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. Helmut -- http://mail.python.org/mailman/listinfo/python-list
