similar to: using xyplot

I wish to display a single-panel Lattice figure with grouped data and fitted regression lines. I don't seem to be able to get the individual regression lines to display, e.g.; d <- data.frame(q = rep(1:6, each=10), cc = rep(seq(10,100, 10),6)) # create data frame with group identifier 'q', independent variable cc d$ba = d$q*0.1*d$cc + 5*rnorm(nrow(d))

Hi, I am trying to create a plot with pairs() using a gplot.hexbin() for each pair. For pairs I can provide a custom upperPanel function: pairs(iris[1:4], panel=mypanel) and mypanel() calls plot.hexbin(): library(hexbin) # Bioconductor mypanel <- function(x, ...){ hb <- hexbin(x) plot(hb) } The problem is that gplot.hexbin() is based on the

Hi there, I'm looking for someone who can give me some hints how to make a nice levelplot. As an example, I have the following code: # create some example data # -------------------------------------- xl <- 4 yl <- 10 my.data <- sapply(1:xl, FUN = function(x) { rnorm( yl, mean = x) }) x_label <- rep(c("X Label 1", "X Label 2", "X Label 3", "X

Hello, I have been trying to make a graph that have error bars and text at specific position. I used the following code from the help file of xYplot(Hmisc) as an example except I add a myPanel function, which is just supposed to add letters from the alphabet at the position aligned at y = 3. It constantly gives me error: "Error using packet 1 argument "subscripts" is

Dear R-users, A while ago, Deepayan Sarkar suggested some code that uses the group argument in bwplot to create some 'side-by-side' boxplots (https://stat.ethz.ch/pipermail/r-help/2010-February/230065.html). The example he gave was relatively specific and I wanted to generalize his approach into a function. Unfortunately, I seem to have some issues passing the correct arguments to the

Thanks, Sanjay, that makes sense. The opportunity for improving instcombining splat sounds promising. Another question about shuffle simplification. This is a testcase from test/Transforms/InstCombine/vec_shuffle.ll: define <4 x i32> @test10(<4 x i32> %tmp5) nounwind { %tmp6 = shufflevector <4 x i32> %tmp5, <4 x i32> undef, <4 x i32> <i32 1, i32 undef, i32

Hi, I have been trying to output my graphs to a file (jpeg, pdf, ps, it doesnt matter) but i cant seem to be able to get it to output. I tried a few things but none of them worked and am lost as what to do now. I am using the scatter3d function, and it prints out the graphs on tot he screen without any problems, but when it comes to writing them to a file i cant make it work. Is there any

Dear expeRts, I would like to colorize the backgrounds of a pairs plot according to the respective panel number. Here is what I tried (without success): count <- 0 mypanel <- function(x, y, ...){ count <<- count+1 bg. <- if(count %in% c(1,4,9,12)) "#FDFF65" else NA points(x, y, cex=0.5, bg=bg) } U <- matrix(runif(4*500), ncol=4) pairs(U, panel=mypanel) I

Hi list, I want to plot two plot in the same figure. I set par(new=TRUE). But it does not work. library(lattice) myPanel <- function(x,...) { panel.histogram(x,alpha=0.4,...) ltext(0.4,1.5,paste("Mean=","0.05",digit=2)),cex=0.8) ltext(0.8,1.5,paste("s.d.=","0.06",digit=2)),cex=0.8) } histogram(sh2,

Dear friends - please give me a hand. I have a dataset of 40 patients in two groups observed on three occasions. I only want to plot a line for each patient in the two groups. I use the ltext function to put the patient number but fail to make lattice understand the numbers as unique since apparently it starts all over with 1:20 for each panel instead of respecting my desires to have 1:20

I've just spent today trying to fix a Heisenbug... this function returns a linear interpolator function: interpOne <- function(xl,yl){ f = function(data){ t = (data-min(xl))/(max(xl)-min(xl)) return(min(yl)+t*(max(yl)-min(yl))) } return(f) } > k=interpOne(c(0,1),c(4,5)) > k(0.5) [1] 4.5 and this function uses the above to return a function that returns a piece-wise

Dear r-help, Sleep-deprivation from having 2 youngsters under 2 around the house is fuzzing my brain, so please be gentle if the answer to this query is obvious! In the example below, I'm trying to use grid.rect to add grey rectangles to the panels of a lattice plot to indicate which months spawning occurred of a (very cute) native Tasmanian fish. The fish in the two lakes spawned at

I wish to create a multipanel plot (map) from several datasets ("d" and "q" in the example below). I can condition the main xyplot statement on the "site" variable, but I don't know how to pass a conditioning variable to panel.xyplot plot so that the x-y coordinates from dataset q are only plotted at the appropriate site. library(lattice) d <-

After installation of R into VineLinux2.1.5, I started to enjoy statistics following some instruction, and found it very useful. One of my main purpose to use R is to try spatial statistics. Since library named "spatial" has already installed, I just tried ... > library(spatial) > towns <- ppinit(test.dat) ------- test.dat ------- x,y 4,7 5,7 5,8 5,9 6,7 6,8 6,9 7,8

I have two data sets with locations, X, Y of houses (df.house) and habitats(df.habitat), respectively. In each dataset, there are 3 replicates (Repeat). Because each replicate has different locations of houses and habitats, I would like to plot them in panels. I wrote something like this: mypanel<-function(x,y,subscripts,...){ panel.xyplot(x,y,pch=20) panel.xyplot(

Hi, I have a data.frame df with names(df) = c("Var1", "Var2", "Var3", "Var4") and I plot data with xyplot(Var1+Var2~Var3|Var4, data=df) I want to use different panel functions for Var1 and Var2. How can I do ? Something like : panel.mypanel = function(x, y, ...) { if (Var1) panel.Var1Panel(x, y, ...) else panel.Var2Panel(x, y, ...) }

Here is a copy of the last few lines in base-Ex.Rout.fail: > x <- seq(3,500);yl <- c(-.3, .2) > plot(x,x, ylim = yl, ylab="",type='n', main = "Bessel Functions Y_nu(x)") > for(nu in nus){xx <- x[x > .6*nu]; lines(xx,besselY(xx,nu=nu), col = nu+2)} > legend(300,-.08, leg=paste("nu=",nus), col = nus+2, lwd=1) > > x <-

Hi: We're trying to install the Hmisc package on a Solaris 9 machine. Here's what we get: R CMD INSTALL /usr/local/srctree/Hmisc_3.4-2.tar.gz * Installing to library '/usr/local/lib/R/library' * Installing *source* package 'Hmisc' ... ** libs g95 -fPIC -g -O2 -c cidxcn.f -o cidxcn.o g95 -fPIC -g -O2 -c cidxcp.f -o cidxcp.o g95 -fPIC -g -O2 -c hoeffd.f -o

The LLVA and LLVM papers motivate the GetElementPtr instruction by arguing that it abstracts implementation details, in particular pointer size, from the compiler. While it does this fine for pointer addresses, it does not manage it for address offsets. Consider the following code: $ cat test.c int main() { int *x[2]; int **y = &x[1]; return (y - x); } $ llvm-gcc -O3 -c test.c

I think the subject says it all. I want to make a simple lattice plot, using xyplot with the argument type=c("l","a"). The problem then is that in the resulting plot it is difficult/impossible to see which plot corresponds to the average and which to the individual profiles. I triedthings like extra arguments lwd=c(1,3) or col=c("blue","red") hoping