pseudo inverse of sparse matrix in python

Question

I am working with data from neuroimaging and because of the large amount of data, I would like to use sparse matrices for my code (scipy.sparse.lil_matrix or csr_matrix).

<

Answer 1

Regardless of the answer to my comment, I would think you could accomplish this fairly easily using the Moore-Penrose SVD representation. Find the SVD with scipy.sparse.linalg.svds, replace Sigma by its pseudoinverse, and then multiply V*Sigma_pi*U' to find the pseudoinverse of your original matrix.