At the moment I'm not actively using umatrix. Back when I needed it I wanted to handle RGB and later RGB-IR photosensor measurements for a particular application. I decided to write it because the alternative 350 ms were too costly for me. I only got into quadcopters and some of the math applied on them a year later and that was when I understood the need for fast matrix inversion and decided to pursue it for others' needs.
Are you talking about 4x4 quaternion matrices? I found quaternions and 3D rotations to be fascinating but difficult so I haven't grasped all their aspects: pardon me if the previous question is ignorant.efahl wrote: ↑Fri Aug 24, 2018 7:57 pmIf they are 3D spatial transformations, then the matrix is orthonormal and its inverse is also its transpose. Our multibody dynamics code uses this to good advantage, and we have also added multiply_inverse and divide_inverse methods on the matrix class so we don't even take the transpose, we just flip the order of evaluation in the inner loop, resulting in enormous speed improvements over actually calculating inverses.
Either way this is very cool and neat to know, thanks for sharing