The code currently computes the 1 norm using norm(A^m,1) instead of estimating more efficiently. This ends up being the bottleneck in the calculation of not so sparse matrices.
The MATLAB code uses normest1(), a proprietary function. However, the algorithm for normest1 is described in
Nicholas J. Higham and Françoise Tisseur (2000) A block algorithm for matrix 1-norm estimation, with an application to 1-norm pseudospectra. SIAM Journal On Matrix Analysis And Applications, 21 (4). pp. 1185-1201. ISSN 1095-7162 (preprint)
and it should not be too hard to reimplemented it, thereby avoiding this performance bottle neck.
The code currently computes the 1 norm using
norm(A^m,1)instead of estimating more efficiently. This ends up being the bottleneck in the calculation of not so sparse matrices.The MATLAB code uses
normest1(), a proprietary function. However, the algorithm fornormest1is described inNicholas J. Higham and Françoise Tisseur (2000) A block algorithm for matrix 1-norm estimation, with an application to 1-norm pseudospectra. SIAM Journal On Matrix Analysis And Applications, 21 (4). pp. 1185-1201. ISSN 1095-7162 (preprint)
and it should not be too hard to reimplemented it, thereby avoiding this performance bottle neck.