Returns a matrix where each entry encodes the diffusion probability between two nodes
get_diffusion_probability_matrix( g, tau, type = "Normalized Laplacian", weights = NULL, verbose = TRUE ) getDiffusionProbabilityMatrix(g, tau, type = "Normalized Laplacian", weights = NULL, verbose = TRUE) get_diffu_Pt( g, tau, type = "Normalized Laplacian", weights = NULL, verbose = TRUE )
g | a single-layer network |
---|---|
tau | diffusion time |
type | default "Normalized Laplacian". The type of Laplacian (i.e. of dynamics) to consider. Other types available are:
Note that you can type abbreviations, e.g. "L", "N", "Q", "M" for the
respective types (case is ignored). The argument match is done through
|
weights | edge weights, representing the strength/intensity (not the cost!) of each link. if weights is NULL (the default) and g has an edge attribute called weight, then it will be used automatically. If this is NA then no weights are used (even if the graph has a weight attribute). |
verbose | default |
The matrix \(exp^{-\tau L}\), exponential of a Laplacian matrix.
getDiffusionProbabilityMatrix
: Old deprecated function
De Domenico, M. (2017). Diffusion Geometry Unravels the Emergence of Functional Clusters in Collective Phenomena. Physical Review Letters. doi: 10.1103/PhysRevLett.118.168301
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