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
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