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Laplacian, adjacency matrix, and spectrum of graphs.
Needs numpy array package: numpy.scipy.org.
Author: Aric Hagberg (hagberg@lanl.gov) Pieter Swart (swart@lanl.gov) Dan Schult(dschult@colgate.edu)
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Return adjacency matrix of graph as a numpy matrix. This just calls networkx.convert.to_numpy_matrix. If you want a pure python adjacency matrix represntation try networkx.convert.to_dict_of_dicts with weighted=False, which will return a dictionary-of-dictionaries format that can be addressed as a sparse matrix. |
Return standard combinatorial Laplacian of G as a numpy matrix. Return the matrix L = D - A, where D is the diagonal matrix in which the i'th entry is the degree of node i A is the adjacency matrix. |
Return normalized Laplacian of G as a numpy matrix. See Spectral Graph Theory by Fan Chung-Graham. CBMS Regional Conference Series in Mathematics, Number 92, 1997. |
Return standard combinatorial Laplacian of G as a numpy matrix. Return the matrix L = D - A, where D is the diagonal matrix in which the i'th entry is the degree of node i A is the adjacency matrix. |
Return normalized Laplacian of G as a numpy matrix. See Spectral Graph Theory by Fan Chung-Graham. CBMS Regional Conference Series in Mathematics, Number 92, 1997. |
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