[R-sig-Geo] How to check a large neighbourhood matrix?

[Oscar Breugelmans]

Roger and Danlin:

Thanks for your help on this. This is the code I used to create and plot
the nb:

pc4.02=readShapePoly("..../pc4_2002/pc4_gebieden_2002",IDvar="PC4NR")
nb.pc4.02=poly2nb(pc4.02,snap=0.01)
coords=coordinates(pc4.02)
plot(pc4.02)
plot.nb(nb.pc4.02,coords,add=T)
summary(nb.pc4.02)

>From Roger's comments I understand that there is no easy way to zoom in on
this plot. I wanted to specifically zoom in on the plot.nb() because it
shows the connections between the neighbours. I was able to check all the
areas with only 1 neighbour, but was afraid that there would be areas that
had only some of its neighbours assigned correctly. I will try to use xlim=
en ylim= to zoom in on the plot. I think writeOGR() is not really an option
because it will not show the lines connecting the neighbours that plot.nb()
so nicely does.

Oscar




On Thu, 27 Mar 2008, Danlin Yu wrote:

> Oscar:
>
> If you produced the nb list in R, you can always summarize the nb list
> to see whether there are units that don't have neighbors.
>
> For instance:
> #loading spdep
> library(spdep)
>
> #you have read a shapefile of postal code areas:
>
> post<-read.shape("../yourshapefile.shp")
>
> #since it is a polygon shapefile, a Map2poly and poly2nb function shall
> do the trick (Roger will have better ideas than my naive ones)
>
> post.nb<-poly2nb(Map2poly(post))

I think that Oscar had got this far using the prefered sp object:

SPDF <- readShapePoly()

nb <- poly2nb(SPDF)

but had needed to use the snap= argument to poly2nb() to overcome slivers
in his polygons.

>
> #then you summarize the nb list:
>
> summary(post.nb)
>

This helps, because it says which have no neighbours. It will indicate how
to "zoom" in on the plot for the locations of the polygons. To actually
"zoom", use xlim= and ylim= in the plot method for nb objects.

If you want real control, consider writeOGR(SPDF, ..., driver="KML") in
the rgdal package, and equivalently writeOGR() of the
SpatialLinesDataFrame output by nb2lines(), and zoom to your satisfaction
in GE using KML files.

Roger

> The summary command will give you the characteristics of the neighbor
> list object, including Number of regions, Number of nonzero links,
> Percentage nonzero weights, Average number of links, regions that have
> no links (which shall give you the idea whether or not some postal code
> areas are connected) and the most and least connected regions
>
> Hope this helps.
>
> Regards,
> Dr. Danlin Yu