The function builds a neighbours list based on regions with contiguous boundaries, that is sharing one or more boundary point. The current function is in part interpreted and may run slowly for many regions or detailed boundaries, but from 0.2-16 should not fail because of lack of memory when single polygons are built of very many border coordinates.
poly2nb(pl, row.names = NULL, snap=sqrt(.Machine$double.eps),
queen=TRUE, useC=TRUE, foundInBox=NULL, small_n=500)list of polygons of class extending SpatialPolygons, or an sf or sfc object containing non-empty (multi-)polygon objects
character vector of region ids to be added to the neighbours list as attribute region.id, default seq(1, nrow(x)); if pl has row.names, they are used instead of the default sequence.
boundary points less than snap distance apart are considered to indicate contiguity
if TRUE, a single shared boundary point meets the contiguity condition, if FALSE, more than one shared point is required; note that more than one shared boundary point does not necessarily mean a shared boundary line
default TRUE, doing the work loop in C, may be set to false to revert to R code calling two C functions in an n*k work loop, where k is the average number of candidate neighbours
default NULL using R code, possibly parallelised if a snow cluster is available, otherwise a list of length (n-1) with integer vectors of candidate neighbours (j > i), or NULL if all candidates were (j < i) (as created by the poly_findInBoxGEOS function in rgeos for clean polygons)
default 500; if foundInBox= is not given, generate internally using sf code if the number of geometries >= small_n. If the geometries are not clean, set to a value larger than the geometry count.
A neighbours list with class nb. See card for details of “nb” objects.
# NOT RUN {
columbus <- st_read(system.file("shapes/columbus.shp", 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)))
xx <- poly2nb(as(columbus, "Spatial"))
dxx <- diffnb(xx, col.gal.nb)
plot(st_geometry(columbus), border="grey")
plot(col.gal.nb, coords, add=TRUE)
plot(dxx, coords, add=TRUE, col="red")
title(main=paste("Differences (red) in Columbus GAL weights (black)",
"and polygon generated queen weights", sep="\n"), cex.main=0.6)
# poly2nb with sf sfc_MULTIPOLYGON objects
sf_xx <- poly2nb(columbus)
diffnb(sf_xx, xx)
sfc_xx <- poly2nb(st_geometry(columbus))
diffnb(sfc_xx, xx)
xxx <- poly2nb(as(columbus, "Spatial"), queen=FALSE)
dxxx <- diffnb(xxx, col.gal.nb)
plot(st_geometry(columbus), border = "grey")
plot(col.gal.nb, coords, add = TRUE)
plot(dxxx, coords, add = TRUE, col = "red")
title(main=paste("Differences (red) in Columbus GAL weights (black)",
"and polygon generated rook weights", sep="\n"), cex.main=0.6)
cards <- card(xx)
maxconts <- which(cards == max(cards))
if(length(maxconts) > 1) maxconts <- maxconts[1]
fg <- rep("grey", length(cards))
fg[maxconts] <- "red"
fg[xx[[maxconts]]] <- "green"
plot(st_geometry(columbus), col=fg)
title(main="Region with largest number of contiguities", cex.main=0.6)
nc.sids <- st_read(system.file("shapes/sids.shp", package="spData")[1], quiet=TRUE)
system.time(xxnb <- poly2nb(nc.sids))
system.time(xxnb <- poly2nb(as(nc.sids, "Spatial")))
plot(st_geometry(nc.sids))
plot(xxnb, coordinates(as(nc.sids, "Spatial")), add=TRUE, col="blue")
sq <- st_polygon(list(rbind(c(0,0), c(1,0), c(1,1), c(0,1), c(0,0))))
sq2 <- sq + c(0,1)
sq3 <- sq + c(1,0)
sq4 <- sq + c(1,1)
gm <- st_sfc(list(sq, sq2, sq3, sq4))
df <- st_as_sf(gm, id=1:4)
plot(st_geometry(df))
text(st_coordinates(st_centroid(gm)), as.character(df$id))
unclass(poly2nb(df, queen = FALSE))
# }
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