[Numpy-discussion] Fwd: Backslash operator A\b and np/sp.linalg.solve

[josef.pktd at gmail.com]

On Mon, Jan 9, 2017 at 6:27 AM, Ilhan Polat <ilhanpolat at gmail.com> wrote:

> > Note that you're proposing a new scipy feature (right?) on the numpy
> list....
>
> > This sounds like a good idea to me. As a former heavy Matlab user I
> remember a lot of things to dislike, but "\" behavior was quite nice.
>
> Correct, I am not sure where this might go in. It seemed like a NumPy
> array operation (touching array elements rapidly etc. can also be added for
> similar functionalities other than solve) hence the NumPy list. But of
> course it can be pushed as an exclusive SciPy feature. I'm not sure what
> the outlook on np.linalg.solve is.
>
>
> > How much is a noticeable slowdown? Note that we still have the current
> interfaces available for users that know what they need, so a nice
> convenience function that is say 5-10% slower would not be the end of the
> world.
>
> the fastest case was around 150-400% slower but of course it might be the
> case that I'm not using the fastest methods. It was mostly shuffling things
> around and using np.any on them in the pure python3 case. I will cook up
> something again for the baseline as soon as I have time.
>
>
>
All this checks sound a bit expensive, if we have almost always completely
unstructured arrays that don't satisfy any special matrix pattern.

In analogy to the type proliferation in Julia to handle those cases: Is
there a way to attach information to numpy arrays that for example signals
that a 2d array is hermitian, banded or diagonal or ...?

(After second thought: maybe completely unstructured is not too expensive
to detect if the checks are short-circuited, one off diagonal element
nonzero - not diagonal, two opposite diagonal different - not symmetric,
...)

Josef




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