boscoh
commented
9 years ago Hi Andrey,
Just tested your changes, and they're fantastic. Example with the structure 1FNF.
I added a flag -o to turn optimization on/off:
> time pypy `which pdbasa` -o 1fnf.pdb
real 0m40.573sAnd without:
> time pypy `which pdbasa` 1fnf.pdb
real 1m4.901sA solid reduction by 40%. Great!
Before I merge the commit, could you harmonize your coding style with mine?
Namely:
- snake case for function names/variables http://en.wikipedia.org/wiki/Snake_case
- I save CamelCase for ObjectClassNames
- I use lower case for all variables/parameters pretty much everywhere
- rename calculate_asa_opt to calculate_asa_optimized: as this function is not called often, I prefer to spell out whole words, which makes it considerably easier for others to read!
Once this is done, I'll merge it and then add the -o flag in pdbasa to use your fantastic optimization.
Great work!
Bosco
Andrey-Tokarev
Hi Bosco,
I finally managed to finish and submit my article :) . As I wrote in the comments (http://boscoh.com/protein/calculating-the-solvent-accessible-surface-area-asa.html) in that work I used your code for calculating ASA (which I referenced, as well as Shake-Rupley paper). In the process I slightly optimized it: function "calculate_asa_opt" in asa.py is linear in number of atoms by "pre-partition the atoms into disjoint cubes to speed up the search for neighboring atoms" as you suggested in the post. Specifically, it works in O(n * m + n * N * m) time complexity in comparison to original version "calculate_asa" that works in O(n * n + n * N * m), where n - number of atoms = len(atoms), m - averaged number of neighbors of an atom = mean[len(neighbor_indices)], N - number of generated sphere points = n_sphere_point.
Another optimization is in using square of distance instead of distance in two places: "calculate_asa_opt" and "find_neighbor_indices_mod": it allows to avoid a heavy square root operation (actually, this simple change saved up to 20% of time!). For this purpose new function "mag2" (square of vector magnitude) was added to two files: v3numpy.py and v3array.py.
I tested "calculate_asa_opt" for "1be9.pdb" protein structure for all atoms (1045 atoms). Overall speed up: for N = 960 sphere points, it was ~1.8 times faster; for N = 96 sphere points, it was ~2.7 times faster. As it is seen from the above formula, the greater is n (and less N), the greater is speed up.
As you see, I did not delete or modify any of your code. Everything new was added. So if can either substitute your functions with mine, or leave it as it is: two functions, quadratic and linear.
Kind regards, Andrey Tokarev
P.S. I am a complete novice to GitHub. This is actually my first action here. So I am sorry for any possible missteps