title: Cholesky/LDL-decomposition for semidefinite matrices in python
body: <p>I am looking for Cholesky/LDL-decomposition for <strong>semi</strong>-definite matrices in python.</p>
  
  <p>Search-results:</p>
  
  <ul>
  <li>Both <code>numpy.linalg.cholesky</code> and <code>sympy.Matrix.LDLdecomposition</code> only work for positive-definite.</li>
  <li>There is a request on the scipy-mailing list from 2011 <a href="https://mail.scipy.org/pipermail/scipy-user/2011-July/029926.html" rel="nofollow noreferrer">https://mail.scipy.org/pipermail/scipy-user/2011-July/029926.html</a>, but it seems that was not implemented.</li>
  <li>There is a rough description on <a href="https://mathoverflow.net/questions/155147/cholesky-decomposition-of-a-positive-semi-de%EF%AC%81nite">https://mathoverflow.net/questions/155147/cholesky-decomposition-of-a-positive-semi-de%EF%AC%81nite</a>, but no code. Is there a straightforward implementation?</li>
  </ul>
  
  <p>My instances are rather small, about $100\times100$, so a symbolic solution is fine (the bottleneck is in some other place).</p>