Maps in R

Apologies in advance from an R newbie if this is a dumb question. Is it
possible to produce choropleth maps in R? I gather from some nice research
papers on the AT&T (sorry, Lucent) S web site that in S (and S Plus) there
is a map() function which uses arrays of polylines and regions to draw map
borders and then fill them with patterns or shades according to some scalar
quantity. We currently produce such maps (of disease rates) using PROC GMAP
in SAS/GRAPH which also uses the same sort of polyline format for definition
of the areas. The problem in SAS is that although the colours and sharding
can be precisely controlled, the means of allocating those colours to
regions on the map or ranges in the data stinks.

If the map() function hasn't been implemented in R, are there any plans?

I am most of the way through porting the Becker/Wilks code to R and I will
be finishing this some time in the next few months.  Fritz Leisch has also
expressed an interest and I passed what I had along to him. The remaining
problems to solve are:

  1. Thinning the polygons which make up the map (so they will print in
      postscript).

  2. Assembling a reasonable collection of map projections.

There is nothing difficult in this, its just a matter of finding a few
days to do the job.

In addition I'm looking at putting a better set of maps together (I'm
expecting the US National Imagery and Mapping Agency 4 CD set to show up
on my doorstep at any minute).

If you have Java expertise available, you might also want to have a look
at Openmap from BBN <http://openmap.bbn.com>.  It looks like a pretty good
framework for doing high-quality mapping work. Now if we just had that
R/Java link which John Chambers and Duncan Temple Lang are working on ...

I must say that we have been mightily impressed by the scope and stability
of R. We are using it under Win NT at present but we are about to set it up
on a Linux box. I am very much hoping that we can spend this year's
discretionary budget on a nice new and fast Linux box (stuffed with RAM) for
running R rather than spending the same amount on two S Plus licenses for
Windows (which are not exactly cheap since we are a government department,
although since we started paying for SAS each year nothing shocks us any
more...).

I know the feeling, though we fare a little better because we are
educational.  My department is however looking into getting SAS Data
Enterprise Miner -- which should effectively absorb any amount of budget
excess we might have.

	Ross

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