[R] Drawing rectangles in multiple panels

[Stephen Tucker]

Hi Deepayan, that's very hard-core... for the atmospheric science
applications (which is what I do) that I've encountered, (time-series) data
sets are often pre-aggregated before distribution (to 'average out'
instrument noise) so I haven't had the need for such requirements thus far...
but very good to know (and cool demonstrations btw). Thanks!

Stephen

--- Deepayan Sarkar <deepayan.sarkar at gmail.com> wrote:

> On 7/14/07, Stephen Tucker <brown_emu at yahoo.com> wrote:
> >
> > I wonder what kind of objects? Are there large advantages for allowing
> > lattice functions to operate on objects other than data frames - I
> > couldn't find any screenshots of flowViz but I imagine those objects
> > would probably be list of arrays and such? I tend to think of mapply()
> > [and more recently melt()], etc. could always be applied beforehand,
> > but I suppose that would undermine the case for having generic
> > functions to support the rich collection of object classes in R...
> 
> There's a copy of a presentation at
> 
>
http://www.ficcs.org/meetings/ficcs3/presentations/DeepayanSarkar-flowviz.pdf
> 
> and a (largish - 37M) vignette linked from
> 
> http://bioconductor.org/packages/2.1/bioc/html/flowViz.html
> 
> Neither of these really talk about the challenge posed by the size of
> the data. The data structure, as with most microarray-type
> experiments, is like a data frame, except that the response for every
> experimental unit is itself a large matrix. If we represented the GvHD
> data set (the one used in the examples) as a "long format" data frame
> that lattice would understand, it would have 585644 rows and 12
> columns (8 measurements that are different for each row, and 4
> phenotypic variables that are the same for all rows coming from a
> single sample). And this is for a smallish subset of the actual
> experiment.
> 
> In practice, the data are stored in an environment to prevent
> unnecessary copying, and panel functions only access one data matrix
> at a time.
> 
> -Deepayan
> 
> 
> > --- 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
> 



       
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