On Mon, Jan 9, 2017 at 6:27 AM, Ilhan Polat <ilhanpo...@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 > > > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion > >
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
