The "gwt" functions read and write GeoDa GWT files (the example file baltk4.GWT was downloaded from the site given in the reference), and the "dat" functions read and write Matlab sparse matrix files as used by James LeSage's Spatial Econometrics Toolbox (the example file wmat.dat was downloaded from the site given in the reference). The body of the files after any headers should have three columns separated by white space, and the third column must be numeric in the locale of the reading platform (correct decimal separator).

read.gwt2nb(file, region.id=NULL)
write.sn2gwt(sn, file, shpfile=NULL, ind=NULL, useInd=FALSE, legacy=FALSE)
read.dat2listw(file)
write.sn2dat(sn, file)

Arguments

file

name of file with weights data

region.id

region IDs

sn

a spatial.neighbour object

shpfile

character string: if not given Shapefile name taken from GWT file for this dataset

ind

character string: region id indicator field name

useInd

default FALSE, if TRUE, write region.id attribute ID key tags to output file (use in OpenGeoDa will depend on the shapefile having the field named in the ind argument matching the exported tags)

legacy

default FALSE; if TRUE, header has single field with number of observations only

Details

Attempts to honour the region.id argument given when reading GWT files. If the region IDs given in region.id= do not match the origins or destinations in the GWT file, an error will be thrown reporting Error: !anyNA(reg*dij) is not TRUE where '*' may be ‘o’ for origins or ‘d’ for destinations.

Value

read.gwt2nb returns a neighbour "nb" object with the generalised weights stored as a list element called "dlist" of the "GeoDa" attribute.

References

Luc Anselin (2003) GeoDa 0.9 User's Guide, pp. 80--81, Spatial Analysis Laboratory, Department of Agricultural and Consumer Economics, University of Illinois, Urbana-Champaign, http://geodacenter.github.io/docs/geoda093.pdf; also http://spatial-econometrics.com/data/contents.html

Author

Roger Bivand Roger.Bivand@nhh.no

See also

Examples

data(baltimore, package="spData")
STATION <- baltimore$STATION
gwt1 <- read.gwt2nb(system.file("weights/baltk4.GWT", package="spData")[1],
 STATION)
#> Warning: 102, 115, 208 are not destinations
cat(paste("Neighbours list symmetry;", is.symmetric.nb(gwt1, FALSE, TRUE),
 "\n"))
#> Neighbours list symmetry; FALSE 
listw1 <- nb2listw(gwt1, style="B", glist=attr(gwt1, "GeoDa")$dist)
tmpGWT <- tempfile()
write.sn2gwt(listw2sn(listw1), tmpGWT)
gwt2 <- read.gwt2nb(tmpGWT, STATION)
#> Warning: 102, 115, 208 are not destinations
cat(paste("Neighbours list symmetry;", is.symmetric.nb(gwt2, FALSE, TRUE),
 "\n"))
#> Neighbours list symmetry; FALSE 
diffnb(gwt1, gwt2)
#> Neighbour list object:
#> Number of regions: 211 
#> Number of nonzero links: 0 
#> Percentage nonzero weights: 0 
#> Average number of links: 0 
#> 211 regions with no links:
#> 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
#> 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
#> 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75
#> 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
#> 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117
#> 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135
#> 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153
#> 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171
#> 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189
#> 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207
#> 208 209 210 211
data(oldcol)
tmpMAT <- tempfile()
COL.W <- nb2listw(COL.nb)
write.sn2dat(listw2sn(COL.W), tmpMAT)
listwmat1 <- read.dat2listw(tmpMAT)
diffnb(listwmat1$neighbours, COL.nb, verbose=TRUE)
#> Warning: region.id differ; using ids of first list
#> Neighbour list object:
#> Number of regions: 49 
#> Number of nonzero links: 0 
#> Percentage nonzero weights: 0 
#> Average number of links: 0 
#> 49 regions with no links:
#> 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
#> 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
listwmat2 <- read.dat2listw(system.file("etc/weights/wmat.dat", 
 package="spdep")[1])
diffnb(listwmat1$neighbours, listwmat2$neighbours, verbose=TRUE)
#> Neighbour list object:
#> Number of regions: 49 
#> Number of nonzero links: 0 
#> Percentage nonzero weights: 0 
#> Average number of links: 0 
#> 49 regions with no links:
#> 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
#> 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49