On Wed, 2018-11-14 at 14:46 -0800, Stephan Hoyer wrote:
On Wed, Nov 14, 2018 at 2:35 PM Sebastian Berg < sebastian@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
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