As we move toward QFED 4, there is a need for efficient binning of observations directly on the cubed sphere grid. For enhanced portability, it would be useful to have this implementation in pure python.
High Level Assumptions and Requirements
Assume there exists netcdf files with the cubed sphere coordinates for each face.
Given a list of coordinates (non,lat), come up with indices (i,j,face) on the cubed sphere grid.
Provide efficient, vectorized, dining algorithm.
@amdasilva will provide API design on feature branch associated with this issue, and simple implementation of 3).
@weiyuan-jiang will implement 2) and write tests.
Background
As we move toward QFED 4, there is a need for efficient binning of observations directly on the cubed sphere grid. For enhanced portability, it would be useful to have this implementation in pure python.
High Level Assumptions and Requirements
@amdasilva will provide API design on feature branch associated with this issue, and simple implementation of 3). @weiyuan-jiang will implement 2) and write tests.