|
Sebastien,
The easiest way
is:
#put a line at the
beginning of the function:
assign("mydata", mydata,
frame=1)
May be it is not a
good way for a programmer, but it works.
Thanks,
Ron
Hi Ron,
Thanks for your input. I have
however tested my code with and without the strip function and still had the
same error message:
Problem in eval(if(no.given) formula else
expr[[1]],..: Object "mydata" not found
Sebastien
On Thu, Oct 30, 2008 at 10:10 AM, Rongsheng Liu <rsliu@homer.att.com>
wrote:
Sebastien,
try to passing parameter into strip
function:
strip =
function(which.panel, nID=nID,
...){
lines(c(0,1,1,0,0),c(0,0,1,1,0),col=1)
text(rep(0.5,nID),rep(0.5,nID),
paste("SD = ",mysds[which.panel],sep=""),
cex = 0.75)}
Thanks,
Ron
Dear S-plus users,
I am trying to plot
some density histograms from a data.frame of simulated data. Since I want
to plot several sets of simulated data, I have created this function
myhisto which supposedly should do the work. Funny thing: the code within
the function does not work when the data are passed to the function, BUT
it does when it is used outside of a function (see the end of the code
below). Can anyone explain what I am doing wrong in my
function?
Thanks you in advance,
Sebastien
PS: if anyone
can also explain why the attribute which.panel does not work in strip, I
would also be grateful!
############# Code starts here
#
Custom functions
# Random generation of 10000 individuals for each
input sd
myranddf <- function(mysds){
nsd <-
length(mysds)
tmp <- c()
for (i in
seq(nsd)){
tmp <- c(tmp,rnorm(10000, mean = 0, sd
= mysds[i]))
}
mydf <- data.frame(X=tmp,
SD=rep(mysds, each = 10000))
mydf
}
# Histogram
plot
myhisto <- function(mydata,nBar){
mysds <-
levels(factor(mydata[,2]))
nID <- length(mysds)
myplot <-
histogram(~mydata[,1]|mydata[,2],
data =
"">
as.table=TRUE,
type =
"percent",
nint=nBar,
xlim=c(0,1),
xlab="X",
ylab="Probability
density",
layout=c(2,2),
main=NULL,
strip =
function(which.panel,...){
lines(c(0,1,1,0,0),c(0,0,1,1,0),col=1)
text(rep(0.5,nID),rep(0.5,nID),
paste("SD =
",mysds[which.panel],sep=""),
cex =
0.75)},
key=NULL)
print(myplot)
}
# Create data set for
typical logit transform with additive variability model
# X =
exp(ln(TVX/(100-TVX))+eta)/(1+exp(ln(TVX/(100-TVX))+eta))
TVX =
50
mysds = c(0.05,0.1,0.25,0.75)*TVX
mydf <-
myranddf(mysds)
mydf[,1] <-
exp(log(TVX/(100-TVX))+mydf[,1])
mydf[,1] <-
mydf[,1]/(1+mydf[,1])
# Plotting using the
function
myhisto(mydf,50)
# Plotting outside a
function
mydata <- mydf
nBar <- 50
myplot
<-
histogram(~mydata[,1]|mydata[,2],
data =
"">
as.table=TRUE,
type =
"percent",
nint=nBar,
xlim=c(0,1),
xlab="X",
ylab="Probability
density",
layout=c(2,2),
main=NULL,
strip =
function(which.panel,...){
lines(c(0,1,1,0,0),c(0,0,1,1,0),col=1)
text(rep(0.5,4),rep(0.5,4),
paste("SD =
",mysds[which.panel],sep=""),
cex =
0.75)},
key=NULL)
print(myplot)
################ END of
code
|