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eigenvalues of a derivative vs derivative of eigenvalues

Hi! I have this little problem. If anyone would be so kind to share his knowledge and shed some lite on it, I'd be very grateful. Big thanks in advance (and sorry for my english)!

I have a matrix M=M(x) depending on a variable x. I want sage to compute trace of a product of a derivative of M, M' and some function of it, f(M), at a fixed value of x=x_0; that is:

(tr[M'*f(M)])|_(x=x_0).

It just so happens that tr[M'*f(M)] = sum( ev_i' *f(ev_i) ), where {ev_i(x)} are eigenvalues of M. Lucky me. Diagonalisation of M commutes with differentiating or taking the function of it, one could say.

But my M and its derivative are somewhat complicated, yet simplify greatly after substituting x=x_0. So I would very much prefer first to compute M', substitute x_0 M0:=M|_(x=x_0) and M'0:=M'|_(x=x_0), and only after that ask sage for eigenvalues:

ev1=M0.eigenvalues()

ev2=M'0.eigenvalues()

So here's the question: do i have any reason for hoping that:

(tr[M'*f(M)])|_(x=x_0) = sum( ev2[i] *f(ev1[i]) for i in range(dim of M) )?

(That is, wether the order of eigenvalues changes if I exchange diagonalisation with differentiation?)