# [Numpy-discussion] Accessing rank-0 array value?

Todd Miller jmiller at stsci.edu
Mon Jun 7 09:05:04 CDT 2004

```On Mon, 2004-06-07 at 11:51, Colin J. Williams wrote:
> Todd,
>
> What are the objections to returning a scalar?

Where?

> To me, this seems to be
> simpler than some kluge, such as float(array) or int(array).  To use
> these, one has first to determine what array._type is.

I don't think so.  What you get is driven by what you ask for, not the
type of the array:

>>> a = numarray.array(10)
>>> float(a)
10.0
>>> int(a)
10
>>> a = numarray.array(10.0)
>>> int(a)
10
>>> float(a)
10.0
>>> complex(a)
(10+0j)

Regards,
Todd

> Colin W.
>
> Todd Miller wrote:
>
> >On Mon, 2004-06-07 at 06:50, Nadav Horesh wrote:
> >
> >
> >>b has a scalar properties:
> >>
> >>
> >>
> >>>>>b+3
> >>>>>
> >>>>>
> >>5
> >>
> >>
> >>
> >>>>>b.rank
> >>>>>
> >>>>>
> >>0
> >>
> >>The odd issue is that rank>0 arrays keeps their type in similar operations:
> >>
> >>
> >>
> >>>>>a = array((2,), type=Int16)
> >>>>>a
> >>>>>
> >>>>>
> >>array([2], type=Int16)
> >>
> >>
> >>
> >>>>>a + 3
> >>>>>
> >>>>>
> >>array([5], type=Int16)
> >>
> >>I would expect that rank 0 arrays would behave like scalars with a given numarray type (Int8, UInt64, ...).
> >>
> >>  Nadav.
> >>
> >>
> >
> >Originally, I think your expected behavior was the behavior.  The
> >official policy now, always subject to debate, is that rank-0 arrays
> >should be a mostly hidden implementation detail.  The fact that a scalar
> >is returned here is a matter of consistency and no accident.  (This is
> >not to say that I'm confident that we're completely consistent... I'm
> >just trying to explain the direction we're heading.)
> >
> >Todd
> >
> >
> >
--
Todd Miller <jmiller at stsci.edu>

```

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