Re: [SciPy-User] Eigenvectors of sparse symmetric matrix

Sun, 24 Oct 2010 18:42:14 -0700, Hao Xiong wrote:

I am trying to compute the eigenvectors corresponding to the d+1 smallest eigenvalues of A=W.T*W. I started with W as a dense matrix and then W = sparse.csr_matrix(W) A = W.dot(W) # W.T * W

That is W*W and not (W.T)*W

W,V = eigen_symmetric(A,d+1, which='SM')

The biggest problem is that the algorithm fails to converge and I get all zeros as eigenvectors for a testing dataset. Using dense SVD I got the expected results.

You can try playing with setting the maxiter parameter to allow ARPACK to spend more iterations on the problem. -- Pauli Virtanen