[R-sig-Geo] zip code map - huge files!
h.wickham at gmail.com
Mon Apr 27 04:37:21 CEST 2009
Yes, this is basically the method that my code implements, although I
definitely preserve all junction points, and it's not clear from the
description whether v.generalize does or not.
On Sun, Apr 26, 2009 at 6:13 PM, Dylan Beaudette
<dylan.beaudette at gmail.com> wrote:
> You can use the v.generalize command in GRASS to reduce the complexity
> of vectors like these.
> 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
>> On Sun, Apr 26, 2009 at 3:06 PM, Enrico Rossi <enrico.a.rossi at gmail.com> wrote:
>>> 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
>>> zip<-readShapePoly("tl_2008_us_zcta5") # This takes a while!
>>> val<-runif(length(zip[])) # there are about 32000 zip codes
>>> 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
>>> # This also takes too long, I never got any output out of it
>>> Many thanks!
>>> Enrico Rossi
>>> R-sig-Geo mailing list
>>> R-sig-Geo at stat.math.ethz.ch
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