| neig | R Documentation |
Neighbourhood Graphs
Description
neig creates objects of class neig with :
a list of edges
a binary square matrix
a list of vectors of neighbours
an integer (linear and circular graphs)
a data frame of polygons (area)
scores.neig returns the eigenvectors of neighbouring,
orthonormalized scores (null average, unit variance 1/n and null covariances) of maximal autocorrelation.
nb2neig returns an object of class neig using an object of class nb in the library ‘spdep’
neig2nb returns an object of class nb using an object of class neig
neig2mat returns the incidence matrix between edges (1 = neighbour ; 0 = no neighbour)
neig.util.GtoL and neig.util.LtoG are utilities.
Usage
neig(list = NULL, mat01 = NULL, edges = NULL,
n.line = NULL, n.circle = NULL, area = NULL)
scores.neig (obj)
## S3 method for class 'neig'
print(x, ...)
## S3 method for class 'neig'
summary(object, ...)
nb2neig (nb)
neig2nb (neig)
neig2mat (neig)
Arguments
list |
a list which each component gives the number of neighbours |
mat01 |
a symmetric square matrix of 0-1 values |
edges |
a matrix of 2 columns with integer values giving a list of edges |
n.line |
the number of points for a linear plot |
n.circle |
the number of points for a circular plot |
area |
a data frame containing a polygon set (see area.plot) |
nb |
an object of class ‘nb’ |
neig, x, obj, object |
an object of class ‘neig’ |
... |
further arguments passed to or from other methods |
Author(s)
Daniel Chessel
References
Thioulouse, J., D. Chessel, and S. Champely. 1995. Multivariate analysis of spatial patterns: a unified approach to local and global structures. Environmental and Ecological Statistics, 2, 1–14.
Examples
data(mafragh)
if (require(deldir, quietly=TRUE)) {
par(mfrow = c(2,1))
provi <- deldir(mafragh$xy)
provi.neig <- neig(edges = as.matrix(provi$delsgs[,5:6]))
s.label(mafragh$xy, neig = provi.neig, inc = FALSE,
addax = FALSE, clab = 0, cnei = 2)
dist <- apply(provi.neig, 1, function(x)
sqrt(sum((mafragh$xy[x[1],] - mafragh$xy[x[2],])^2)))
#hist(dist, nclass = 50)
mafragh.neig <- neig(edges = provi.neig[dist<50,])
s.label(mafragh$xy, neig = mafragh.neig, inc = FALSE,
addax = FALSE, clab = 0, cnei = 2)
par(mfrow = c(1,1))
data(irishdata)
irish.neig <- neig(area = irishdata$area)
summary(irish.neig)
print(irish.neig)
s.label(irishdata$xy, neig = irish.neig, cneig = 3,
area = irishdata$area, clab = 0.8, inc = FALSE)
irish.scores <- scores.neig(irish.neig)
par(mfrow = c(2,3))
for (i in 1:6) s.value(irishdata$xy, irish.scores[,i],
inc = FALSE, grid = FALSE, addax = FALSE,
neig = irish.neig,
csi = 2, cleg = 0, sub = paste("Eigenvector ",i), csub = 2)
par(mfrow = c(1,1))
a.neig <- neig(n.circle = 16)
a.scores <- scores.neig(a.neig)
xy <- cbind.data.frame(cos((1:16) * pi / 8), sin((1:16) * pi / 8))
par(mfrow = c(4,4))
for (i in 1:15) s.value(xy, a.scores[,i], neig = a.neig,
csi = 3, cleg = 0)
par(mfrow = c(1,1))
a.neig <- neig(n.line = 28)
a.scores <- scores.neig(a.neig)
par(mfrow = c(7,4))
par(mar = c(1.1,2.1,0.1,0.1))
for (i in 1:27) barplot(a.scores[,i], col = grey(0.8))
}
par(mfrow = c(1,1))
if (require(maptools, quiet = TRUE) & require(spdep, quiet = TRUE)) {
data(columbus)
par(mfrow = c(2,1))
par(mar = c(0.1,0.1,0.1,0.1))
plot(col.gal.nb, coords)
s.label(data.frame(coords), neig = neig(list = col.gal.nb),
inc = FALSE, clab = 0.6, cneig = 1)
par(mfrow = c(1,1))
data(mafragh)
maf.rel <- relativeneigh(as.matrix(mafragh$xy))
maf.rel <- graph2nb(maf.rel)
s.label(mafragh$xy, neig = neig(list = maf.rel), inc = FALSE,
clab = 0, addax = FALSE, cne = 1, cpo = 2)
par(mfrow = c(2,2))
w <- matrix(runif(100), 50, 2)
x.gab <- gabrielneigh(w)
x.gab <- graph2nb(x.gab)
s.label(data.frame(w), neig = neig(list = x.gab), inc = FALSE,
clab = 0, addax = FALSE, cne = 1, cpo = 2, sub = "relative")
x.rel <- relativeneigh(w)
x.rel <- graph2nb(x.rel)
s.label(data.frame(w), neig = neig(list = x.rel), inc = FALSE,
clab = 0, addax = FALSE, cne = 1, cpo = 2, sub = "Gabriel")
k1 <- knn2nb(knearneigh(w))
s.label(data.frame(w), neig = neig(list = k1), inc = FALSE,
clab = 0, addax = FALSE, cne = 1, cpo = 2, sub = "k nearest neighbours")
all.linked <- max(unlist(nbdists(k1, w)))
z <- dnearneigh(w, 0, all.linked)
s.label(data.frame(w), neig = neig(list = z), inc = FALSE,
clab = 0, addax = FALSE, cne = 1, cpo = 2,
sub = "Neighbourhood contiguity by distance")
}
par(mfrow = c(1,1))
Results
R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-unknown-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(ade4)
Attaching package: 'ade4'
The following object is masked from 'package:base':
within
> png(filename="/home/oogasawa/snapshot/RGM3/R_CC/result/ade4/neig.Rd_%03d_medium.png", width=480, height=480)
> ### Name: neig
> ### Title: Neighbourhood Graphs
> ### Aliases: neig neig.util.GtoL neig.util.LtoG print.neig summary.neig
> ### scores.neig nb2neig neig2nb neig2mat
> ### Keywords: utilities
>
> ### ** Examples
>
> data(mafragh)
> if (require(deldir, quietly=TRUE)) {
+ par(mfrow = c(2,1))
+ provi <- deldir(mafragh$xy)
+ provi.neig <- neig(edges = as.matrix(provi$delsgs[,5:6]))
+
+ s.label(mafragh$xy, neig = provi.neig, inc = FALSE,
+ addax = FALSE, clab = 0, cnei = 2)
+ dist <- apply(provi.neig, 1, function(x)
+ sqrt(sum((mafragh$xy[x[1],] - mafragh$xy[x[2],])^2)))
+ #hist(dist, nclass = 50)
+ mafragh.neig <- neig(edges = provi.neig[dist<50,])
+ s.label(mafragh$xy, neig = mafragh.neig, inc = FALSE,
+ addax = FALSE, clab = 0, cnei = 2)
+ par(mfrow = c(1,1))
+
+ data(irishdata)
+ irish.neig <- neig(area = irishdata$area)
+ summary(irish.neig)
+ print(irish.neig)
+ s.label(irishdata$xy, neig = irish.neig, cneig = 3,
+ area = irishdata$area, clab = 0.8, inc = FALSE)
+
+ irish.scores <- scores.neig(irish.neig)
+ par(mfrow = c(2,3))
+ for (i in 1:6) s.value(irishdata$xy, irish.scores[,i],
+ inc = FALSE, grid = FALSE, addax = FALSE,
+ neig = irish.neig,
+ csi = 2, cleg = 0, sub = paste("Eigenvector ",i), csub = 2)
+ par(mfrow = c(1,1))
+
+ a.neig <- neig(n.circle = 16)
+ a.scores <- scores.neig(a.neig)
+ xy <- cbind.data.frame(cos((1:16) * pi / 8), sin((1:16) * pi / 8))
+ par(mfrow = c(4,4))
+ for (i in 1:15) s.value(xy, a.scores[,i], neig = a.neig,
+ csi = 3, cleg = 0)
+ par(mfrow = c(1,1))
+
+ a.neig <- neig(n.line = 28)
+ a.scores <- scores.neig(a.neig)
+ par(mfrow = c(7,4))
+ par(mar = c(1.1,2.1,0.1,0.1))
+ for (i in 1:27) barplot(a.scores[,i], col = grey(0.8))
+ }
deldir 0.0-22
PLEASE NOTE: The components "delsgs" and "summary" of the
object returned by deldir() are now DATA FRAMES rather than
matrices (as they were prior to release 0.0-18).
See help("deldir").
PLEASE NOTE: The process that deldir() uses for determining
duplicated points has changed from that used in version
0.0-9 of this package (and previously). See help("deldir").
Neigbourhood undirected graph
Vertices: 25
Degrees: 5 5 4 4 1 5 3 6 5 5 5 4 4 2 3 7 3 7 7 3 8 4 6 4 4
Edges (pairs of vertices): 57
S01 .
S02 ..
S03 ...
S04 ....
S05 .....
S06 ..1...
S07 ..11...
S08 1.......
S09 1........
S10 1......11.
S11 .1..1......
S12 ..11..1.....
S13 .1........1..
S14 ..............
S15 .....1.........
S16 .1.....1.....1..
S17 .1...........1.1.
S18 .....1.1.1.....1..
S19 .....1....1.1.1..1.
S20 ..........1...1...1.
S21 ..11.1..11.1.....1...
S22 ...1....1...........1.
S23 .1.....1....1..1.11....
S24 1.......1............1..
S25 1......1.......1.......1.
> par(mfrow = c(1,1))
>
> if (require(maptools, quiet = TRUE) & require(spdep, quiet = TRUE)) {
+ data(columbus)
+ par(mfrow = c(2,1))
+ par(mar = c(0.1,0.1,0.1,0.1))
+ plot(col.gal.nb, coords)
+ s.label(data.frame(coords), neig = neig(list = col.gal.nb),
+ inc = FALSE, clab = 0.6, cneig = 1)
+ par(mfrow = c(1,1))
+
+ data(mafragh)
+ maf.rel <- relativeneigh(as.matrix(mafragh$xy))
+ maf.rel <- graph2nb(maf.rel)
+ s.label(mafragh$xy, neig = neig(list = maf.rel), inc = FALSE,
+ clab = 0, addax = FALSE, cne = 1, cpo = 2)
+
+ par(mfrow = c(2,2))
+ w <- matrix(runif(100), 50, 2)
+ x.gab <- gabrielneigh(w)
+ x.gab <- graph2nb(x.gab)
+ s.label(data.frame(w), neig = neig(list = x.gab), inc = FALSE,
+ clab = 0, addax = FALSE, cne = 1, cpo = 2, sub = "relative")
+ x.rel <- relativeneigh(w)
+ x.rel <- graph2nb(x.rel)
+ s.label(data.frame(w), neig = neig(list = x.rel), inc = FALSE,
+ clab = 0, addax = FALSE, cne = 1, cpo = 2, sub = "Gabriel")
+ k1 <- knn2nb(knearneigh(w))
+ s.label(data.frame(w), neig = neig(list = k1), inc = FALSE,
+ clab = 0, addax = FALSE, cne = 1, cpo = 2, sub = "k nearest neighbours")
+
+ all.linked <- max(unlist(nbdists(k1, w)))
+ z <- dnearneigh(w, 0, all.linked)
+ s.label(data.frame(w), neig = neig(list = z), inc = FALSE,
+ clab = 0, addax = FALSE, cne = 1, cpo = 2,
+ sub = "Neighbourhood contiguity by distance")
+ }
Checking rgeos availability: TRUE
Attaching package: 'boot'
The following object is masked from 'package:lattice':
melanoma
Attaching package: 'spdep'
The following object is masked from 'package:ade4':
mstree
> par(mfrow = c(1,1))
>
>
>
>
>
> dev.off()
null device
1
>
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