[R] Drawing rectangles in multiple panels

[Gabor Grothendieck]

Suppose ri were already defined as in the example below.
Then panel.qrect is a bit harder to define although with
work its possible as shown below:

rectInfo <-
   list(matrix(runif(4), 2, 2),
        matrix(runif(4), 2, 2),
        matrix(runif(4), 2, 2))

ri <- 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, ...)
 }

panel.qrect <- function(rect.info) {
	function(x, y, ...) {
		environment(ri) <- environment() ###
		ri(x, y, ..., rect.info = rect.info)
	}
}

xyplot(runif(30) ~ runif(30) | gl(3, 10),
      panel = panel.qrect(rectInfo))



On 7/14/07, Stephen Tucker <brown_emu at yahoo.com> wrote:
> 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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