Hi again Thomas, ah, sorry, I should be more precise. Please construct a reproducible worked example that does not require us to download 7 Mb of data. You might also try the suggestions that I made and let us know if they worked for you.
Cheers Andrew On Sat, Mar 17, 2007 at 10:37:46PM -0500, Thomas Colson wrote: > Thanks for the warning: > Here is the link to the datasets, rather large at 2 and 5 mb. Another note > is that one set has more datapoints than the other, don't know if this can > be done with xyplot. > http://www4.ncsu.edu/~tpcolson/coastcurvfreqs.txt > http://www4.ncsu.edu/~tpcolson/coastslopefreqs.txt > > Thomas Colson, PhD > North Carolina State University > Department of Forestry and Environmental Resources > (919)673-8023 > [EMAIL PROTECTED] > > Schedule: www4.ncsu.edu/~tpcolson > -----Original Message----- > From: Andrew Robinson [mailto:[EMAIL PROTECTED] > Sent: Saturday, March 17, 2007 10:15 PM > To: Thomas Colson > Cc: r-help@stat.math.ethz.ch > Subject: Re: [R] "Groups" in XYPLOT > > Hi Thomas, > > sadly, the full code is not much help to us in the absence of the data. Can > I suggest that you construct a reproducible worked example to help explain > your question? For what it's worth I suspect that the answer is that you > need to join these datasets into one and theneitehr use the groups argument, > or the "+" protocol on the LHS of the plot formula. > > Cheers > > Andrew > > On Tue, Mar 27, 2007 at 04:51:55PM -0500, Thomas Colson wrote: > > I'm not sure I'm barking up the right tree here, but would I need to > > make use of groups to plot two separate datasets within ONE panel in > > xyplot? The desired end result is a single xy plot of two separate > > (but similar in values and ranges). > > > > Full code follows, xyplot code at bottom > > > > > > > > > > > > #########Determine Frequencies > > ##########coastal_slope > > #needs the maptools package to read ESRI grid > > require(maptools) > > #import the flow slope grid > > basin.map <- readAsciiGrid("C:/R_PLots/coastal_slp.asc", > > colname="slope") basin_slope <- (basin.map$slope) #read the slopes > > into a dataframe > > freqs<-as.data.frame(table(basin_slope)) > > #rank the frequencies based on each unique occerence, note, ranks from > > 1 to n > > r<-rank(freqs$basin_slope) > > n<-length(r) > > #determing the probability, n+1 insures there is no 100%, 1- reverses > > the order so #low slopes gets high probability of exceedence > > z<-cbind(Rank = r, PRank = 1-(r/(n+1))) #attach the probability to the > > table, result is high prob of exceed is in row with low slope #and low > > probabibility is in row with high slope freqs$rank<-z > > write.table(freqs, "C:/R_PLots/coastslopefreqs.txt", sep=",", > > col.names=TRUE, row.names=TRUE, quote=TRUE, na="NA") > > > > ##########coastal_curvature > > #needs the maptools package to read ESRI grid > > require(maptools) > > #import the curvature grid > > basin.map <- readAsciiGrid("C:/R_PLots/coastal_crv.asc", > > colname="curv") basin_curv <- (basin.map$curv) #read the curvs into a > > dataframe > > freqs<-as.data.frame(table(basin_curv)) > > #rank the frequencies based on each unique occerence, note, ranks from > > 1 to n > > r<-rank(freqs$basin_curv) > > n<-length(r) > > #determing the probability, n+1 insures there is no 100%, 1- reverses > > the order so #low curvature gets high probability of exceedence > > z<-cbind(Rank = r, PRank = 1-(r/(n+1))) #attach the probability to the > > table, result is high prob of exceed is in row with low curv #and low > > probabibility is in row with high curv freqs$rank<-z > > write.table(freqs, "C:/R_PLots/coastcurvfreqs.txt", sep=",", > > col.names=TRUE, row.names=TRUE, quote=TRUE, na="NA") > > > > > > > > > > > > ##############Make XYPLOT and export to ps coastcurv <- > > read.table("C:/R_PLots/coastcurvfreqs.txt", header=TRUE, sep=",", > > na.strings="NA", dec=".", strip.white=TRUE) > > xyplot(coastcurv$rank.PRank~coastcurv$basin_curv,scales=list(y=list(lo > > g=TRUE > > ,at=c(.0001,.001,.01,.1,1)),x=list(log=TRUE,at=c(0.0001,0.001,0.01,0.1 > > ,1,10) > > )),xlab="Curvature",ylab="P(C>C*)") > > dev.copy2eps(file="C:/R_PLots/coastcurv_cad.eps", width=8.0, > > height=8.0, > > pointsize=10) > > > > > > ########How to get this in the first plot graphic? > > > > coastslope <- read.table("C:/R_PLots/coastslopefreqs.txt", > > header=TRUE, sep=",", na.strings="NA", dec=".", strip.white=TRUE) > > xyplot(coastslope$rank.PRank~coastslope$basin_slope,scales=list(y=list > > (log=T > > RUE,at=c(.0001,.001,.01,.1,1)),x=list(log=TRUE,at=c(0.0001,0.001,0.01, > > 0.1,1, > > 10))),xlab="Slope",ylab="P(S>S*)") > > dev.copy2eps(file="C:/R_PLots/coastslope_cad.eps", width=8.0, > > height=8.0, > > pointsize=10) > > > > Thomas Colson, PhD > > North Carolina State University > > Department of Forestry and Environmental Resources > > > > ______________________________________________ > > R-help@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. > > -- > Andrew Robinson > Department of Mathematics and Statistics Tel: +61-3-8344-9763 > University of Melbourne, VIC 3010 Australia Fax: +61-3-8344-4599 > http://www.ms.unimelb.edu.au/~andrewpr > http://blogs.mbs.edu/fishing-in-the-bay/ > > ______________________________________________ > R-help@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. -- Andrew Robinson Department of Mathematics and Statistics Tel: +61-3-8344-9763 University of Melbourne, VIC 3010 Australia Fax: +61-3-8344-4599 http://www.ms.unimelb.edu.au/~andrewpr http://blogs.mbs.edu/fishing-in-the-bay/ ______________________________________________ R-help@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.