[Numpy-discussion] numpy scalars and savez -- bug?

Sebastian Berg sebastian@sipsolutions....
Fri Apr 19 11:10:17 CDT 2013


On Fri, 2013-04-19 at 08:03 -0700, Chris Barker - NOAA Federal wrote:
> On Apr 18, 2013, at 11:33 PM, Nathaniel Smith <njs@pobox.com> wrote:
> 
> 
> 
> > On 18 Apr 2013 01:29, "Chris Barker - NOAA Federal"
> > <chris.barker@noaa.gov> wrote:
> > > This has been annoying, particular as rank-zero scalars are kind
> > of a pain.
> > 
> > BTW, while we're on the topic, can you elaborate on this? I tend to
> > think scalars (as opposed to 0d ndarrays) are kind of a pain, so I'm
> > curious if you have specific issues you've run into with 0d
> > ndarrays.
> > 
> > 
> Well, I suppose what's really a pain is that we have both, and they
> are not the same, and neither can be used in all cases one may want.
> 
> 
> In the case at hand, I really wanted a datetime64 scalar. By saving
> and re-loading in an npz, it got converted to a rank-zero array, which
> had different behavior. In this case, the frustrating bit was how to
> extract a scalar again ( which I really wanted to turn into a datetime
> object).
> 
> 
> After the fact, I discovered .item(), which seems to do what I want.
> 
Fun fact, array[()] will convert a 0-d array to a scalar, but do nothing
(or currently create a view) for other arrays. Which is actually a good
question. Should array[()] force a view or not?

- Sebastian
> 
> On a phone now, so sorry about the lack of examples.
> 
> 
> Note: I've lost track of why we need both scalers and rank-zero
> arrays. I can't help thinking that there could be an object that acts
> like a scalar in most contexts, but also has the array methods that
> make sense.
> 
> 
> But I know it's far from simple.
> 
> 
> -Chris 
> 
> 
> 
> 
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