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Step 1: t
t +1; for each v i
= v r with parent v k calculate w i ( t ) according to the
equation dw i ( t )
dt
w i ( t )+ ˆ i ( t ) which models network synchronisation
dynamics. The term ˆ i ( t ) is an adjustment which allows larger drawing space
for subtrees rooted at nodes with a relatively high degree.
Step 2: For each pair of nodes v i
= sin( w k ( t ))
= v j , calculate the dissimilarity of their
cos( w j ( t ))) 2 +(sin( w i ( t ))
dynamic variables dis ij ( t )=max
{
L, ((cos( w i ( t ))
sin( w j ( t ))) 2 ) 2
.
Step 3: Update the coordinates of all nodes in force-directed manner. If v i and
v j are adjacent then the force of attraction between them is q
}
p ( dis ij ( t )); if
×
× ( dis ij ( t )) is the force of repulsion between
they are not adjacent then
1
them. The values of q
1 grow with the size of the tree.
Step 4: Scaling up the value of L at each iteration gradually and continuing
this process until layout gets stable (typically
1and0 <p
steps).
Figure 1 shows two trees drawn with our algorithm. The one in the left is one of
the example trees which is also drawn by Bannister et al. [2]. We have observed
that our algorithm achieves more even distribution of nodes within a circular
drawing area compared to other tree drawing algorithms. Our algorithm has the
same time complexity as the classical force-directed graph drawing algorithms,
i.e. O ( m
|
V
|
2 ), where m is the number of iterations.
|
V
|
Fig. 1. A tree with 70 nodes (right) and a tree with 82 nodes (left). Nodes have different
size and color depending on the distance to the root.
References
1. Arenas, A., Daz-Guilera, A., Prez-Vicente, C.J.: Synchronization reveals topological
scales in complex networks. Phys. Rev. Lett. 96(11), 114102-1-114102-4 (2006)
2. Bannister, M.J., Eppstein, D., Goodrich, M.T., Trott, L.: Force-directed graph draw-
ing using social gravity and scaling. In: Didimo, W., Patrignani, M. (eds.) GD 2012.
LNCS, vol. 7704, pp. 414-425. Springer, Heidelberg (2013)
 
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