compon: Depth First Search on Neighbor Lists

In r-spatial/spdep: Spatial Dependence: Weighting Schemes, Statistics

Depth First Search on Neighbor Lists

Description

n.comp.nb() finds the number of disjoint connected subgraphs in the graph depicted by nb.obj - a spatial neighbours list object.

Usage

n.comp.nb(nb.obj)

Arguments

nb.obj

a neighbours list object of class nb

Details

If attr(nb.obj, "sym") is FALSE and igraph::components is available, the components of the directed graph will be found by a simple breadth-first search; if igraph::components is not available, the object will be made symmetric (which may be time-consuming with large numbers of neighbours) and the components found by depth-first search. If attr(nb.obj, "sym") is TRUE, the components of the directed graph will be found by depth-first search. The time complexity of algorithms used in native code and through igraph::components is linear in the sum of the number of nodes and the number of edges in the graph, see https://github.com/r-spatial/spdep/issues/160 for details; very dense neighbour objects will have large numbers of edges.

Value

A list of:

nc	number of disjoint connected subgraphs
comp.id	vector with the indices of the disjoint connected subgraphs that the nodes in nb.obj belong to

Author(s)

Nicholas Lewin-Koh [e-mail]

See Also

plot.nb

Examples

columbus <- st_read(system.file("shapes/columbus.gpkg", package="spData")[1], quiet=TRUE)
col.gal.nb <- read.gal(system.file("weights/columbus.gal", package="spData")[1])
coords <- st_coordinates(st_centroid(st_geometry(columbus)))
plot(col.gal.nb, coords, col="grey")
col2 <- droplinks(col.gal.nb, 21)
res <- n.comp.nb(col2)
table(res$comp.id)
plot(col2, coords, add=TRUE)
points(coords, col=res$comp.id, pch=16)
run <- FALSE
if (require("igraph", quietly=TRUE) && require("spatialreg", quietly=TRUE)) run <- TRUE
if (run) {
B <- as(nb2listw(col2, style="B", zero.policy=TRUE), "CsparseMatrix")
g1 <- graph_from_adjacency_matrix(B, mode="undirected")
c1 <- components(g1)
print(c1$no == res$nc)
}
if (run) {
print(all.equal(c1$membership, res$comp.id))
}
if (run) {
print(all.equal(c1$csize, c(table(res$comp.id)), check.attributes=FALSE))
}
if (run) {
W <- as(nb2listw(col2, style="W", zero.policy=TRUE), "CsparseMatrix")
g1W <- graph_from_adjacency_matrix(W, mode="directed", weighted="W")
c1W <- components(g1W, mode="weak")
print(all.equal(c1W$membership, res$comp.id, check.attributes=FALSE))
}

if (run) {
data(house, package="spData")
house <- sf::st_as_sf(house)
k6 <- knn2nb(knearneigh(house, k=6))
is.symmetric.nb(k6)
}
if (run) {
print(k6)
}
if (run) {
length(k6) + sum(card(k6))
}
if (run) {
# no pre-computed graph components
str(attr(k6, "ncomp"))
}
if (run) {
# raising the subgraph compute ceiling to above |N|+|E| computes and stores the
# object in the neighbour object
set.SubgraphCeiling(180000L)
k6 <- knn2nb(knearneigh(house, k=6))
str(attr(k6, "ncomp"))
}
if (run) {
print(k6)
}
if (run) {
system.time(udir <- n.comp.nb(make.sym.nb(k6)))
}
if (run) {
system.time(dir <- n.comp.nb(k6))
}
if (run) {
udir$nc
}
if (run) {
dir$nc
}
if (run) {
all.equal(dir, udir)
}

r-spatial/spdep documentation built on Dec. 3, 2024, 3:27 a.m.