Enables the evaluation of diffusion distances for complex single-layer networks.
Given a network one can define different types of Laplacian (or transition)
matrices corresponding to different continuous-time random walks dynamics on the network.
This package enables the evaluation of Laplacians, stochastic matrices, and the
corresponding diffusion distance matrices. The metric structure induced by the network-driven
process is richer and more robust than the one given by shortest-paths and allows to study
the geometry induced by different types of diffusion-like communication mechanisms taking
place on complex networks.
For more details see: De Domenico, M. (2017)