That function was only being used by the unit tests and the benchmark. In order
to remove memory usage, the triangles will be removed, since we don't actually
need to keep them in real situations. Thus, this patch removes that function
and copy those triangles to the test and benchmark.
This is the second optimization. With that we don't have to iterate over the
umbrella's components.
The table below summarizes the mean CPU time in ns from the brenchmark results
on an Intel(R) Core(TM) i7-3520M CPU @ 2.90GHz processor:
| Naive implementation | First Optimization | Second Optimization
------------------------------------------------------------------------
Min. | 26.0 | 28.00 | 26.0
1st Qu.| 78.0 | 48.75 | 39.0
Median | 132.0 | 57.00 | 41.0
Mean | 130.1 | 61.20 | 41.6
3rd Qu.| 182.2 | 76.00 | 47.0
Max. | 234.0 | 98.00 | 54.0
If v is the null vector, then alpha * v is still the null vector for any alpha
as a real number. That means that the null vector doesn't cross any section.
This is a first optimization of the algorithm. The struct for the neighbor
umbrella has only one member, but new members will be added in the next
optimization.
The table below summarizes the mean CPU time in ns from the brenchmark results
on an Intel(R) Core(TM) i7-3520M CPU @ 2.90GHz processor:
Cases | Naive implementation | First Optimization
--------------------------------------------------
Min. | 26.0 | 28.00
1st Qu.| 78.0 | 48.75
Median | 132.0 | 57.00
Mean | 130.1 | 61.20
3rd Qu.| 182.2 | 76.00
Max. | 234.0 | 98.00
This optimization reduces the mean time for the worst case (Max. line) by more
than 50%.
- Change the order of the icosahedron triangles so that there's a uniform way of
finding the opposite triangle. The order visually still makes sense.
- Change test to accommodate the order change.
