Open kne42 opened 6 years ago
cc @jni
@kne42 you should practice your math lecturing skills before the sprint, so you can explain this gibberish to me. 😂
Incidentally, it is ok for a subset of transforms to only support a subset of dimensionalities, as long as it is all well-documented. The principal goal is to make sure our coordinates match NumPy axes for the whole transform
module.
@jakirkham No, I have not. It looks very useful though! I should probably familiarize myself with dask
before the sprint lol...
Should probably add an einsum
implementation was added very recently as well. Maybe that’s even a better option depending on what’s required for these operations.
The einsum
function should do nicely for wedge product computation; thank you!
I have been considering expanding the
transforms
module of scikit-image to support n-dimensional operations. This would provide more utility and lay the groundwork to start expanding the rest of the library to work in nD as well.Essential matrices will be an issue however since they make use of the wedge product, which is not implemented in
numpy
.