The function JacobiSVD and BDCSVD can calcuate condtion number of a dense matrix via singular values. However I need to know condition number of a sparese matrix due to slow computation speed using iterative linear solver. I can't find such function. If the sparse matrix is converted to one dense one in advance, the memory allocation occur because of large size of the matrix(about 10,000 x 10, 000). Many people may encounter this problem. Is there one way there to calculate condition number for a large sparese matrix in Eigen?
Is there any function to calculate condition number of sparse matrix in Eigen libraray?
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cholmod rcondwhich estimates the reciprocal condition number of a sparse matrix that can be decomposed with an LLT or LDLT factorization. "Returns a rough estimate of the reciprocal of the condition number: the minimum entry on the diagonal of L (or absolute entry of D for an LDLT factorization) divided by the maximum entry." This seems like a viable alternative to forming the dense matrix. fossies.org/linux/SuiteSparse/CHOLMOD/Doc/CHOLMOD_UserGuide.pdf $\endgroup$