How to Solve Numba Lowering error?

Question

I have a function, which I am trying to speed up using the @jit decorator from Numba module. For me it is essential to speed this up as much as possible, because my main code ca

Answer 1

I can't see from your code why this isn't vectorizable. Vectorizing can speed up this kind of Python code by around 100x. Not sure of how it does relative to jit.

It looks like you could, for instance, take your dEdt out of the loop, and compute it in one step with something like :

dEdt = 0.5 * (Cmx[:, :, :, 0] * dg * (1+A*1j) * Nf[:] * Ef[:, None] * np.exp( 1j* (Sweep.omega[None, :, None, None]-Sweep.omega) *tijd)).sum(axis=2).sum(axis=1) - 0.5*(pd-g)*Ef + fbr*Ef2  + Kinj*EAinj*(1 + np.exp(1j*(u+Vmzm)) )

(Though I don't really know what the dimensionality of your Sweet.omega is).