The power iteration to compute the largest Singular Value sometimes fails, if the matrix is badly conditioned leading to two "largest" singular values that have approximately the same value.
Enhancement/Discussion
We could think about using numpy.linalg.svd in that case as a fallback. Obviously, this is not a proper solution for large(r) problem sizes.
Problem
The power iteration to compute the largest Singular Value sometimes fails, if the matrix is badly conditioned leading to two "largest" singular values that have approximately the same value.
Enhancement/Discussion
We could think about using numpy.linalg.svd in that case as a fallback. Obviously, this is not a proper solution for large(r) problem sizes.