[Numpy-discussion] Improving Complex Comparison/Ordering in Numpy

[Rakesh Vasudevan]

I agree with the idea of setting apart the parameter from python , "by"
sounds like a good alternative

Rakesh



On Wed, Jul 1, 2020, 18:45 Sebastian Berg <sebastian at sipsolutions.net>
wrote:

> On Wed, 2020-07-01 at 12:48 -0700, Stephan Hoyer wrote:
> > On Wed, Jul 1, 2020 at 12:23 PM Sebastian Berg <
> > sebastian at sipsolutions.net>
> > wrote:
> >
> > > This is a WIP, but allows nicely to try out how the new API
> > > could/should look like, and see the potential impact to code.  The
> > > current choice is for:
> > >
> > >     np.sort(arr, keys=(arr.real, arr.image))
> > >
> > > for example.  `keys` is like the `key` argument to pythons sorts,
> > > but
> > > unlike python sorts is not passed a function but rather a sequence
> > > of
> > > arrays.
> > >
> > > Alternative spellings could be `by=...`? Or maybe someone has a
> > > different API idea.
> > >
> >
> > I really like the look of np.sort(arr, by=(arr.real, arr.image)).
> > - This avoids adding an extra function sortby into NumPy's API. The
> > default
> > behavior (by=None) would of course be to sort by the arrays being
> > sorted,
> > so it's backwards compatible.
> > - Calling the new argument "by" instead of "key" avoids confusion
> > with the
> > behavior of Python's sort/sorted (which take functions instead of
> > sequences).
>
>
> I just noticed that `DataFrame.sort_values()` uses `by=...` with a list
> of column names.  However, I guess that is fairly compatible with this
> usage.
>
> - Sebastan
>
>
> > The combination of lexsort() and take_along_axis() makes it possible
> > to
> > achieve this behavior currently, but it is definitely less clear than
> > a
> > single function call.
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