On Tue, Aug 20, 2013 at 7:34 AM, Nathaniel Smith <[email protected]> wrote: > On 20 Aug 2013 12:09, <[email protected]> wrote: >> >> On Tue, Aug 20, 2013 at 5:04 AM, Nathaniel Smith <[email protected]> wrote: >> > On 20 Aug 2013 01:39, "Joe Kington" <[email protected]> wrote: >> >> >> >> >> >> >> >> >> >> ...<snip> >> >>> >> >>> >> >>> However, my first interpretation of an axis argument in unique would >> >>> be that it treats each column (or whatever along axis) separately. >> >>> Analogously to max, argmax and similar. >> >> >> >> >> >> Good point! >> >> >> >> That's certainly a potential source of confusion. However, I can't >> >> seem >> >> to come up with a better name for the kwarg. Matlab's "unique" function >> >> has >> >> a "rows" option, which is probably a more intuitive name, but doesn't >> >> imply >> >> the expansion to N-dimensions. >> >> >> >> "axis" is still fairly idiomatic, despite the confusion over "unique >> >> rows/columns/etc" vs "unique items within each row/column/etc". >> >> >> >> Any thoughts on a better name for the argument? >> > >> > I also found this pretty confusing when first looking at the PR. >> > >> > One option might be to invert the sense of the argument to emphasize >> > that >> > it's treating subarrays as units, so instead of specifying the iteration >> > axis you specify the axes of the subarray. compare_axis= or something? >> >> you would need compare_axes (plural for ndim>2) and have to specify >> all but one axis, AFAICS. > > Well, it makes sense to specify any arbitrary subset of axes, whether or not > that's currently implemented.
not AFAICS, if you want to return a rectangular array without nans/missing values. Josef > > -n > > > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
