Setting `which=:LR, nev=1` does not return the generalized eigenvalue with the largest real parts, and does not give a warning or error:
n = 10 C = eye(n) A = zeros(n,n) A[1] = 100 A[end] = -100 @assert eigs(A, C, nev=1, which=:LR)[1][1] == maximum(eigs(A, C)[1]) Am I expected to set nev greater than the number of eigenvalues I truly desire, based on my intuition as a numerical analyst? Or has eigs broken its implicit guarantee?
