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The function identifies neighbours of region points by Euclidean distance between lower (greater than or equal to (changed from version 1.1-7)) and upper (less than or equal to) bounds, or with longlat = TRUE, by Great Circle distance in kilometers.
dnearneigh(x, d1, d2, row.names = NULL, longlat = NULL, bounds=c("GE", "LE"),
use_kd_tree=TRUE, symtest=FALSE, use_s2=FALSE, max_cells=200, dwithin=FALSE)matrix of point coordinates, an object inheriting from SpatialPoints or an "sf" or "sfc" object; if the "sf" or "sfc" object geometries are in geographical coordinates (use_s2=FALSE, sf::st_is_longlat(x) == TRUE and sf::sf_use_s2() == TRUE), s2 will be used to find the neighbours because it will (we hope) use spatial indexing https://github.com/r-spatial/s2/issues/125 as opposed to the legacy method which uses brute-force (at present s2 also uses brute-force)
lower distance bound
upper distance bound
character vector of region ids to be added to the neighbours list as attribute region.id, default seq(1, nrow(x))
TRUE if point coordinates are longitude-latitude decimal degrees, in which case distances are measured in kilometers; if x is a SpatialPoints object, the value is taken from the object itself, and overrides this argument if not NULL
character vector of length 2, default c("GE", "LE"), (GE: greater than or equal to, LE: less than or equal to) that is the finite and closed interval [d1, d2], d1 <= x <= d2. The first element may also be "GT" (GT: greater than), the second "LT" (LT: less than) for finite, open intervals excluding the bounds; the first bound default was changed from "GT" to "GE" in release 1.1-7. When creating multiple distance bands, finite, half-open right-closed intervals may be used until the final interval to avoid overlapping on bounds: "GE", "LT", that is [d1, d2), d1 <= x < d2
default TRUE, if TRUE, use dbscan frNN if available (permitting 3D distances).
Default FALSE; before release 1.1-7, TRUE - run symmetry check on output object, costly with large numbers of points.
default=FALSE, as of s2 1.0-5, distance bound compuations do not use spatial indexing so even if sf::sf_use_s2() is TRUE, s2 will not be used for distances on the sphere for "sf" or "sfc" objects; the default will change when/if spatial indexing becomes available. Until then, setting set.coresOption to a positive integer will experimentaly use that number of cores on .Platform$OS.type== "unix" systems.
default 200; if use_s2=TRUE, sf::st_is_longlat(x) == TRUE, sf::sf_use_s2() == TRUE and dwithin=FALSE, set max_cells in s2::s2_buffer_cells()
default FALSE to use s2::s2_buffer_cells() and s2::s2_intersects_matrix(), if TRUE, use s2::s2_dwithin_matrix(), both if use_s2=TRUE, sf::st_is_longlat(x) == TRUE and sf::sf_use_s2() == TRUE; both yield the same lists of neighbours.
The function returns a list of integer vectors giving the region id numbers
for neighbours satisfying the distance criteria. See card for details of “nb” objects.
# NOT RUN {
columbus <- st_read(system.file("shapes/columbus.shp", package="spData")[1], quiet=TRUE)
coords <- st_centroid(st_geometry(columbus), of_largest_polygon=TRUE)
rn <- row.names(columbus)
k1 <- knn2nb(knearneigh(coords))
all.linked <- max(unlist(nbdists(k1, coords)))
col.nb.0.all <- dnearneigh(coords, 0, all.linked, row.names=rn)
summary(col.nb.0.all, coords)
opar <- par(no.readonly=TRUE)
plot(st_geometry(columbus), border="grey", reset=FALSE,
main=paste("Distance based neighbours 0-", format(all.linked), sep=""))
plot(col.nb.0.all, coords, add=TRUE)
par(opar)
(sfc_obj <- st_centroid(st_geometry(columbus)))
col.nb.0.all_sf <- dnearneigh(sfc_obj, 0, all.linked, row.names=rn)
all.equal(col.nb.0.all, col.nb.0.all_sf, check.attributes=FALSE)
data(state)
us48.fipsno <- read.geoda(system.file("etc/weights/us48.txt",
package="spdep")[1])
if (as.numeric(paste(version$major, version$minor, sep="")) < 19) {
m50.48 <- match(us48.fipsno$"State.name", state.name)
} else {
m50.48 <- match(us48.fipsno$"State_name", state.name)
}
xy <- as.matrix(as.data.frame(state.center))[m50.48,]
llk1 <- knn2nb(knearneigh(xy, k=1, longlat=FALSE))
(all.linked <- max(unlist(nbdists(llk1, xy, longlat=FALSE))))
ll.nb <- dnearneigh(xy, 0, all.linked, longlat=FALSE)
summary(ll.nb, xy, longlat=TRUE, scale=0.5)
gck1 <- knn2nb(knearneigh(xy, k=1, longlat=TRUE))
(all.linked <- max(unlist(nbdists(gck1, xy, longlat=TRUE))))
gc.nb <- dnearneigh(xy, 0, all.linked, longlat=TRUE)
summary(gc.nb, xy, longlat=TRUE, scale=0.5)
plot(ll.nb, xy)
plot(diffnb(ll.nb, gc.nb), xy, add=TRUE, col="red", lty=2)
title(main="Differences Euclidean/Great Circle")
xy1 <- SpatialPoints((as.data.frame(state.center))[m50.48,],
proj4string=CRS("+proj=longlat +ellps=GRS80"))
gck1a <- knn2nb(knearneigh(xy1, k=1))
(all.linked <- max(unlist(nbdists(gck1a, xy1))))
gc.nb <- dnearneigh(xy1, 0, all.linked)
summary(gc.nb, xy1, scale=0.5)
xy1 <- st_as_sf((as.data.frame(state.center))[m50.48,], coords=1:2,
crs=st_crs("+proj=longlat +ellps=GRS80"))
old_use_s2 <- sf_use_s2()
sf_use_s2(TRUE)
gck1b <- knn2nb(knearneigh(xy1, k=1))
system.time(o <- nbdists(gck1b, xy1))
(all.linked <- max(unlist(o)))
# use s2 brute-force buffer/intersect approach (with two passes if d1 > 0)
system.time(gc.nb <- dnearneigh(xy1, 0, all.linked, use_s2=TRUE))
summary(gc.nb, xy1, scale=0.5)
# use s2 brute-force buffer/intersect approach with smaller max_cells
system.time(gc.nb <- dnearneigh(xy1, 0, all.linked, use_s2=TRUE, max_cells=500))
summary(gc.nb, xy1, scale=0.5)
# use s2 brute-force dwithin_matrix approach
system.time(gc.nb <- dnearneigh(xy1, 0, all.linked, use_s2=TRUE, dwithin=TRUE))
summary(gc.nb, xy1, scale=0.5)
# use legacy symmetric brute-force approach
system.time(gc.nb <- dnearneigh(xy1, 0, all.linked))
summary(gc.nb, xy1, scale=0.5)
sf_use_s2(old_use_s2)
# }
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