Re: New keyword name for linalg.lu

In the end I went with "matrix_p = True" to ring like "permute_l" which was
I think what you were suggesting anyways. Hopefully some day in the future
we can change this to False and be done with it.

On Sun, May 21, 2023 at 11:31 PM Andras Deak <[email protected]> wrote:

> On Sun, May 21, 2023, at 17:08, Ilhan Polat wrote:
> > Sorry for reviving this thread, but indeed "p_indices" sounding uglier
> > the more I look at it. Just to summarize what it does to save you from
> > the thread above;
> >
> > when
> >
> > P, L, U = scipy.linalg.lu(A)
> >
> > is run, currently, P is returning a full 2D array. If A is a tall array
> > say, (25, 5) then P is necessarily (25, 25). And it is just a
> > permutaiton matrix, a row shuffled np.eye(25). Instead, you can ask
> > with this new keyword to return that shuffle pattern. as a 1D array and
> > hence P becomes (25, ) array. And there are more than rare cases that
> > only L and U is needed for other purposes.
> >
> > So we would like to make that matrix vs array switch with a keyword. I
> > thought "p_indices = True/False" was a good idea but it became a bit
> > disturbing. Other matlab following software offers a string selector
> > with "outputForm='matrix'/'vector'" which forces users to remember the
> > options hence I am voting for a TrueFalse flag. However I can't come up
> > with the right keyword.
> >
> > Could you please offer some alternatives even just for inspiration?
>
> How about reversing the meaning of the flag and naming it something like
> `p_full` or `full_p` with a `True` default? I also considered "squareform"
> instead of "full" as in `spatial.distance.squareform`, because there's a
> similar 1d <-> 2d square thing here, but the semantics are different enough
> that this name would probably be more confusing than helpful.
>
> András
>
> >
> > Best,
> > ilhan
> >
> >
> >
> > On Tue, Apr 25, 2023 at 9:34 AM Jake Bowhay <[email protected]>
> wrote:
> >> It would be nice to add a quick note to the docs explaining when/which
> you should use. Currently both state "Compute pivoted LU decomposition of a
> matrix." which while true isn't very helpful for a user trying to decide
> which function to pick!
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