There are two approaches for indexing dense and sparse matrices: single-argument indexing and double-argument indexing. In double-argument indexing a matrix is indexed using two index-sets I and J.
>>> from cvxopt import matrix
>>> A = matrix(range(16),(4,4))
>>> print A
[ 0 4 8 12]
[ 1 5 9 13]
[ 2 6 10 14]
[ 3 7 11 15]
>>> print A[[0,1,2,3],[0,2]]
[ 0 8]
[ 1 9]
[ 2 10]
[ 3 11]
The index-sets can be integers, lists, integer matrices, or slices.
>>> print A[1,:]
[ 1 5 9 13]
>>> print A[::-1,::-1]
[ 15 11 7 3]
[ 14 10 6 2]
[ 13 9 5 1]
[ 12 8 4 0]
In single-argument indexing a matrix is indexed in vector-form by considering the matrix in column-major order (i.e., by stacking the columns from left to right).
>>> A[::5] = -1
>>> print A
[ -1 4 8 12]
[ 1 -1 9 13]
[ 2 6 -1 14]
[ 3 7 11 -1]
This is useful for accessing parts of matrix that are not sub-matrices, e.g., the diagonal part of a matrix.