[R] create separate plots by factors

[David M Smith]

If you want to use foreach to do the looping, you can use the "isplit"
function to create an iterator returning blocks of data, each block
being the data for one site:

> require(foreach)
> site.data <- read.table("isplit-data.txt",header=T) # data copied from email
> sites <- isplit(site.data,site.data$site)

You can see how the iterator works with nextElem. The value is a list
with two elements "value" (the block) and "key" (the site name, as a
list):

> nextElem(sites)
$value
   site year     peak
1 ALBEN    5 101529.6
2 ALBEN   10 117483.4
3 ALBEN   20 132960.9
4 ALBEN   50 153251.2
5 ALBEN  100 168647.8
6 ALBEN  200 184153.6
7 ALBEN  500 204866.5

$key
$key[[1]]
[1] "ALBEN"

Now you can use foreach to loop over your data frame, without a
separate split operation:

sites <- isplit(site.data,site.data$site)
foreach(site=sites) %dopar% {
 pdf(paste(site$key[[1]],".pdf",sep=""))	
 plot(site$value$year,site$value$peak,main=site$key[[1]])
 dev.off()
}

On the data you showed, this creates three files: ALBEN.pdf, ALDER.pdf
and AMERI.pdf, each with a scatterplot of peak by year.

If your 300 plots take a non-trivial amount of time to produce, and
speed is a concern, you could even parallelize the production on a
multiprocessor system (Mac/Unix only) with registerDoMC().

Hope this helps,
# David Smith

On Fri, Aug 7, 2009 at 12:05 PM, Ingrid Tohver<itohver at u.washington.edu> wrote:
> Hello,
> I am attempting to create several plots based on "site" (~300 total) and am
> having trouble with the code. I simply want to create a plot using the code,
> plot(year, peak), for the following dataset. I would like for each site to
> be plotted on a separate page and the plots saved in a directory. Would a
> "foreach" loop work? I tried a "by" statement, but it doesn't seem to work
> with plotting functions.
> I would really appreciate any leads.
> Ingrid
>
>  site          year   peak
> ALBEN       5  101529.6
> ALBEN      10  117483.4
> ALBEN      20  132960.9
> ALBEN      50  153251.2
> ALBEN     100  168647.8
> ALBEN     200  184153.6
> ALBEN     500  204866.5
> ALDER       5    6561.3
> ALDER      10    7897.1
> ALDER      20    9208.1
> ALDER      50   10949.3
> ALDER     100   12287.6
> ALDER     200   13650.2
> ALDER     500   15493.6
> AMERI       5   43656.5
> AMERI      10   51475.3
> AMERI      20   58854.4
> AMERI      50   68233.3
> AMERI     100   75135.9
> AMERI     200   81908.3
>
>
> Ingrid M Tohver
> Research Scientist, Climate Impacts Group
> University of Washington


-- 
David M Smith <david at revolution-computing.com>
Director of Community, REvolution Computing www.revolution-computing.com
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