CVXOPT includes an interface to the AMD library for computing approximate minimum degree orderings of sparse matrices.
See also:
order(A[, uplo=’L’])
Computes the approximate mimimum degree ordering of a symmetric sparse matrix A. The ordering is returned as an integer dense matrix with length equal to the order of A. Its entries specify a permutation that reduces fill-in during the Cholesky factorization. More precisely, if p = order(A), then A[p,p] has sparser Cholesky factors than A.
As an example we consider the matrix
>>> from cvxopt import spmatrix, amd
>>> A = spmatrix([10,3,5,-2,5,2], [0,2,1,2,2,3], [0,0,1,1,2,3]) >>> P = amd.order(A) >>> print P [ 1] [ 0] [ 2] [ 3] |