[Numpy-discussion] Good way to develop numpy as popular choice!
Fri Jun 22 08:48:30 CDT 2012
On Fri, Jun 22, 2012 at 9:42 AM, eat <email@example.com> wrote:
> On Fri, Jun 22, 2012 at 7:51 AM, Gael Varoquaux <
> firstname.lastname@example.org> wrote:
>> On Thu, Jun 21, 2012 at 08:59:09PM -0400, Benjamin Root wrote:
>> > > munkres seems to be a pure python implementation ;-).
>> > Oops! I could have sworn that I once tried one named munkres that
>> > numpy. But that was several years ago.
>> > There is a development branch of sk-learn with an implementation of
>> > hungarian assignment solver using numpy. It will even do non-square
>> > matrices and matrices with an empty dimension.
>> Yes, absolutely, thanks to Ben:
>> I never merged this in the main scikit-learn tree, because munkres is not
>> used so far. Maybe I should merge it in the main tree, or maybe it should
>> be added to scipy or numpy.
> I made some simple timing comparisons (see attached picture) between numpy
> based hungarian and pure python shortest path based hungarian_sp. It seems
> that pure python based implementation outperforms numpy based
> implementation. Timings are averaged over five runs.
> The difference cannot totally be explained by different algorithms
> (although shortest path based seem to scale better). Rather the heavy
> access to rows and columns seem to favor list of lists. So this type of
> algorithms may indeed be real challenges for numpy.
Thanks for that analysis. Personally, I never needed high-performance so I
never bothered to optimize it. However, it does appear that there is an
order-of-magnitude difference between the two, and so it might be worth it
to see what can be done to fix that.
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