spdep (version 1.1-3)

nb2lines: Use vector files for import and export of weights

Description

Use vector files for import and export of weights, storing spatial entity coordinates in the arcs, and the entity indices in the data frame.

Usage

nb2lines(nb, wts, coords, proj4string=CRS(as.character(NA)))
listw2lines(listw, coords, proj4string=CRS(as.character(NA)))
df2sn(df, i="i", i_ID="i_ID", j="j", wt="wt")

Arguments

nb

a neighbour object of class nb

wts

list of general weights corresponding to neighbours

coords

matrix of region point coordinates

proj4string

Object of class CRS; holding a valid proj4 string

listw

a listw object of spatial weights

df

a data frame read from a shapefile, derived from the output of nb2lines

i

character name of column in df with from entity index

i_ID

character name of column in df with from entity region ID

j

character name of column in df with to entity index

wt

character name of column in df with weights

Value

nb2lines and listw2lines return a SpatialLinesDataFrame object; its data slot contains a data frame with the from and to indices of the neighbour links and their weights. df2sn converts the data retrieved from reading the data from df back into a spatial.neighbour object.

Details

The maptools package function writeSpatialShape is used to transport out the list of lines made by nb2lines or listw2lines, which is a simple wrapper function. The neighbour and weights objects may be retrieved by converting the specified columns of the data slot of the SpatialLinesDataFrame object into a spatial.neighbour object, which is then converted into a weights list object.

See Also

sn2listw, readShapeLines

Examples

# 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 <- coordinates(as(columbus, "Spatial"))
res <- listw2lines(nb2listw(col.gal.nb), coords)
summary(res)
tf <- paste0(tempfile(), ".gpkg")
st_write(st_as_sf(res), dsn=tf, driver="GPKG")
inMap <- st_read(tf)
summary(inMap)
diffnb(sn2listw(df2sn(as.data.frame(inMap)))$neighbours, col.gal.nb)
# }