title: Method for finding all eigenvalues of a sparse matrix in python
body: <p>I am currently trying to use the sparse matrices from the scipy library to compute all the eigenvalues of a Hermitian matrix. From what I have seen so far, there is no simple method to get all the eigenvalues of the matrix, but instead a subrange of eigenvalues.
  I was wondering whether there is a  method for this somewhere, or perhaps the only way is to compute the eigenvalues in parts and save to an array. <strong>EDIT:</strong> According to this API, <a href="https://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.linalg.eigsh.html#scipy.sparse.linalg.eigsh" rel="nofollow noreferrer">scipy.sparse.linalg.eigsh
  </a>, it is not possible to compute all the eigenvalues.</p>
  <p>Without the sparse matrices, I am able to code this in numpy, but have a memory allocation error very quickly. I should mention that my matrices have only 5 non-zero entries in a row.</p>
  <p>Does anyone know of a method to accomplish this?</p>