Another option in this specific case is to use the new useRaster=TRUE option, which makes the image function generate much more compact and faster-rendering image plots. This code:
setEPS() postscript (file="volc.eps",width=5,height=4) image(volcano,useRaster=TRUE) dev.off() in R 2.13 generates a 37Kb file which renders very quickly (compared to a 193Kb file without using the useRaster=TRUE option). # David Smith On Thu, Jul 21, 2011 at 12:23 AM, pilchat <pilc...@gmail.com> wrote: > > Dear R users, > > I have a desktop computer and a laptop, both of them with Ubuntu Lucid. The > former has R2.10 installed from Ubuntu repositories (this is the most recent > version in the repositories), while the latter has R2.13 from the CRAN > repositories. > > I noticed that postscript files generated with R2.10 are "better" than > files generated with the latest release of R, in particular for plots with > colored areas, such as the output of image or persp. The thing is that my ps > viewer (e.g. gv or evince) is very slow in opening ps files from R2.13, > while it smoothly displays ps files from R2.10, regardless of > "encapsulation". > > I think this is related to differences in the way the ps file is generated > by the two versions of R, but I don't know how to go deeper in the matter. > > Is there anyone experiencing the same issue? Is there any solution? > > Thank you in advance > > Cheers > > Gaetano > > [[alternative HTML version deleted]] > > ______________________________________________ > 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. -- David M Smith <da...@revolutionanalytics.com> VP of Marketing, Revolution Analytics http://blog.revolutionanalytics.com Tel: +1 (650) 646-9523 (Palo Alto, CA, USA) ______________________________________________ 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.
