graph_tool.draw.sfdp_layout#

graph_tool.draw.sfdp_layout(g, vweight=None, eweight=None, pin=None, groups=None, C=0.2, K=None, p=2.0, theta=0.6, max_level=15, r=1.0, gamma=0.3, mu=2.0, kappa=1.0, rmap=None, R=1, init_step=None, cooling_step=0.95, adaptive_cooling=True, epsilon=0.01, max_iter=0, pos=None, multilevel=None, coarse_method='hybrid', mivs_thres=0.9, ec_thres=0.75, weighted_coarse=False, verbose=False)[source]#

Obtain the SFDP spring-block layout of the graph.

Parameters:
gGraph

Graph to be used.

vweightVertexPropertyMap (optional, default: None)

A vertex property map with the respective weights.

eweightEdgePropertyMap (optional, default: None)

An edge property map with the respective weights.

pinVertexPropertyMap (optional, default: None)

A vertex property map with boolean values, which, if given, specify the vertices which will not have their positions modified.

groupsVertexPropertyMap (optional, default: None)

A vertex property map with group assignments. Vertices belonging to the same group will be put close together.

Cfloat (optional, default: 0.2)

Relative strength of repulsive forces.

Kfloat (optional, default: None)

Optimal edge length. If not provided, it will be taken to be the average edge distance in the initial layout.

pfloat (optional, default: 2)

Repulsive force exponent.

thetafloat (optional, default: 0.6)

Quadtree opening parameter, a.k.a. Barnes-Hut opening criterion.

max_levelint (optional, default: 15)

Maximum quadtree level.

rfloat (optional, default: 1.)

Strength of attractive force between connected components.

gammafloat (optional, default: .3)

Strength of the repulsive force between different groups.

mufloat (optional, default: 2)

Typical length of the repulsive force between different groups.

kappafloat (optional, default: 1.0)

Multiplicative factor on the attracttive force between nodes of the same group.

rmapVertexPropertyMap (optional, default: None)

Vertex rank to be used around to order them preferentially in the \(y\) direction.

Rfloat (optional, default: 1.0)

Strength of the rank ordering in the \(y\) direction.

init_stepfloat (optional, default: None)

Initial update step. If not provided, it will be chosen automatically.

cooling_stepfloat (optional, default: 0.95)

Cooling update step.

adaptive_coolingbool (optional, default: True)

Use an adaptive cooling scheme.

epsilonfloat (optional, default: 0.01)

Relative convergence criterion.

max_iterint (optional, default: 0)

Maximum number of iterations. If this value is 0, it runs until convergence.

posVertexPropertyMap (optional, default: None)

Initial vertex layout. If not provided, it will be randomly chosen.

multilevelbool (optional, default: None)

Use a multilevel layout algorithm. If None is given, it will be activated based on the size of the graph.

coarse_methodstr (optional, default: "hybrid")

Coarsening method used if multilevel == True. Allowed methods are "hybrid", "mivs" and "ec".

mivs_thresfloat (optional, default: 0.9)

If the relative size of the MIVS coarse graph is above this value, the coarsening stops.

ec_thresfloat (optional, default: 0.75)

If the relative size of the EC coarse graph is above this value, the coarsening stops.

weighted_coarsebool (optional, default: False)

Use weighted coarse graphs.

verbosebool (optional, default: False)

Provide verbose information.

Returns:
posVertexPropertyMap

A vector-valued vertex property map with the coordinates of the vertices.

Notes

This algorithm is defined in [hu-multilevel-2005], and has complexity \(O(V\log V)\).

References

[hu-multilevel-2005]

Yifan Hu, “Efficient and High Quality Force-Directed Graph”, Mathematica Journal, vol. 10, Issue 1, pp. 37-71, (2005) http://www.mathematica-journal.com/issue/v10i1/graph_draw.html

Examples

>>> g = gt.price_network(3000)
>>> pos = gt.sfdp_layout(g)
>>> gt.graph_draw(g, pos=pos, output="graph-draw-sfdp.pdf")
<...>
../_images/graph-draw-sfdp.png

SFDP layout of a Price network.#