Hi,
I was taken off guard by the following behavior in a lattice plot.
I frequently want to add a predicted curve defined at more
points than in the formula expression of xyplot. There have
been numerous examples of how to do this on r-help, but I
still often struggle to make this work. I just realized that
specifying one of the axes on a log scale does not guarantee
that the added data for a curve will automatically take that
into account. I don't know if this should be called a bug,
I haven't picked up an indication that would lead me to
expect this in the documentation. I admit that if I had a
deeper understanding of lattice and/or grid, it might be
clearer why... Here is a toy example illustrating the behavior
(there may be a more efficient way to do this),
ds1 <- data.frame( RR = rep(seq(0, 1, len = 5)^2, 2) +
rnorm(10, sd = 0.1),
LL = rep(10^seq(1, 5), 2),
FF = factor(rep(letters[1:2], each = 5))
)
ds2 <- data.frame(RR = rep(seq(0, 1, len = 20)^2, 2),
LL = rep(10^seq(1, 5, len = 20), 2),
FF = factor(rep(letters[1:2], each = 20))
)
library(lattice)
xyplot(RR ~ LL | FF, ds1,
scales = list(x = list(log = TRUE)),
aspect = "xy",
subscripts = TRUE,
ID = ds2$FF,
panel = function(x, y, subscripts, ID, ...) {
w <- unique(ds1$FF[subscripts])
llines(log10(ds2$LL[ID == w]), ds2$RR[ID == w], ...)
panel.xyplot(x, y, ...)
}
)
Note that the x-variable of llines must be logged to plot the correct values
and so the scales argument seems to apply only to the x, y arguments
passed to the panel function.
Thank you.
best,
Ken
--
Ken Knoblauch
Inserm U846
Institut Cellule Souche et Cerveau
Département Neurosciences Intégratives
18 avenue du Doyen Lépine
69500 Bron
France
tel: +33 (0)4 72 91 34 77
fax: +33 (0)4 72 91 34 61
portable: +33 (0)6 84 10 64 10
http://www.lyon.inserm.fr/846/english.html
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