Re: [Numpy-discussion] cross product of two 3xn arrays

[Charles R H. <cha...@gm...>]

On 2/17/06, Bill Baxter <wb...@gm...> wrote:
> For folks using quats to represent rotations (which is all I use them for=
,
> anyway), if you're batch transforming a bunch of vectors by one quaternio=
n,
> it's a lot more efficient to convert the quat to a 3x3 matrix first and
> transform using matrix multiply (9 mults per transform that way vs 21 or =
so
> depending on the implementation of q*v*q^-1).  Given that, I can't see ma=
ny
> situations when I'd need a super speedy C version of quaternion multiply.
>
> --Bill

True. On the other hand, I have files containing 20,000 quaternions,
each of which needs to be converted to a rotation matrix and applied
to some 400 vectors, so a c version would have its place. I have a
python quaternion class that I use for such things but profiling shows
that it is one of the prime time bandits, so I am tempted to use c for
that class anyway. Note that the current NumPy cross product is
implemented in Python.

On a related note, indexing in numarray is some 3x faster than in
NumPy and I'm wondering what needs to be done to speed that up.

Chuck