Change RGBACluster to be a class that only really persists once per block.
When we switch shapes and do operations on them, then we really only need
to change which points in the block are accessed. We don't need to do this
very often, so just change the mask whenever we need it. This brings us back
closer to our original performance, but we're still not where we were when
we started refactoring.
We suffered another performance hit. This time it comes from the fact
that we're copying around a lot of data based on what partition we're
choosing. We can get rid of this a tad by only copying the data that we
need once and then using getters/setters that selectively pull from
an array based on our shape index.
Changed the RGBAEndpoints to use the vector/matrix classes in
FasTCBase. This caused a ~20ms performance hit on an 8-core machine
which is likely due to the compiler having difficulty compiling away
some procedure call overheads. Upon profiling, the biggest bottleneck
is still by far the QuantizedError function, so any and all further
optimization should be focused on that.
eigenvalues of the covariance matrix associated with the cluster.
- Compared results of testing the ratio of eigenvalues as a measurement of
'linearity' for the different shapes, and output statistics.
- Added a #define that controls whether or not we do shape estimation using
quantized AABB error or eigenvalue ratios. The former seems to be better.
