arf_layout

arf_layout(G, pos=None, scaling=1, a=1.1, etol=1e-06, dt=0.001, max_iter=1000, *, seed=None)

Arf layout for networkx

The attractive and repulsive forces (arf) layout [1] improves the spring layout in three ways. First, it prevents congestion of highly connected nodes due to strong forcing between nodes. Second, it utilizes the layout space more effectively by preventing large gaps that spring layout tends to create. Lastly, the arf layout represents symmetries in the layout better than the default spring layout.

Parameters:

Gnx.Graph or nx.DiGraph

Networkx graph.

posdict

Initial position of the nodes. If set to None a random layout will be used.

scalingfloat

Scales the radius of the circular layout space.

afloat

Strength of springs between connected nodes. Should be larger than 1. The greater a, the clearer the separation ofunconnected sub clusters.

etolfloat

Gradient sum of spring forces must be larger than etol before successful termination.

dtfloat

Time step for force differential equation simulations.

max_iterint

Max iterations before termination of the algorithm.

seedint, RandomState instance or None optional (default=None)

Set the random state for deterministic node layouts. If int, seed is the seed used by the random number generator, if numpy.random.RandomState instance, seed is the random number generator, if None, the random number generator is the RandomState instance used by numpy.random.

References

.. [1] “Self-Organization Applied to Dynamic Network Layout”, M. Geipel,

International Journal of Modern Physics C, 2007, Vol 18, No 10, pp. 1537-1549. https://doi.org/10.1142/S0129183107011558 https://arxiv.org/abs/0704.1748

Returns:

posdict

A dictionary of positions keyed by node.

Examples

>>> G = nx.grid_graph((5, 5))
>>> pos = nx.arf_layout(G)