Michael Friendly wrote:
Two short questions about working with maps:
1. I'm reading a shapefile with character labels for the regions
(FSA). I can add the labels using plot(),
but when I try the same thing using spplot(), the labels are in the
wrong positions -- they all seem to be
shrunk somewhat in toward the center of the map. What am I doing wrong?
library(maptools)
# using readShapeSpatial
ontario
<-readShapeSpatial("ForwardSortationAreas_JUL07_ON_region.shp",
IDvar="FSA", proj4string=CRS("+proj=longlat +datum=NAD83") )
toronto <- ontario[ontario$F=="M",]
summary(toronto)
# this works OK
plot(toronto)
text(coordinates(toronto), labels=as.character(toronto$FSA), cex=0.4)
# this doesn't work-- labels in wrong position
spplot(toronto,"FSA_NAME", colorkey=FALSE)
text(coordinates(toronto), labels=as.character(toronto$FSA), cex=0.4)
Right: text() works with base graphics, not with lattice on which spplot
is built.
Something like this should work:
spplot(toronto,"FSA_NAME", colorkey=FALSE,
sp.layout = list("sp.text", coordinates(toronto),
as.character(toronto$FSA), cex=0.4))
2. I have a bunch of attribute variables for the geographic regions,
all on different scales. Id like to
produce a set of comparative maps in the same figure (say with
spplot()) with each attribute shaded
by its quantiles, e.g., 5 classes each. Do I have to precompute these
first, or is there something I can do in the call
to spplot() to have this done, using the variables in the
SpatialPolygonsDataFrame?
What exactly did you mean by "all on different scales"? They have
different polygon structures?
--
Edzer
> toronto <- spCbind(toronto, crimeTO)
> summary(toronto)
Object of class SpatialPolygonsDataFrame
Coordinates:
min max
r1 -79.63925 -79.11484
r2 43.58103 43.85547
Is projected: FALSE
proj4string : [+proj=longlat +datum=NAD83]
Data attributes:
FSA FSA_NAME F PR Area
Jail.Cost Rank M1B : 1 TORONTO :48 K: 0
35:102 Toronto :39 Min. : 0 Min. : 6.0 M1C : 1
NORTH YORK :22 L: 0 North York :24 1st Qu.: 3205
1st Qu.:126.8 M1E : 1 SCARBOROUGH:17 M:102
Scarborough:17 Median : 42249 Median :296.5 M1G : 1
ETOBICOKE :12 N: 0 Etobicoke :12 Mean : 84991
Mean :259.7 M1H : 1 EAST YORK : 3 P: 0 East
York : 5 3rd Qu.:139404 3rd Qu.:406.0 M1J : 1 ACTON :
0 York : 5 Max. :506339 Max. :413.0
(Other):96 (Other) : 0 (Other) :
0 Inmates Inmates.per.10K
Days.Sentenced Population Household.Income
Min. : 0.000 Min. :0.000 Min. : 0.0 Min. : 0
Min. : 35129 1st Qu.: 1.000 1st Qu.:0.325 1st Qu.: 30.0 1st
Qu.:15857 1st Qu.: 48438 Median : 3.000 Median :1.000 Median :
395.5 Median :23564 Median : 58015 Mean : 3.559 Mean
:1.180 Mean : 795.6 Mean :25161 Mean : 62123 3rd Qu.:
5.000 3rd Qu.:1.800 3rd Qu.:1305.0 3rd Qu.:34878 3rd Qu.:
66259 Max. :15.000 Max. :4.300 Max. :4740.0 Max.
:66878 Max. :127669
NA's : 5 Low.Income Unemployed University
Female.Homes Public.Housing
Min. : 6.00 Min. :2.000 Min. : 8.00 Min. : 8.00 Min.
: 2 1st Qu.:15.00 1st Qu.:4.000 1st Qu.:20.00 1st Qu.:13.00
1st Qu.: 234 Median :20.00 Median :5.000 Median :28.00 Median
:16.00 Median : 685 Mean :20.05 Mean :5.412 Mean :31.31
Mean :16.16 Mean : 995 3rd Qu.:25.00 3rd Qu.:7.000 3rd
Qu.:45.00 3rd Qu.:19.00 3rd Qu.:1276 Max. :41.00 Max.
:9.000 Max. :64.00 Max. :30.00 Max. :9289 NA's : 5.00
NA's :5.000 NA's : 5.00 NA's : 5.00 NA's : 27 >
--
Edzer Pebesma
Institute for Geoinformatics (ifgi), University of Münster,
Weseler Straße 253, 48151 Münster, Germany. Phone: +49 251
8333081, Fax: +49 251 8339763 http://ifgi.uni-muenster.de/
_______________________________________________
R-sig-Geo mailing list
[email protected]
https://stat.ethz.ch/mailman/listinfo/r-sig-geo
