[SciPy-User] Eigenvectors of sparse symmetric matrix
Mon Oct 25 05:03:43 CDT 2010
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
> 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.
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