tnss_tree: Create Steiner tree from real and dummy points

In schochastics/edgebundle: Algorithms for Bundling Edges in Networks and Visualizing Flow and Metro Maps

Create Steiner tree from real and dummy points

Description

creates an approximated Steiner tree for a flow map visualization

Usage

tnss_tree(
  g,
  xy,
  xydummy,
  root,
  gamma = 0.9,
  epsilon = 0.3,
  elen = Inf,
  order = "random"
)

Arguments

g	original flow network (must be a one-to-many flow network, i.e star graph). Must have a weight attribute indicating the flow
xy	coordinates of "real" nodes
xydummy	coordinates of "dummy" nodes
root	root node id of the flow
gamma	edge length decay parameter
epsilon	percentage of points keept on a line after straightening with Visvalingam Algorithm
elen	maximal length of edges in triangulation
order	in which order shortest paths are calculated ("random","weight","near","far")

Details

Use tnss_smooth to smooth the edges of the tree

Value

approximated Steiner tree from dummy and real nodes as igraph object

Author(s)

David Schoch

References

Sun, Shipeng. "An automated spatial flow layout algorithm using triangulation, approximate Steiner tree, and path smoothing." AutoCarto, 2016.

Examples

xy <- cbind(state.center$x, state.center$y)[!state.name %in% c("Alaska", "Hawaii"), ]
xy_dummy <- tnss_dummies(xy, root = 4)
gtree <- tnss_tree(cali2010, xy, xy_dummy, root = 4, gamma = 0.9)

schochastics/edgebundle documentation built on Sept. 25, 2024, 8:44 p.m.