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? Bruce _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
