title: How to compute scipy sparse matrix determinant without turning it to dense?
body: <p>I am trying to figure out the fastest method to find the determinant of sparse symmetric and real matrices in python. using scipy <code>sparse</code> module but really surprised that there is no determinant function. I am aware I could use LU factorization to compute determinant but don't see a easy way to do it because the return of <code>scipy.sparse.linalg.splu</code> is an object and instantiating a dense L and U matrix is not worth it - I may as well do <code>sp.linalg.det(A.todense())</code> where <code>A</code> is my scipy sparse matrix. </p>
  
  <p>I am also a bit surprised why others have not faced the problem of efficient determinant computation within scipy. How would one use <code>splu</code> to compute determinant? </p>
  
  <p>I looked into <code>pySparse</code> and <code>scikits.sparse.chlmod</code>. The latter is not practical right now for me - needs package installations and also not sure sure how fast the code is before I go into all the trouble. 
  Any solutions? Thanks in advance. </p>