[Numpy-discussion] Different attributes for NumPy types
Travis E. Oliphant
Thu May 22 19:38:10 CDT 2008
Charles R Harris wrote:
> On Thu, May 22, 2008 at 5:07 PM, Robert Kern <email@example.com
> <mailto:firstname.lastname@example.org>> wrote:
> On Thu, May 22, 2008 at 4:25 PM, Bruce Southey <email@example.com
> <mailto:firstname.lastname@example.org>> wrote:
> > On Thu, May 22, 2008 at 2:59 PM, Robert Kern
> <email@example.com <mailto:firstname.lastname@example.org>> wrote:
> >> On Thu, May 22, 2008 at 2:46 PM, Charles R Harris
> >> <email@example.com <mailto:firstname.lastname@example.org>>
> >>> It also leads to various inconsistencies:
> >>> In : float32(array([]))
> >>> Out: array([[ 1.]], dtype=float32)
> >>> In : float64(array([]))
> >>> Out: 1.0
> >> Okay, so don't do that. Always use x.astype(dtype) or
> asarray(x, dtype).
> > So, should these return an error if the argument is an ndarray
> > a list or similar?
> I think it was originally put in as a feature, but given the
> inconsistency and the long-standing alternatives, I would deprecate
> its use for converting array dtypes. But that's just my opinion.
> I agree. Having too many ways to do things just makes for headaches.
> Should we schedule in a deprecation for anything other than scalars
> and strings.
I don't have a strong opinion either way.
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