On 5 Jul 2013 11:58, "Helmut Jarausch" <jarau...@igpm.rwth-aachen.de> wrote: > > On Fri, 05 Jul 2013 11:13:33 +0100, Oscar Benjamin wrote: > > > My one comment is that you're not really making the most out of numpy > > arrays. Numpy's ndarrays are efficient when each line of Python code > > is triggering a large number of numerical computations performed over > > the array. Because of their N-dimensional nature and the fact that > > they are in some sense second class citizens in CPython they are often > > not as good as lists for this kind of looping and indexing. > > > > I would actually expect this program to run faster with ordinary > > Python lists and lists of lists. It means that you need to change e.g. > > Grid[r, c] to Grid[r][c] but really I think that the indexing syntax > > is all you're getting out of numpy here. > > > > Thanks Oscar, that was a big improvement, indeed. > Using lists of lists instead of numpy arrays made the code more than > twice as fast (13 seconds down to 6 seconds) > > Since I don't do any numerical stuff with the arrays, Numpy doesn't seem to be > a good choice. I think this is an argument to add real arrays to Python. > > I even tried to use dictionaries instead of Numpy arrays. This version is a bit > slower then the lists of lists version (7.2 seconds instead of 6 second) but still > much faster than the Numpy array solution.
May I suggest you avoid range and use enumerate(the_array) instead? It might be faster.
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