Home

CLPM is created and maintained by:

• Dr. Marco Corneli (Université Côte d'Azur, France)

• Dr. Riccardo Rastelli (University College Dublin, Ireland)

CLPM is a Python tool that can be used to model and visualize dynamic networks.

This software accompanies the paper http://arxiv.org/abs/2103.17146

As a brief overview, this is what the CLPM software does:

• Input: CLPM takes in input a list of interactions between N nodes, where the generic entry in the list is a triplet (t, i, j) indicating that node i and node j had an instantaneous interaction at time t.

• Output: CLPM returns the trajectories of the nodes on a plane, at each point in time. These are inferred from the interaction data, assuming that the distances between the nodes on the plane, at each time, determine the rates at which they interact.

This software can be used to reconstruct latent space visualizations of dynamic networks of instantaneous interactions.

Examples of dynamic network data includes text message networks, email networks, proximity networks, transportation networks, brain connectome networks. Interactions between any two entities are assumed to be instantaneous, and they can happen at any point in time.