spdep: nb2lines – R documentation

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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=NULL, as_sf=FALSE)
listw2lines(listw, coords, proj4string=NULL, as_sf=FALSE)
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, a `Spatial` object (points or polygons), or an `sfc` object (points or polygons)
`proj4string`	default NULL; if `coords` is a Spatial or sf object, this value will be used, otherwise the value will be converted appropriately
`as_sf`	output object in `Spatial` or `sf` format, default FALSE, set to TRUE if coords is an `sfc` object and FALSE if a `Spatial` object
`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

Details

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.

Value

nb2lines and listw2lines return a SpatialLinesDataFrame object or an sf object; the data frame contains 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.

Note

Original idea due to Gidske Leknes Andersen, Department of Biology, University of Bergen, Norway

Author(s)

Roger Bivand Roger.Bivand@nhh.no

Examples

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])
res <- listw2lines(nb2listw(col.gal.nb), st_geometry(columbus))
summary(res)
tf <- paste0(tempfile(), ".gpkg")
st_write(res, dsn=tf, driver="GPKG")
inMap <- st_read(tf)
summary(inMap)
diffnb(sn2listw(df2sn(as.data.frame(inMap)))$neighbours, col.gal.nb)
res1 <- listw2lines(nb2listw(col.gal.nb), as(columbus, "Spatial"))
summary(res1)

spdep

Spatial Dependence: Weighting Schemes, Statistics

v1.1-11

GPL (>= 2)

Authors

Roger Bivand [cre, aut] (<https://orcid.org/0000-0003-2392-6140>), Micah Altman [ctb], Luc Anselin [ctb], Renato Assunção [ctb], Olaf Berke [ctb], Andrew Bernat [ctb], Guillaume Blanchet [ctb], Eric Blankmeyer [ctb], Marilia Carvalho [ctb], Bjarke Christensen [ctb], Yongwan Chun [ctb], Carsten Dormann [ctb], Stéphane Dray [ctb], Virgilio Gómez-Rubio [ctb], Martin Gubri [ctb], Rein Halbersma [ctb], Elias Krainski [ctb], Pierre Legendre [ctb], Nicholas Lewin-Koh [ctb], Angela Li [ctb], Hongfei Li [ctb], Jielai Ma [ctb], Abhirup Mallik [ctb, trl], Giovanni Millo [ctb], Werner Mueller [ctb], Hisaji Ono [ctb], Pedro Peres-Neto [ctb], Gianfranco Piras [ctb], Markus Reder [ctb], Jeff Sauer [ctb], Michael Tiefelsdorf [ctb], René Westerholt [ctb], Levi Wolf [ctb], Danlin Yu [ctb]

Initial release

2021-09-07