On Fri, 05 Jul 2013 14:41:23 +0100, Oscar Benjamin wrote: > On 5 July 2013 11:53, Helmut Jarausch <jarau...@igpm.rwth-aachen.de> wrote: >> 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. > > When you switched to dictionaries did you take advantage of the > sparseness by iterating over dictionary keys instead of indices? This > is the kind of thing that I meant when I said that in Python it's > often easier to implement a better algorithm than in C. What I mean is > that if Grid is a dict so that Grid[(r, c)] is the entry at row r and > column c (if it exists) then you can change a loop like: > > for r in range(9): > for c in range(9): > if Grid[r, c] > 0: continue > # do stuff > > so that it looks like: > > for r, c in Grid: > # do stuff > > If the grid is sparsely occupied then this could be a significant improvement. > > > Oscar
This gives a big speedup. Now, the time is gone down to 1.73 seconds in comparison to original 13 seconds or the 7 seconds for the first version above. Many thanks, it seems hard to optimize a Python program, Helmut -- http://mail.python.org/mailman/listinfo/python-list
