get_spectral_decomp {diffudist} | R Documentation |
Laplacian Spectral Decomposition
Description
Returns the eigenvalue spectrum together with eigenvectors of a Laplacian
corresponding to a network. This involves computing the eigendecomposition of
a (symmetric) matrix, so it is computationally intense and may take some time.
The decomposition of the normalized Laplacian L = I - D^{-1}A
takes
is computed through the decomposition of its symmetric version
L = D^{-\frac{1}{2}}AD^{-\frac{1}{2}}
. See the package vignette for details.
Usage
get_spectral_decomp(g, type = "Normalized Laplacian", verbose = FALSE)
Arguments
g |
the network in the [igraph] format |
type |
the Laplacian type, default "Normalized Laplacian". At the moment this is the only available option. For other types of Laplacians one should get autonomously the eigendecomposition, e.g. using eigen. See the package vignette for an example. |
verbose |
whether warnings have to be printed or not |
Value
lambdas the eigenvalues of the Laplacian
'u_L' the matrix of left eigenvectors (rows)
'u_R' the matrix of right eigenvectors (columns)
References
Bertagnolli, G., & De Domenico, M. (2021). Diffusion geometry of multiplex and interdependent systems. Physical Review E, 103(4), 042301. doi:10.1103/PhysRevE.103.042301 arXiv: 2006.13032
See Also
get_laplacian
get_ddm_from_eigendec