Thanks for the example. Makes it easy to see what you mean.
Yes, if I understand you correctly, you are right:
boxplot() (base) transforms the axes, so ?boxplot.stats, which is the
function that essentially computes the boxplot, does so on the
original data.
bwplot(lattice) transforms the data first, as the documentation for
the "log" component of the scales list makes clear, and **then** calls
boxplot.stats.
Although I think the latter makes more sense then the former, I think
the way to do it is to modify the "stats" function in an explicit call
to panel.bwplot to something like (UNTESTED!)
mystats <- function(x){
out <- boxplot.stats(10^x)
out$stats <- log10(out$stats)
out$conf <- log10(out$conf) ## Omit if you don't want notches
out$out <- log10(out$out)
out ## With the boxplot statistics converted to the log10 scale
}
I leave it to you to test and modify as necessary.
Cheers,
Bert
On Fri, Sep 14, 2012 at 2:37 AM, maxbre <mbres...@arpa.veneto.it> wrote:
> Given my reproducible example
>
> test<-structure(list(site = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L,
> 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
> 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L), .Label = c("A",
> "B", "C", "D", "E"), class = "factor"), conc = c(2.32, 0.902,
> 0.468, 5.51, 1.49, 0.532, 0.72, 0.956, 0.887, 20, 30, 2.12, 0.442,
> 10, 50, 110, 3.36, 2.41, 20, 70, 3610, 100, 4.79, 20, 0.0315,
> 30, 60, 1, 3.37, 80, 1.21, 0.302, 0.728, 1.29, 30, 40, 90, 30,
> 0.697, 6.25, 0.576, 0.335, 20, 10, 620, 40, 9.98, 4.76, 2.61,
> 3.39, 20, 4.59)), .Names = c("site", "conc"), row.names = c(NA,
> 52L), class = "data.frame")
>
>
>
> And the following code
>
> #standard graphics
> with(test,boxplot(conc~site, log="y"))
>
> #lattice
> bwplot(conc~site, data=test,
> scales=list(y=list(log=10))
> )
>
> There is an evident difference for site A, B, D in the way some outliers are
> plotted by comparing the plot produced by lattice vs. the standard graphics
>
> I think to understand this might be due to the different treatment of data:
> i.e. log transformation (before or after the plotting?)
>
> Is it possible to achieve the same plotting result with both graphic
> facilities?
> I would like to show the outliers also in lattice…
>
> Thank you
>
> http://r.789695.n4.nabble.com/file/n4643121/standard.png
>
> http://r.789695.n4.nabble.com/file/n4643121/lattice.png
>
>
>
>
>
> --
> View this message in context:
> http://r.789695.n4.nabble.com/Boxplot-lattice-vs-standard-graphics-tp4643121.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help@r-project.org mailing list
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
--
Bert Gunter
Genentech Nonclinical Biostatistics
Internal Contact Info:
Phone: 467-7374
Website:
http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm
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