another thing to consider is f2py, which allows calls to Fortran subroutines from Python. in my experience, it was faster than numpy, but you have to suffer from writing Fortran.

Just use numba and get fortran like performance by writing in python.

I got inconsistent results when using Numba. when it worked well, it was way faster than Numpy, but sometimes it was slower. I wasn't able to figure out how to do AOT compilation, so I just went with f2py. if Numba has AOT compilation, I'd definitely use that over f2py though.

AOT compilation is in the works. Also you might have been using features that numba didn't support yet. They just added more numpy ops, array allocation and vector ops, so your code might be working now.

I am no longer working on the project (it was part of a 4-month research project), but I'll make sure to tell my supervisor. thanks! :D