brainconn.utils.visualization.reorderMAT¶
-
reorderMAT
(m, H=5000, cost='line')[source]¶ This function reorders the connectivity matrix in order to place more edges closer to the diagonal. This often helps in displaying community structure, clusters, etc.
Parameters: - MAT (NxN
numpy.ndarray
) – connection matrix - H (int) – number of reordering attempts
- cost (str) – ‘line’ or ‘circ’ for shape of lattice (linear or ring lattice). Default is linear lattice.
Returns: - MATreordered (NxN
numpy.ndarray
) – reordered connection matrix - MATindices (Nx1
numpy.ndarray
) – reordered indices - MATcost (float) – objective function cost of reordered matrix
Notes
I’m not 100% sure how the algorithms between this and reorder_matrix differ, but this code looks a ton sketchier and might have had some minor bugs in it. Considering reorder_matrix() does the same thing using a well vetted simulated annealing algorithm, just use that. ~rlaplant
- MAT (NxN