You might also want to consider writing a wrapper object that contains an ndarray as a (possibly private) attribute and then presents different views or interpretations of that array.
Subclassing ndarray is a pit of snakes, it's best to avoid it if you can (I say as the author and maintainer of an ndarray subclass). On Tue, Nov 15, 2016 at 1:48 PM, Marten van Kerkwijk < m.h.vankerkw...@gmail.com> wrote: > Hi Stuart, > > It certainly seems correct behaviour to return the subclass you > created: after all, you might want to keep the information on > `columns` (e.g., consider doing nanmin along a given axis). Indeed, we > certainly want to keep the unit in astropy's Quantity (which also is a > subclass of ndarray). > > On the shape: shouldn't that be print(np.nanmin(r).shape)?? > > Overall, I think it is worth considering very carefully what exactly > you try to accomplish; if different elements along a given axis have > different meaning, I'm not sure it makes all that much sense to treat > them as a single array (e.g., np.sin might be useful for one column, > not not another). Even if pandas is slower, the advantage in clarity > of what is happening might well be more important in the long run. > > All the best, > > Marten > > p.s. nanmin is not a ufunc; you can find it in numpy/lib/nan_functions.py > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion >
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