[R] Drawing rectangles in multiple panels

[Stephen Tucker]

This is very interesting - but I'm not entirely clear on your last statement
though about how existing functions can cause problems with the scoping that
createWrapper() avoids... (but thanks for the tip).


--- Gabor Grothendieck <ggrothendieck at gmail.com> wrote:

> Your approach of using closures is cleaner than that
> given below but just for comparison in:
> 
> http://tolstoy.newcastle.edu.au/R/devel/06/03/4476.html
> 
> there is a createWrapper function which creates a new function based
> on the function passed as its first argument by using the components
> of the list passed as its second argument to overwrite its formal
> arguments.  For example,
> 
> createWrapper <- function(FUN, Params) {
>    as.function(c(replace(formals(FUN), names(Params), Params), body(FUN)))
> }
> 
> library(lattice)
> 
> rectInfo <-
>    list(matrix(runif(4), 2, 2),
>         matrix(runif(4), 2, 2),
>         matrix(runif(4), 2, 2))
> 
> 
> panel.qrect <- function(x, y, ..., rect.info) {
>    ri <- rect.info[[packet.number()]]
>    panel.rect(ri[1, 1], ri[1, 2], ri[2, 1], ri[2, 2],
>               col = "grey86", border = NA)
>    panel.xyplot(x, y, ...)
> }
> 
> xyplot(runif(30) ~ runif(30) | gl(3, 10),
>       panel = createWrapper(panel.qrect, list(rect.info = rectInfo)))
> 
> The createWrapper approach does have an advantage in the situation
> where the function analogous to panel.qrect is existing since using
> scoping then involves manipulation of environments in the closure
> approach.
> 
> On 7/11/07, Stephen Tucker <brown_emu at yahoo.com> wrote:
> > In the Trellis approach, another way (I like) to deal with multiple
> pieces of
> > external data sources is to 'attach' them to panel functions through
> lexical
> > closures. For instance...
> >
> > rectInfo <-
> >    list(matrix(runif(4), 2, 2),
> >         matrix(runif(4), 2, 2),
> >         matrix(runif(4), 2, 2))
> >
> > panel.qrect <- function(rect.info) {
> >  function(x, y, ...) {
> >    ri <- rect.info[[packet.number()]]
> >    panel.rect(ri[1, 1], ri[1, 2], ri[2, 1], ri[2, 2],
> >               col = "grey86", border = NA)
> >    panel.xyplot(x, y, ...)
> >  }
> > }
> >
> > xyplot(runif(30) ~ runif(30) | gl(3, 10),
> >       panel = panel.qrect(rectInfo))
> >
> > ...which may or may not be more convenient than passing rectInfo (and
> perhaps
> > other objects if desired) explicitly as an argument to xyplot().
> >
> >
> > --- Deepayan Sarkar <deepayan.sarkar at gmail.com> wrote:
> >
> > > On 7/11/07, hadley wickham <h.wickham at gmail.com> wrote:
> > > > > A question/comment: I have usually found that the subscripts
> argument
> > > is
> > > > > what I need when passing *external* information into the panel
> > > function, for
> > > > > example, when I wish to add results from a fit done external to the
> > > trellis
> > > > > call. Fits[subscripts] gives me the fits (or whatever) I want to
> plot
> > > for
> > > > > each panel. It is not clear to me how the panel layout information
> from
> > > > > panel.number(), etc. would be helpful here instead. Am I correct?
> -- or
> > > is
> > > > > there a smarter way to do this that I've missed?
> > > >
> > > > This is one of things that I think ggplot does better - it's much
> > > > easier to plot multiple data sources.  I don't have many examples of
> > > > this yet, but the final example on
> > > > http://had.co.nz/ggplot2/geom_abline.html illustrates the basic idea.
> > >
> > > That's probably true. The Trellis approach is to define a plot by
> > > "data source" + "type of plot", whereas the ggplot approach (if I
> > > understand correctly) is to create a specification for the display
> > > (incrementally?) and then render it. Since the specification can be
> > > very general, the approach is very flexible. The downside is that you
> > > need to learn the language.
> > >
> > > On a philosophical note, I think the apparent limitations of Trellis
> > > in some (not all) cases is just due to the artificial importance given
> > > to data frames as the one true container for data. Now that we have
> > > proper multiple dispatch in S4, we can write methods that behave like
> > > traditional Trellis calls but work with more complex data structures.
> > > We have tried this in one bioconductor package (flowViz) with
> > > encouraging results.
> > >
> > > -Deepayan
> > >
> > > ______________________________________________
> > > R-help at stat.math.ethz.ch mailing list
> > > https://stat.ethz.ch/mailman/listinfo/r-help
> > > PLEASE do read the posting guide
> > > http://www.R-project.org/posting-guide.html
> > > and provide commented, minimal, self-contained, reproducible code.
> > >
> >
> > ______________________________________________
> > R-help at stat.math.ethz.ch mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
> 



       
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