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. 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 ______________________________________________ R-help@r-project.org 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.