11.10.2011 17:57, Christoph Groth kirjoitti: [clip] > My question was about ways to achieve a speedup without modifying the > algorithm. I was hoping that there is some numpy-like library for > python which for small arrays achieves a performance at least on par > with the implementation using tuples. This should be possible > technically.
I'm not aware of such a library. Writing one e.g. with Cython should be quite straightforward, however. [clip] > To generate the output, the algorithm (flood-fill) recursively examines > the starting point and its neighbors, calling for each of them the shape > function. There are various variants of this algorithm, but all of them > rely on the same basic operations. > > To my knowledge, it is not possible to vectorize this algorithm using > numpy. One can vectorize it if a bounding box for the shape is known in > advance, but this is not very efficient as all the lattice points inside > the bounding box are checked. The only way to vectorize this I see is to do write the floodfill algorithm on rectangular supercells, so that the constant costs are amortized. Sounds a bit messy to do, though. -- Pauli Virtanen _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
