I posted this question on https://scicomp.stackexchange.com, but received no attention. As long as I get answer in one of them, I will inform in the other. I have a matrix B which is sparse and try to utilize a function scipy.sparse.linalg.spilu specialized for sparse matrix to factorize B. Could you please explain why this function is significantly less efficient than
Tag: sparse-matrix
Python-Scipy sparse Matrices – what is A[i, j] doing?
According to my previous question here (Python – Multiply sparse matrix row with non-sparse vector by index) direct indexing of sparse matrices is not possible (at least not if you don’t want to work with the three arrays by which the sparse.csr matrix is defined, data, indices, indptr). But I just found out, that given a csr-sparse matrix A, this
Efficiently accumulating a collection of sparse scipy matrices
I’ve got a collection of O(N) NxN scipy.sparse.csr_matrix, and each sparse matrix has on the order of N elements set. I want to add all these matrices together to get a regular NxN numpy array. (N is on the order of 1000). The arrangement of non-zero elements within the matrices is such that the resulting sum certainly isn’t sparse (virtually