Dear useRs,
I have a longitudinal experiment with several treatment groups, ~20 subjects
per group, ~6 timepoints and a continuous dependent variable. I have been
successfully been using lattice::xyplot with this data. However, I have been
stumped with a particular application of it.
I would like to use xyplot on my data, broken into treatment groups with the
groups argument, using type='b' to show subjectwise longitudinal data. So far
so good, I have done this many times. But now I wish to show the same data but
having the color of the lines and symbols overridden in some arbitrary way, yet
not without changing anything else about the plot, in particular the
structure/topology of the plot from using the groups argument and type='b'.
This requires using a panel function of some sort. I have come to think I will
need to use a function with a 'subscripts' argument as the panel function,
which then itself calls panel.xyplot() and uses its arguments col.line and
col.symbol. The closest example I could find is on page 73 of Sarkar's UseR!
Lattice book, where the subscripts argument indexed the data within each
grouped subplot, and it was used as an index for a user-generated vector of
colors. This seems like what I want to do.
But I could not get this paradigm to work. Here is a simple example using
trivial data:
> unlist(R.Version())
platform
arch
"i386-pc-mingw32"
"i386"
os
system
"mingw32"
"i386, mingw32"
status
major
"Patched"
"2"
minor
year
"12.2"
"2011"
month
day
"03"
"18"
svn rev
language
"55383"
"R"
version.string
"R version 2.12.2 Patched (2011-03-18 r55383)"
> search()
[1] ".GlobalEnv" "package:stats" "package:graphics"
[4] "package:grDevices" "package:utils" "package:datasets"
[7] "package:methods" "Autoloads" "package:base"
> require(lattice)
Loading required package: lattice
> set.seed(388659262)
> dat <- data.frame(Panel=rep(c('A','B'), each=4),
+ ID=factor(rep(letters[1:4], each=2)),
+ X=rep(c(0,1), times=4),
+ Y=runif(8)
+ )
##### now for the arbitrary colors. Let's highlight one subject red, the rest
black
> dat$Color <- with(dat, ifelse(Panel=='A' & ID == 'a', 2, 1))
> dat
Panel ID X Y Color
1 A a 0 0.1138821 2
2 A a 1 0.7361403 2
3 A b 0 0.3304683 1
4 A b 1 0.5866701 1
5 B c 0 0.8819857 1
6 B c 1 0.7329025 1
7 B d 0 0.5000357 1
8 B d 1 0.6365438 1
##### The following standard plot is fine.
##### Each subject is colored differently,
##### I believe recycling through the colors from either
##### trellis.par.get("superpose.symbol")$col or
##### trellis.par.get("superpose.line")$col,
##### but be default they are the same anyway
> xyplot(Y ~ X | Panel, data=dat, groups=ID, type='b',
+ scales=list(x=list(at=c(0,1),labels=c(0,1))))
##### But for example, this following attempt to grab the
##### corresponding values of dat$Color do not have
##### my intended effect. There are now three "subjects"
##### plotted per group, each groups' line colors are the same,
##### and the symbol colors are nearly the same as the line colors....but not
exactly!
> xyplot(Y ~ X | Panel, data=dat, groups=ID, type='b',
+ scales=list(x=list(at=c(0,1),labels=c(0,1))),
+ panel=function(..., groups, subscripts) panel.xyplot(...,
col.symbol=dat$Color[subscripts],
+
col.line=dat$Color[subscripts])
+ )
At one point in my efforts I was actually able to get the symbol colors
correct, but the line colors were (to me) incomprehensibly wrong. But alas I
have not be able to reproduce that to show here.
\begin{ignorant speculation alert}
I suspect that having (in the example) 8 points but only 4 lines causes
undesired recycling somewhere.
\end{speculation}
Any assistance as to how to properly use the panel functions (or any other
approach short of abandoning lattice graphics) to override the coloring would
be greatly appreciated.
John
John Szumiloski, Ph.D.
Senior Biometrician
Biometrics Research
WP53B-120
Merck Research Laboratories
P.O. Box 0004
West Point, PA 19486-0004
USA
(215) 652-7346 (PH)
(215) 993-1835 (FAX)
john<dot>szumiloski<at>merck<dot>com
___________________________________________________
These opinions are my own and do not necessarily reflect that of
Merck & Co., Inc.
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