On 11/20/07, Dylan Beaudette <[EMAIL PROTECTED]> wrote:
> On Tuesday 20 November 2007, Deepayan Sarkar wrote:
> > On 11/20/07, Dylan Beaudette <[EMAIL PROTECTED]> wrote:
> >
> > [...]
> >
> > > Example:
> > > library(lattice)
> > >
> > > # generate some data:
> > > resp <- rnorm(100)
> > > pred <- resp*1.5 + rnorm(100)
> > > d <- data.frame(resp=resp, pred=pred)
> > >
> > > # add a grouping factor:
> > > d$grp <- gl(4, 25, labels=letters[1:4])
> > >
> > > # plot: looks ok!
> > > main.plot <- xyplot(resp ~ pred | grp, data=d, panel=function(x,y, ...)
> > > {panel.xyplot(x, y, ...) ; panel.lmline(x,y, ...) })
> > >
> > > # however, we have some other information which needs to go in each panel
> > > # note that the dimensions (i.e. no of obs) are not the same as the
> > > original # data, and the values are different, but on the same scale
> > > resp.other <- rnorm(20)
> > > pred.other <- resp.other*1.5 + rnorm(20)
> > > d.other <- data.frame(resp=resp.other, pred=pred.other)
> > > d.other$grp <- gl(4, 5, labels=letters[1:4])
> > >
> > >
> > > The big question:
> > > Now that we have the main plot (main.plot) looking ok, how can we add the
> > > data from d.other to the frames of main.plot without using subset() for
> > > each level of our grouping variable?
>
> Hi,
>
> > I would say you are asking the wrong question. The right question is:
> > how do I manipulate my data so that it becomes easy to work with. Try
> >
> > combined <- make.groups(d, d.other)
>
> excellent! this makes complete sense...
>
> > xyplot(resp ~ pred | grp, data=combined, groups = which,
> > panel = panel.superpose,
> > panel.groups = function(x,y, ...) {
> > panel.xyplot(x, y, ...)
> > panel.lmline(x,y, ...)
> > })
> >
> > Is that close to what you want? Does it extend to your real example?
> >
> > -Deepayan
>
> This is close for the contrived example, but not quite what I need. I would
> like to plot the first 'group' of data as lines, and the second as points. I
> have tried specifying type=c('l', 'p') but this does not appear to work.
Try adding 'distribute.type = TRUE' (see ?panel.superpose). My UseR!
2007 talk had some relevant examples, so you might find those slides
useful:
http://www.user2007.org/program/presentations/sarkar.pdf
-Deepayan
> If I plot everything as point, the data plot correctly, but not in the symbols
> that I would like.
>
> Cheers,
>
> Dylan
>
>
> > > # after some messing around, how about this:
> > > xyplot(resp ~ pred | grp, data=d, panel=function(x,y, ...)
> > > {
> > > panel.xyplot(x, y, ...)
> > > panel.lmline(x,y, ...)
> > > # now the other data:
> > > panel.superpose(d.other$pred, d.other$resp, groups=d.other$grp,
> > > col=c('red', 'blue', 'green', 'orange')[as.numeric(d.other$grp)], pch=16,
> > > subscripts=TRUE)
> > > }
> > > )
> > >
> > > #... hmm it doesn't look like the information from 'd.other' is being
> > > stratified into the panels setup in panel.xyplot() ...
> > >
> > > The main point to this rather contrived example is this :
> > >
> > > 1. i have a data frame with continuous predictions, the response, and the
> > > grouping variable -- which plot nicely with the default use of xyplot()
> > >
> > > 2. I would like to embellish each panel with the original response and
> > > predictor values to illustrate the relationship between the original data
> > > and the smooth, fitted curve.
> > >
> > > ideas?
> > >
> > > thanks!
> > >
> > > Dylan
> > >
> > >
> > > --
> > > Dylan Beaudette
> > > Soil Resource Laboratory
> > > http://casoilresource.lawr.ucdavis.edu/
> > > University of California at Davis
> > > 530.754.7341
>
>
>
> --
> Dylan Beaudette
> Soil Resource Laboratory
> http://casoilresource.lawr.ucdavis.edu/
> University of California at Davis
> 530.754.7341
>
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