) is fine for PyData/sparse. The bigger issue is that this change should be conditional on making breaking changes (at least raising FutureWarning for now) to np.ma.MaskedArray. I don't know how people who currently use MaskedArray would feel about that. I would love to hear their thoughts.
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