get_mean_distance_matrix

getMeanDistanceMatrix

Given a sequence of distance matrices, expected to correspond to sequential increasing values of time, calculate the average distance between any pairs of nodes
shortest-path (or geodesic) distance

distance

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) <doi:10.1103/physrevlett.118.168301> and
Bertagnolli, G. and De Domenico, M. (2021) <doi:10.1103/PhysRevE.103.042301>.

Giulia Bertagnolli

diffudist

Diffusion Distance for Complex Networks

Manlio De Domenico

get_mean_distance_matrix function

<dl><dt>DM_list</dt>
<dd>list of distance matrices</dd></dl>

Arguments

<ul>
<li><code>getMeanDistanceMatrix()</code>: Old deprecated function</li>
</ul>

Functions

Mean distance matrix — get_mean_distance_matrix

<dl>

<dt>DM_list</dt>
<dd>list of distance matrices</dd>

</dl>

get_mean_distance_matrix: Mean distance matrix

Description

Usage

Value

Arguments

Functions

References

See Also