[Numpy-discussion] Optimize Floyd-Wallshall algorithm with Numpy
josef.pktd@gmai...
josef.pktd@gmai...
Sat Nov 6 14:46:17 CDT 2010
On Sat, Nov 6, 2010 at 3:28 PM, K. Sun <sunk.cs@gmail.com> wrote:
> Hello,
>
> I wrote the following code with numpy to implement the Floyd-Wallshall
> algorithm to compute the pair-wise shortest path in a undirected weighted
> graph. It is really slow when N ~ 10k, while the same implementation in
> matlab is much faster. I am sorry I don't want to run it again to
> present some accurate comparison. Is there any suggestions to optimize
> this code without destroying the elegant coding style of python?
> Thank you very much.
>
> def floyd( dis ):
> '''
> dis is the pair-wise distance matrix.
> return and update dis as the shortest path matrix w_{ij}.'''
>
> N = dis.shape[0]
> for k in range( N ):
> route = np.kron( np.ones( (N, 1) ), dis[k, :] )
I think your kron just does broadcasting, if you use
route = dis[k:k+1, :]
(I expect) you get the same results, and it would save one intermediary array
> dis = np.minimum( dis, route + route.T )
Otherwise, I don't see much that I would speed up (without
understanding the algorithm)
Josef
>
> return dis
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