On Mar 1, 2011, at 1:05 AM, Bruce Southey wrote: > On Mon, Feb 28, 2011 at 4:52 PM, Wes McKinney <wesmck...@gmail.com> 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 >> NumPy-Discussion@scipy.org >> 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 NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
