A Friday 06 February 2009, Travis Oliphant escrigué: > Pierre GM wrote: > > On Feb 5, 2009, at 6:08 PM, Travis E. Oliphant wrote: > >> Hi all, > >> > >> I've been fairly quiet on this list for awhile due to work and > >> family schedule, but I think about how things can improve > >> regularly. One feature that's been requested by a few people is > >> the ability to select multiple fields from a structured array. > >> > >> > >> > >> [...] > > > > +1 for #2. > > > > Note that we now have a drop_fields function in > > np.lib.recfunctions, a reimplementation of the equivalent function > > in matplotlib. It works along the lines of your proposition #1 > > (create a new array w/ a new dtype and fill it) > > After more thought, I think I was too eager in my suggestion of #2. > It's actually not really possible to do a view the way I would want > it to work. It would be possible to create a data-type with > hidden-fields, but a copy would be not "get rid of the extra data". > > Thus newarr = arr[['name', 'age']].copy() would be exactly the same > size as arr because elements are copied wholesale and each "row" is > a single element in the NumPy array. Some infrastructure would > have to be implemented at a fundamental level to handle > partial-element manipulation similar at least in spirit to what is > needed to handle bit-level striding on a fundamental level. > > Also, I don't remember if we resolved how hidden fields would be > shown in the array interface. > > So, I think that we may be stuck with #1 which at least is consistent > with the "fancy-indexing" is a copy pattern (and is just syntatic > sugar for capability you've already implemented in recfunctions).
Mmh, I'd also vote for #2 for performance reasons, but as the implementation seems quite involved, I suppose that #1 would be great too. Cheers, -- Francesc Alted _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
