I use gprof2dot to visualize the output from python cProfile quite a lot. You may want to try that out:
It only breaks it down between functions, but it should give an idea of where most the time is being spent.
On Sat, Mar 26, 2011 at 11:38 AM, Stephen Skory email@example.com:
In summary, for medium to very large sized clumps (in terms of number of cells), the treecode is showing it's usefulness. My tests are not complete, but the break even line with the standard opening angle (==approximation control) of 1.0, is about 100,000 cells. For example, a spherical clump with three levels and 120,000 cells takes 272 seconds with the O(N^2) method, 175 seconds with the treecode, and has a 0.05% error.
That's interesting. To be perfectly honest, I kind of expected it to perform a bit better. Any insight where the overhead comes from?
I'm not sure. I haven't timed individual steps of the code yet to see if something is unreasonably slow. Any useful tool recommendations are welcomed.
It should be on by default. What is the performance difference, for a small/medium clump? 10%? 50%? Factor of 10?
It looks like it's no worse than a factor of two slower for opening_angle=1.0 at around 30,000 cells. I plan on making a figure showing this stuff soon.
Very nice work! I have reviewed your changes and I think you should merge them. This will be a shining addition to the 2.1 release.
Thanks for the praise, I appreciate it.
Could you post a script verifying that it works for clumps on the edge and in the center, to be added to the answer tests?
Sure, I can do that.
Stephen Skory firstname.lastname@example.org http://stephenskory.com/ 510.621.3687 (google voice)
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