Use this if you are using igraph from R
Calculate the average nearest neighbor degree of the given vertices and the same quantity in the function of vertex degree
knn(graph, vids = V(graph), weights = NULL)
graph |
The input graph. It can be directed, but it will be treated as undirected, i.e. the direction of the edges is ignored. |
vids |
The vertices for which the calculation is performed. Normally it
includes all vertices. Note, that if not all vertices are given here, then
both ‘ |
weights |
Weight vector. If the graph has a |
Note that for zero degree vertices the answer in ‘knn
’ is
NaN
(zero divided by zero), the same is true for ‘knnk
’
if a given degree never appears in the network.
A list with two members:
knn |
A numeric vector giving the
average nearest neighbor degree for all vertices in |
knnk |
A numeric vector, its length is the maximum (total) vertex degree in the graph. The first element is the average nearest neighbor degree of vertices with degree one, etc. |
Gabor Csardi csardi.gabor@gmail.com
Alain Barrat, Marc Barthelemy, Romualdo Pastor-Satorras, Alessandro Vespignani: The architecture of complex weighted networks, Proc. Natl. Acad. Sci. USA 101, 3747 (2004)
# Some trivial ones g <- make_ring(10) knn(g) g2 <- make_star(10) knn(g2) # A scale-free one, try to plot 'knnk' g3 <- sample_pa(1000, m=5) knn(g3) # A random graph g4 <- sample_gnp(1000, p=5/1000) knn(g4) # A weighted graph g5 <- make_star(10) E(g5)$weight <- seq(ecount(g5)) knn(g5)