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). -Travis _______________________________________________ Numpy-discussion mailing list [email protected] http://projects.scipy.org/mailman/listinfo/numpy-discussion
