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normalized_laplacian_matrix¶

normalized_laplacian_matrix
(G, nodelist=None, weight='weight')[source]¶ Return the normalized Laplacian matrix of G.
The normalized graph Laplacian is the matrix
where is the graph Laplacian and is the diagonal matrix of node degrees.
Parameters:  G (graph) – A NetworkX graph
 nodelist (list, optional) – The rows and columns are ordered according to the nodes in nodelist. If nodelist is None, then the ordering is produced by G.nodes().
 weight (string or None, optional (default=’weight’)) – The edge data key used to compute each value in the matrix. If None, then each edge has weight 1.
Returns: N – The normalized Laplacian matrix of G.
Return type: NumPy matrix
Notes
For MultiGraph/MultiDiGraph, the edges weights are summed. See to_numpy_matrix for other options.
If the Graph contains selfloops, D is defined as diag(sum(A,1)), where A is the adjacency matrix [2].
See also
References
[1] Fan ChungGraham, Spectral Graph Theory, CBMS Regional Conference Series in Mathematics, Number 92, 1997. [2] Steve Butler, Interlacing For Weighted Graphs Using The Normalized Laplacian, Electronic Journal of Linear Algebra, Volume 16, pp. 9098, March 2007.