Hi all, Thanks for your responses! Dylan, unfortunately I can't install GRASS (although I'm working on getting it approved). Hadley, your code sounds very promising. Which bit of code should I look at? thin? thin-better? Will these methods work with SpatialPoly objects?
Many thanks, Enrico On Sun, Apr 26, 2009 at 7:13 PM, Dylan Beaudette <[email protected]> wrote: > Hi, > > You can use the v.generalize command in GRASS to reduce the complexity > of vectors like these. > > Cheers, > Dylan > > On Sun, Apr 26, 2009 at 3:53 PM, hadley wickham <[email protected]> wrote: >> Hi Enrico, >> >> I have some code to do map generalisation (reducing map resolution >> without visible loss in detail) at >> http://github.com/hadley/data-counties/tree/master. It's applied to >> counties data, but would be trivial (if slow) to modify to work with >> zip codes instead >> >> Hadley >> >> On Sun, Apr 26, 2009 at 3:06 PM, Enrico Rossi <[email protected]> >> wrote: >>> Hello, >>> >>> I have some data at the zip code level, and I'm using the shapefiles >>> downloaded from the Census TigerLine website >>> (http://www2.census.gov/geo/tiger/TIGER2008/tl_2008_us_zcta5.zip) to >>> plot a shaded map of the US. However, the files generated in this way >>> are enormous, and take a long time to process, even on a fast machine >>> with lots of memory. I'm wondering if there's a more efficient way to >>> do this. Maybe rasterize before plotting somehow? >>> >>> If anyone on this list has experience working with zip-level data, I'd >>> appreciate any advice. >>> >>> Here's some example code like what I'm doing: >>> >>> # This works, and produces a 1.2GB PDF file! After it's done, I can >>> rasterize it using gs to reduce file size, but it takes almost an hour >>> library(maptools) >>> zip<-readShapePoly("tl_2008_us_zcta5") # This takes a while! >>> val<-runif(length(zip[[1]])) # there are about 32000 zip codes >>> pdf("zipplot.pdf") >>> plot(zip,xlim=c(-130,-65),ylim=c(20,50),col=grey(val),lty=0) >>> dev.off() >>> system("gs -dSAFER -dBATCH -dNOPAUSE -sDEVICE=png16m -r300 >>> -dTextAlphaBits=4 -dGraphicsAlphaBits=4 -dMaxStripSize=8192 >>> -sOutputFile=zipplot.png zipplot.pdf") >>> >>> # I've tried plotting directly to png, but it just seems to hang, my >>> patience ran out after two hours >>> png("zipplot.png") >>> plot(zip,xlim=c(-130,-65),ylim=c(20,50),col=grey(val),lty=0) >>> dev.off() >>> >>> # This also takes too long, I never got any output out of it >>> library(lattice) >>> zip$val<-val >>> pdf("zipplot2.pdf") >>> spplot(zip,"val",xlim=c(-130,-65),ylim=c(20,50),lty=0) >>> dev.off() >>> >>> Many thanks! >>> Enrico Rossi >>> >>> _______________________________________________ >>> R-sig-Geo mailing list >>> [email protected] >>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo >>> >> >> >> >> -- >> http://had.co.nz/ >> >> _______________________________________________ >> R-sig-Geo mailing list >> [email protected] >> https://stat.ethz.ch/mailman/listinfo/r-sig-geo >> > _______________________________________________ R-sig-Geo mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-geo
