[Numpy-discussion] Vectorized version of numpy.linspace
harrigan.matthew at gmail.com
Wed Nov 14 12:57:35 EST 2018
I put in an issue a while ago, https://github.com/numpy/numpy/issues/8839
My use case was somwhat similar to meshgrid but with a nonrectangular
domain. Not terribly hard to code, but my expectation is that numpy
functions should always allow broadcasting if that operation makes sense.
On Nov 14, 2018 12:42 PM, "Gerrit Holl" <gerrit.holl at gmail.com> wrote:
On Wed, 14 Nov 2018 at 17:29, Ralf Gommers <ralf.gommers at gmail.com> wrote:
> On Wed, Nov 14, 2018 at 8:57 AM Stephan Hoyer <shoyer at gmail.com> wrote:
>> It recently came up on GitHub (at part of the discussion in
https://github.com/numpy/numpy/issues/12379) that numpy.linspace could, at
least in principle, be modified to support array inputs:
>> It looks like this has been requested on StackOverflow, too:
>> My tentative proposal:
>> - "start" and "stop" are broadcast against each other to form start/stop
arrays. (Or we could require that start/stop have matching shape.)
>> - A new dimension of size "num" is inserted into the result, either
along the first or last axis.
>> - A new keyword argument "axis" could control where the axis is inserted
in the result.
>> - Vectorization support should be added in the same way to geomspace and
>> Does this seem like a good idea? It's a relatively simple
generalization, and one that I, at least, would find useful (I can think of
a use-case in my own code that came up just last week).
> This feels a bit forced. There's not much relevance to the minor
performance gain, and for code clarity it probably also wouldn't help
(actually it hurts usability for 99.x% of use cases by making the doc more
complicated). Not sure that it really would require a new axis argument, as
Marten said on the issue. Also, the num keyword cannot be vectorized,
unless one returns a list of arrays, which would actually be more natural
here than a 2-D array.
> So, at best a don't care for me - I'm -0.5.
For what it's worth, I had a use case for this in the past week, when
I needed many simple linear interpolations between two values (thus a
linspace) with only the value of boundary points varying. However,
this was the first time I've ever needed it, and I found a recipe on
Stack Overflow within minutes
(https://stackoverflow.com/a/42617889/974555) so it wasn't a big deal
that it wasn't available in core numpy.
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