[Numpy-discussion] Added atleast_nd, request for clarification/cleanup of atleast_3d

[Ralf Gommers]

On Wed, Jul 6, 2016 at 7:06 AM, Nathaniel Smith <njs at pobox.com> wrote:

On Jul 5, 2016 9:09 PM, "Joseph Fox-Rabinovitz" <jfoxrabinovitz at gmail.com>
> wrote:
> >
> > Hi,
> >
> > I have generalized np.atleast_1d, np.atleast_2d, np.atleast_3d with a
> > function np.atleast_nd in PR#7804
> > (https://github.com/numpy/numpy/pull/7804).
> >
> > As a result of this PR, I have a couple of questions about
> > `np.atleast_3d`. `np.atleast_3d` appears to do something weird with
> > the dimensions: If the input is 1D, it prepends and appends a size-1
> > dimension. If the input is 2D, it appends a size-1 dimension. This is
> > inconsistent with `np.atleast_2d`, which always prepends (as does
> > `np.atleast_nd`).
> >
> >   - Is there any reason for this behavior?
> >   - Can it be cleaned up (e.g., by reimplementing `np.atleast_3d` in
> > terms of `np.atleast_nd`, which is actually much simpler)? This would
> > be a slight API change since the output would not be exactly the same.
>
> Changing atleast_3d seems likely to break a bunch of stuff...
>
> Beyond that, I find it hard to have an opinion about the best design for
> these functions, because I don't think I've ever encountered a situation
> where they were actually what I wanted. I'm not a big fan of coercing
> dimensions in the first place, for the usual "refuse to guess" reasons. And
> then generally if I do want to coerce an array to another dimension, then I
> have some opinion about where the new dimensions should go, and/or I have
> some opinion about the minimum acceptable starting dimension, and/or I have
> a maximum dimension in mind. (E.g. "coerce 1d inputs into a column matrix;
> 0d or 3d inputs are an error" -- atleast_2d is zero-for-three on that
> requirements list.)
>
> I don't know how typical I am in this. But it does make me wonder if the
> atleast_* functions act as an attractive nuisance, where new users take
> their presence as an implicit recommendation that they are actually a
> useful thing to reach for, even though they... aren't that. And maybe we
> should be recommending folk move away from them rather than trying to
> extend them further?
>
> Or maybe they're totally useful and I'm just missing it. What's your use
> case that motivates atleast_nd?
>
I think you're just missing it:) atleast_1d/2d are used quite a bit in
Scipy and Statsmodels (those are the only ones I checked), and in the large
majority of cases it's the best thing to use there. There's a bunch of
atleast_2d calls with a transpose appended because the input needs to be
treated as columns instead of rows, but that's still efficient and readable
enough.

For 3D/nD I can see that you'd need more control over where the dimensions
go, but 1D/2D are fine.

Ralf
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