Precompute distances? Speeds up some graphs, takes up memory.
preGraph
Precomputed graph, taken as a super-graph
Details
Several edge definitions are supported:
geometric
par=numeric>0. Geometric graph, par = connection radius.
knn
par=integer>0. k-nearest neighbours graph, par = k.
mass_geometric
Connect two points if ||x-y||<m(x). par=vector giving the m(x_i)'s
markcross
Connect two points if ||x-y||<m(x)+m(y). par = vector giving the m(x_i)'s
gabriel
Gabriel graph. Additional parameter for allowing par=k instead of 0 points in the circle.
MST
Minimal spanning tree.
SIG
Spheres of Influence.
RST
Radial spanning tree, par=origin of radiation, coordinate vector
RNG
Relative neighbourhood graph
CCC
Class-Cover-Catch, par=factor vector of point types. The factor vector is converted to integers according to R's internal representation of factors, and the points with type 1 will be the target. Use relevel to change the target.
The parameter 'maxR' can be given to bring n^3 graphs closer to n^2. k-nearest neighbours will warn if
maxR is too small (<k neighbours for some points), others, like RNG, don't so be careful.
Voronoi diagram aka Delaunay triangulation is not supported as other R-packages can do it,
see. e.g. package 'deldir'.