I've tried using bitmap(), but it returns this taceback: [Wed Jan 16 16:10:05 2008] [error] [client 127.0.0.1] GPL Ghostscript SVN PRE-RELEASE [Wed Jan 16 16:10:05 2008] [error] [client 127.0.0.1] 8.61 [Wed Jan 16 16:10:05 2008] [error] [client 127.0.0.1] : [Wed Jan 16 16:10:05 2008] [error] [client 127.0.0.1] **** Could not open the file prova.png . [Wed Jan 16 16:10:05 2008] [error] [client 127.0.0.1] GPL Ghostscript SVN PRE-RELEASE [Wed Jan 16 16:10:05 2008] [error] [client 127.0.0.1] 8.61 [Wed Jan 16 16:10:05 2008] [error] [client 127.0.0.1] : [Wed Jan 16 16:10:05 2008] [error] [client 127.0.0.1] Unrecoverable error, exit code 1
I think ghostscript is trying to access the postcript file, but isn't able. It works perfectly out of Apache... I try with Cairo... my last try! 2008/1/16, Paul Hiemstra <[EMAIL PROTECTED]>: > Hi Giovanni, > > You could consider using 'bitmap()' instead of png(). I seem to remember > that the first uses postscript devices and does not need X11. Another > options would be to use the Cairo package, 'Cairo' initializes a new > graphics device that uses the cairo graphics library for rendering. See > ?bitmap and ?Cairo. > > Hope this helps, > > Paul > > G. Allegri wrote: > > Thanks Marcelo, > > I've tried using the suexec module in apache2 (it permits to change > > userid and groupid on the base of the scripts called), but from > > documentation appears to work only for CGI and SSI, not with > > mod_python. > > So, I change mailing-list, since the problem is almost OT now in this one > > :-) > > > > Giovanni > > > > 2008/1/16, Marcelo Oliveira <[EMAIL PROTECTED]>: > > > >> Giovanni, > >> > >> This issue could be related to user permissions. See if you can get > >> Apache running under a user with display access rights. > >> > >> Good Luck, > >> > >> Marcelo > >> > >> -----Original Message----- > >> From: [EMAIL PROTECTED] > >> [mailto:[EMAIL PROTECTED] On Behalf Of > >> [EMAIL PROTECTED] > >> Sent: Wednesday, January 16, 2008 6:00 AM > >> To: [email protected] > >> Subject: R-sig-Geo Digest, Vol 53, Issue 14 > >> > >> Send R-sig-Geo mailing list submissions to > >> [email protected] > >> > >> To subscribe or unsubscribe via the World Wide Web, visit > >> https://stat.ethz.ch/mailman/listinfo/r-sig-geo > >> or, via email, send a message with subject or body 'help' to > >> [EMAIL PROTECTED] > >> > >> You can reach the person managing the list at > >> [EMAIL PROTECTED] > >> > >> When replying, please edit your Subject line so it is more specific > >> than "Re: Contents of R-sig-Geo digest..." > >> > >> > >> Today's Topics: > >> > >> 1. Re: Spatially Constrained Clustering (Elias T. Krainski) > >> 2. regression kriging in gstat with skewed distributions (G. Allegri) > >> 3. I Would Dream ([EMAIL PROTECTED]) > >> 4. R from cgi and Xvfb (G. Allegri) > >> 5. Re: regression kriging in gstat with skewed distributions > >> (Tomislav Hengl) > >> > >> > >> ---------------------------------------------------------------------- > >> > >> Message: 1 > >> Date: Tue, 15 Jan 2008 10:51:48 -0300 (ART) > >> From: "Elias T. Krainski" <[EMAIL PROTECTED]> > >> Subject: Re: [R-sig-Geo] Spatially Constrained Clustering > >> To: [email protected] > >> Message-ID: <[EMAIL PROTECTED]> > >> Content-Type: text/plain; charset=iso-8859-1 > >> > >> Hello Carson, > >> > >> See the SKATER software at > >> http://www.est.ufmg.br/leste/skater.htm > >> The SKATER is a Spatial 'K'luster Analisys by Tree > >> Edge Removal. In future, this method also be available > >> in R. > >> > >> Best, > >> Elias. > >> > >> --- Carson Farmer <[EMAIL PROTECTED]> escreveu: > >> > >> > >>> Hello List, > >>> > >>> I am trying to find an R package that will > >>> accommodate spatially > >>> constrained clustering. While I have been unable to > >>> find a package that > >>> is explicitly designed to do spatially constrained > >>> clustering, I was > >>> wondering if anyone had found a package that would > >>> do constrained > >>> clustering of any kind, and adapted this to spatial > >>> constraints? > >>> I have searched the R site extensively, and googled > >>> all night long, but > >>> to no avail! I HAVE found this post: > >>> > >>> > >> http://finzi.psych.upenn.edu/R/Rhelp02a/archive/56819.html > >> > >>> but the replies did not help much. They lead to > >>> several packages which > >>> perform spatial clustering (such that significant > >>> clusters of say a > >>> disease are located within a study region), however, > >>> what I would like > >>> to do is partition a spatial (grid) dataset based on > >>> multiple variables, > >>> taking into account their spatial locations (i.e. > >>> clustering is based on > >>> the variables, but constrained so that clusters are > >>> spatially > >>> contiguous). I'm thinking mclust is probably the > >>> best way to go, but > >>> I'm not sure where to start. > >>> > >>> Any suggestions would be greatly appreciated. > >>> > >>> Thanks, > >>> > >>> Carson > >>> > >>> _______________________________________________ > >>> R-sig-Geo mailing list > >>> [email protected] > >>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo > >>> > >>> > >> Elias T. Krainski > >> > >> > >> > >> ------------------------------ > >> > >> Message: 2 > >> Date: Tue, 15 Jan 2008 15:27:58 +0100 > >> From: "G. Allegri" <[EMAIL PROTECTED]> > >> Subject: [R-sig-Geo] regression kriging in gstat with skewed > >> distributions > >> To: [email protected] > >> Message-ID: > >> <[EMAIL PROTECTED]> > >> Content-Type: text/plain; charset=WINDOWS-1252 > >> > >> I'm trying to realize e regression kriging with gstat package on my > >> soil samples data. The response variable (ECe measuere) and covariates > >> appear positvely skewed. > >> As Tomislav Hengl suggests in its "framework for RK" [1], a logistic > >> transformation is proposed as a generic way to reduce the skeweness by > >> using the physical limits of the data. > >> Is it really a transformation that can be applied in the generic case > >> of skewed datas? I mean,in my case I have non-normal residuals (from > >> original data regression), and I'm trying to transform the residuals > >> (and not the original values) to do SK on them . Is this approach > >> correct? > >> > >> A related question is how to do normal score transformations (for my > >> residuals) in R and gstat. I know gstat doesn't manage transformations > >> and back-transformations, so it should be done previously in R... but > >> I can't find any package that permit it in a straisghtforward way. > >> I've found something with qqnorm(ppoints(data)) and the approx() > >> function. Is that all? > >> > >> Giovanni > >> > >> > >> [1] "A generic framework for spatial prediction of soil variables > >> based on regressionkriging" Geoderma 122 (1?2), 75?93. > >> > >> > >> > >> ------------------------------ > >> > >> Message: 3 > >> Date: Tue, 15 Jan 2008 19:25:16 +0100 > >> From: <[EMAIL PROTECTED]> > >> Subject: [R-sig-Geo] I Would Dream > >> To: [email protected] > >> Message-ID: <[EMAIL PROTECTED]> > >> Content-Type: text/plain; charset=ISO-8859-1; format=flowed > >> > >> Kisses Through E-mail http://86.123.21.76/ > >> > >> > >> > >> ------------------------------ > >> > >> Message: 4 > >> Date: Wed, 16 Jan 2008 11:04:53 +0100 > >> From: "G. Allegri" <[EMAIL PROTECTED]> > >> Subject: [R-sig-Geo] R from cgi and Xvfb > >> To: [email protected] > >> Message-ID: > >> <[EMAIL PROTECTED]> > >> Content-Type: text/plain; charset=ISO-8859-1 > >> > >> Hi everyone. > >> I'm sorry for the question maybe OT. > >> I'm trying to use R and Python to run some scripts via web interface. > >> I've successfully setup mod_python for Apache and the rpy module. > >> R needs X11 to use png() and jpeg() devices, so I have installed Xvfb > >> (X virtual framebuffer). I works correctly: if I set the DISPLAY > >> variable to point to this X server, rpy can create png files correctly > >> from command-line, but it doesn't work when the python script is run > >> from web browser. > >> I restarted Apache after setting the DISPLAY variable, but the > >> Traceback gives me always the same error, about being not able to open > >> the X11 device? > >> > >> Does anyone have made it work right? > >> How can tell Apache to run R script and forwarding X requests to my > >> Xvfb. > >> > >> Thanks, > >> Giovanni > >> > >> > >> > >> ------------------------------ > >> > >> Message: 5 > >> Date: Wed, 16 Jan 2008 11:08:28 +0100 > >> From: "Tomislav Hengl" <[EMAIL PROTECTED]> > >> Subject: Re: [R-sig-Geo] regression kriging in gstat with skewed > >> distributions > >> To: "'G. Allegri'" <[EMAIL PROTECTED]> > >> Cc: [email protected] > >> Message-ID: <[EMAIL PROTECTED]> > >> Content-Type: text/plain; charset="windows-1250" > >> > >> > >> Dear Giovanni, > >> > >> Logit transformation can be automatically applied to any variables which > >> has a lower and upper > >> physical limits (e.g. 0-100%). In R, you can transform a variable to > >> logits by e.g.: > >> > >> > >>> points = read.dbf("points.dbf") > >>> points$SANDt = log((points$SAND/100)/(1-(points$SAND/100))) > >>> > >> After you interpolate your variable, you can back-transform the values > >> by using: > >> > >> > >>> SAND.rk = krige(fsand$call$formula, points[sel,], SPC, sand.rvgm) > >>> > >>> SAND.rk$pred=exp(SAND.rk$var1.pred)/(1+exp(SAND.rk$var1.pred))*100 > >>> > >> The prediction variance can not be back-transformed, but you can use the > >> normalized prediction > >> variance by dividing it with the sampled variance. See also section > >> 4.2.1 of my lecture notes > >> (http://geostat.pedometrics.org/). > >> > >> There are many transformations that can be applied to force a normality > >> of your target variable (see > >> e.g. http://en.wikipedia.org/wiki/Data_transformation_(statistics) ). > >> The most generic > >> transformation is to work with the probability density function values > >> (see e.g. > >> http://dx.doi.org/10.1016/j.jneumeth.2006.11.004 ), this way you do not > >> have to think about how the > >> histogram looks at all. But then the interpretation of the regression > >> plots becomes rather > >> difficult. > >> > >> In any case, you should apply the transformation already to the target > >> variable because also a > >> requirement for linear regression is that the residuals are normally > >> distributed around the > >> regression line. > >> > >> > >> see also: > >> FITTING DISTRIBUTIONS WITH R (by Vito Ricci) > >> http://cran.r-project.org/doc/contrib/Ricci-distributions-en.pdf > >> > >> > >> Tom Hengl > >> http://spatial-analyst.net > >> > >> > >> -----Original Message----- > >> From: [EMAIL PROTECTED] > >> [mailto:[EMAIL PROTECTED] On Behalf Of > >> G. Allegri > >> Sent: dinsdag 15 januari 2008 15:28 > >> To: [email protected] > >> Subject: [R-sig-Geo] regression kriging in gstat with skewed > >> distributions > >> > >> I'm trying to realize e regression kriging with gstat package on my > >> soil samples data. The response variable (ECe measuere) and covariates > >> appear positvely skewed. > >> As Tomislav Hengl suggests in its "framework for RK" [1], a logistic > >> transformation is proposed as a generic way to reduce the skeweness by > >> using the physical limits of the data. > >> Is it really a transformation that can be applied in the generic case > >> of skewed datas? I mean,in my case I have non-normal residuals (from > >> original data regression), and I'm trying to transform the residuals > >> (and not the original values) to do SK on them . Is this approach > >> correct? > >> > >> A related question is how to do normal score transformations (for my > >> residuals) in R and gstat. I know gstat doesn't manage transformations > >> and back-transformations, so it should be done previously in R... but > >> I can't find any package that permit it in a straisghtforward way. > >> I've found something with qqnorm(ppoints(data)) and the approx() > >> function. Is that all? > >> > >> Giovanni > >> > >> > >> [1] "A generic framework for spatial prediction of soil variables > >> based on regressionkriging" Geoderma 122 (1?2), 75?93. > >> > >> _______________________________________________ > >> R-sig-Geo mailing list > >> [email protected] > >> https://stat.ethz.ch/mailman/listinfo/r-sig-geo > >> > >> > >> > >> ------------------------------ > >> > >> _______________________________________________ > >> R-sig-Geo mailing list > >> [email protected] > >> https://stat.ethz.ch/mailman/listinfo/r-sig-geo > >> > >> > >> End of R-sig-Geo Digest, Vol 53, Issue 14 > >> > >> _______________________________________________ > >> R-sig-Geo mailing list > >> [email protected] > >> https://stat.ethz.ch/mailman/listinfo/r-sig-geo > >> > >> > > > > _______________________________________________ > > R-sig-Geo mailing list > > [email protected] > > https://stat.ethz.ch/mailman/listinfo/r-sig-geo > > > > > -- > Drs. Paul Hiemstra > Department of Physical Geography > Faculty of Geosciences > University of Utrecht > Heidelberglaan 2 > P.O. Box 80.115 > 3508 TC Utrecht > Phone: +31302535773 > Fax: +31302531145 > http://intamap.geo.uu.nl/~paul > > _______________________________________________ R-sig-Geo mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-geo
