It is a layout algorithm based on an attraction-repulsion force system. All nodes suffer repulsion forces from every other node and attraction to those who are linked. The total energy of the system is minimized using simulated annealing, finding a state with force equilibrium. The intensity of the attraction force can be influenced by any numerical link property, reflecting the strength of the link. This layout is recommended for small and medium-size networks (10.000 nodes max.) due to the bad scaling with the number of nodes.
|Iterations*||int > 0||200||Number of iterations of the plugin.|
|Cooling||float > 0||3||Cooling exponent for reducing the temperature along the iterations. The maximum node displacement is proportional to. Small values (~1) represent slow cooling, while higher values (~4) indicate faster cooling.|
|2D||Bool||False||Whether to use a 2D or 3D layout.|
|Expansion factor||float>0||1.0||Multiplicative factor for the repulsion force. Increase it to increment the distance between nodes.|
|Link weight||text||None||Link property that represents the intensity of the attraction between connected nodes. Must have positive values|
|Seed||int||0||Random seed. If equals zero, it is chosen by the system.|
|Reset Positions||Bool||False||Whether to delete any previously calculated positions and start a new fresh layout.|
* Required Field
Here we show two examples of this layout results applied on two social networks. Node color correspond to the Louvain community detection algorithm.
The next plot shows the effect of the expansion factor [e.f.] on the same network: