On Tue, Mar 1, 2011 at 8:51 AM, Wes McKinney <[email protected]> wrote:

> On Mon, Feb 28, 2011 at 10:52 PM, Wes McKinney <[email protected]>
> wrote:
> > On Mon, Feb 28, 2011 at 7:24 PM, Pierre GM <[email protected]> wrote:
> >>
> >> On Mar 1, 2011, at 1:05 AM, Bruce Southey wrote:
> >>
> >>> On Mon, Feb 28, 2011 at 4:52 PM, Wes McKinney <[email protected]>
> wrote:
> >>>> I'm having some trouble with the zeros_like function via np.fix:
> >>>>
> >>>> def zeros_like(a):
> >>>>    if isinstance(a, ndarray):
> >>>>        res = ndarray.__new__(type(a), a.shape, a.dtype,
> order=a.flags.fnc)
> >>>>        res.fill(0)
> >>>>        return res
> >>>>    try:
> >>>>        wrap = a.__array_wrap__
> >>>>    except AttributeError:
> >>>>        wrap = None
> >>>>    a = asarray(a)
> >>>>    res = zeros(a.shape, a.dtype)
> >>>>    if wrap:
> >>>>        res = wrap(res)
> >>>>    return res
> >>>>
> >>>> As you can see this is going to discard any metadata stored in a
> >>>> subtype. I'm not sure whether this is a bug or a feature but wanted to
> >>>> bring it up.
> >>>>
> >>>> Thanks,
> >>>> Wes
> >>>> _______________________________________________
> >>>> NumPy-Discussion mailing list
> >>>> [email protected]
> >>>> http://mail.scipy.org/mailman/listinfo/numpy-discussion
> >>>>
> >>>
> >>> I guess this is ticket 929.
> >>> http://projects.scipy.org/numpy/ticket/929
> >>>
> >>> I was looking at it today but was not sure what is really desired
> >>> here. I considered that this just meant shape and dtype but not sure
> >>> about masked or record arrays behavior. So:
> >>> What is the value of having the metadata?
> >>> What is the meaning of 'like' here?
> >>
> >> Well, that depends on what you wanna do, of course. To handle metadata,
> I use some kind of dictionary updated in the __array_finalize__. Check
> numpy.ma.MaskedArray and its subclasses (like scikits.timeseries.TimeSeries)
> for the details.
> >> Now that you could store some extra data in the dtype (if I remmbr and
> understand correctly), it might be worth considering a proper way to deal
> with that.
> >>
> >>
> >> _______________________________________________
> >> NumPy-Discussion mailing list
> >> [email protected]
> >> http://mail.scipy.org/mailman/listinfo/numpy-discussion
> >>
> >
> > The ticket is exactly related to the problem at hand-- having
> > __array_finalize__ defined won't help you as it never gets called.
> >
>
> Looks like this commit fixed the problem, so the ticket can be closed
>
>
> https://github.com/numpy/numpy/commit/c9d1849332ae5bf73299ea1268f6a55f78624688#numpy/core/numeric.py
> ______
>

I've closed the ticket.

Chuck
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