Dear all,
I am not an expert in NumPy but my undergraduate student is having some issues with the way Numpy returns the normalized eigenvectors corresponding to the eigenvalues. We do understand that an eigenvector is divided by the norm to get the unit eigenvectors, however we do need the original vectors for the purpose of my research. This has been a really frustrated experience as NumPy returns the normalized vectors as a default. I appreciate any suggestions of how to go about this issue. This seems to be a outstanding issue from people using Numpy.
I'm not sure what you mean by "the original vectors". All multiples of the unit eigenvector are eigenvectors. None have a claim on being "the original vector". Do you have a reference for what you are referring to? It's possible that there are specific procedures that happen to spit out vectors that are eigenvectors but have semantics about the magnitude, but `np.linalg.eig()` does not implement that procedure. The semantics about the magnitude would be supplied by that specific procedure.