On further thought, this might be better as it keeps the keys distinct

library(lattice)
library(latticeExtra)

D1 <- data.frame(y=1:3, x=4:6)
D2 <- data.frame(y=7:10, x=11:14)

T1 <- xyplot(y ~ x, data=D1,
             key=list(space="right", text=list(LETTERS[1:3],
col=c("red","green","blue"))))

T2 <- xyplot(y ~ x, data=D2,
             key=list(space="right", text=list(LETTERS[4:7],
col=c("orange","purple","brown","pink"))))

c(T1, T2, layout=c(1,2), merge.legends=TRUE)


print(update(T1, xlim=c(3,15)), split=c(1,1,1,2), more=TRUE)
print(update(T2, xlim=c(3,15)), split=c(1,2,1,2), more=FALSE)



On Mon, Feb 4, 2013 at 3:06 PM, Richard M. Heiberger <rmh@temple.edu> wrote:

> This will get you started
>
> library(lattice)
> library(latticeExtra)
>
> D1 <- data.frame(y=1:3, x=4:6)
> D2 <- data.frame(y=7:10, x=11:14)
>
> T1 <- xyplot(y ~ x, data=D1,
>              key=list(space="right", text=list(LETTERS[1:3],
> col=c("red","green","blue"))))
>
> T2 <- xyplot(y ~ x, data=D2,
>              key=list(space="right", text=list(LETTERS[4:7],
> col=c("orange","purple","brown","pink"))))
>
> c(T1, T2, layout=c(1,2), merge.legends=TRUE)
>
>
> Rich
>
>
> On Mon, Feb 4, 2013 at 2:37 PM, Ryan Flaherty <ryan1.flaherty@gmail.com>wrote:
>
>> Dear R users-
>>
>> Do the lattice/latticeExtra packages support multiple tileplots with
>> unique
>> colorkeys? I am trying to create a visualization of the encounter rate of
>> certain stocks of salmon across two years. The issue I am having is that
>> some stocks are encountered at much higher rates than others.the high
>> encounter rate for one stock washes out the patterns I'm hoping to
>> visualize
>> across the other, less common, stocks. In the example below, the high
>> encounter rate of Central Valley Fall (CVF) in San Francisco (SF) during
>> June of 2011 makes it impossible to identify differences in encounter rate
>> of the other stocks. Is there a way to create the same plot but with a
>> unique colorkey for each panel?
>>
>> #Please first load packages RCurl and latticeExtra
>>
>> #Import data
>> getdata<-getURL("
>> https://docs.google.com/spreadsheet/pub?hl=en&hl=en&key=0Aj
>> zYZNH9Dw9qdENjREl2ZkVlcFA4MDN2S1h6Vi03ZUE&single=true&gid=0&output=csv<https://docs.google.com/spreadsheet/pub?hl=en&hl=en&key=0AjzYZNH9Dw9qdENjREl2ZkVlcFA4MDN2S1h6Vi03ZUE&single=true&gid=0&output=csv>
>> ",ssl.
>> verifypeer=FALSE)
>> test<-read.csv(textConnection(getdata),header=T)
>> test$year<-as.factor(test$year)
>> head(test)
>>
>> ##Custom color ramp
>> jet.colors <-
>>   colorRampPalette(c("#00007F", "blue", "#007FFF", "cyan",
>>                      "#7FFF7F", "yellow", "#FF7F00", "red", "#7F0000"))
>>
>> ##create trellis of tileplots
>>
>> betweenyear<-tileplot(index~month*-area|stock+year,test,col.regions=jet.colo
>> rs(256),
>>         scales=list(x=list(at=5:9, labels=c('May'
>> ,'Jun','Jul','Aug','Sep'),cex=0.6),
>>       y=list(at=(-1):-8,labels=c('T','N','C','B','KC','FB','SF','MO'))),
>>         main = list(label="Stock specific encounter rate by WCGSI: 2010
>> versus 2011",cex=0.75) ,
>>         xlab= "Month",
>>         ylab= "Management Area",
>>         border = "black",
>>         panel = function(...){
>>         panel.fill("black")
>>         panel.voronoi(...)
>>         })
>>
>> ##plot object
>> plot(betweenyear)
>>
>> Thank you for your time and consideration.
>>
>> Regards,
>>
>> Ryan
>>
>> Ryan Flaherty
>> Oregon State University
>> College of Oceanic and Atmospheric Science
>> Marine Resource Management
>> 541-513-0293
>> rflaherty@coas.oregonstate.edu
>>
>> ______________________________________________
>> R-help@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
>

	[[alternative HTML version deleted]]

