On Wed, 2018-11-14 at 14:46 -0800, Stephan Hoyer wrote: > > > On Wed, Nov 14, 2018 at 2:35 PM Sebastian Berg < > sebast...@sipsolutions.net> wrote: > > On Wed, 2018-11-14 at 14:32 -0500, Marten van Kerkwijk wrote: <snip> > > some old issue or even PR somewhere. > > I am mildly in favor, just because there is probably not much > > reason > > against an easy vectorization. Doesn't need to be advertised much > > in > > the docs anyway. > > Although it might be good to settle the "obvious" part in case I am > > not > > alone in first thinking of -1 being the obvious default. I would > > probably skip the axis argument for now, unless someone actually > > has a > > use case. > > Indeed -- I think the best argument for adding an "axis" argument is > that it allows people to be explicit about where the axis ends up, > e.g., both np.linspace(start, stop, num=5, axis=0) and > np.linspace(start, stop, num=5, axis=-1) make their intent quite > clear. > > To me, axis=0 feels like the right default, matching np.concatenate > and np.stack. But NumPy already has split conventions for this sort > of thing (e.g., gufuncs add axes at the end), so I like the explicit > option.
I think that argument goes both ways. Because linspace with an array input can be seen as stacking the linear ramps and not stacking some interpolated intermediate values from start/stop. (Sure, it is more then one dimension, but I would seriously argue the linear ramps are the basic building block and not the input start/stop arrays.) - Sebastian > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion
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