[R-sig-Geo] zip code map - huge files!

[hadley wickham]

Hi Enrico,

Start with county-to-csv.r - that converts the shape files to normal
csv files.  Then look at thin-all.r, which actually does the thinning
- although I see that I've forgotten to source thin-better.csv.  I
don't have any code to convert it back to into shapefiles because I
don't use them myself.

Hadley


On Sun, Apr 26, 2009 at 7:54 PM, Enrico Rossi <enrico.a.rossi at gmail.com> wrote:
> 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
> <dylan.beaudette at gmail.com> 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 <h.wickham at gmail.com> 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 <enrico.a.rossi at gmail.com> 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
>>>> R-sig-Geo at stat.math.ethz.ch
>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>>>>
>>>
>>>
>>>
>>> --
>>> http://had.co.nz/
>>>
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>>
>



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