[R-sig-Geo] 4. R from cgi and Xvfb (G. Allegri)
G. Allegri
giohappy at gmail.com
Wed Jan 16 16:14:40 CET 2008
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 <p.hiemstra at geo.uu.nl>:
> 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 <moliveira at geostats.com>:
> >
> >> 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: r-sig-geo-bounces at stat.math.ethz.ch
> >> [mailto:r-sig-geo-bounces at stat.math.ethz.ch] On Behalf Of
> >> r-sig-geo-request at stat.math.ethz.ch
> >> Sent: Wednesday, January 16, 2008 6:00 AM
> >> To: r-sig-geo at stat.math.ethz.ch
> >> Subject: R-sig-Geo Digest, Vol 53, Issue 14
> >>
> >> Send R-sig-Geo mailing list submissions to
> >> r-sig-geo at stat.math.ethz.ch
> >>
> >> 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
> >> r-sig-geo-request at stat.math.ethz.ch
> >>
> >> You can reach the person managing the list at
> >> r-sig-geo-owner at stat.math.ethz.ch
> >>
> >> 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 (vacates at patiencegroup.com)
> >> 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" <eliaskrainski at yahoo.com.br>
> >> Subject: Re: [R-sig-Geo] Spatially Constrained Clustering
> >> To: r-sig-geo at stat.math.ethz.ch
> >> Message-ID: <569895.79461.qm at web50604.mail.re2.yahoo.com>
> >> 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 <cfarmer at uvic.ca> 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
> >>> R-sig-Geo at stat.math.ethz.ch
> >>> 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" <giohappy at gmail.com>
> >> Subject: [R-sig-Geo] regression kriging in gstat with skewed
> >> distributions
> >> To: r-sig-geo at stat.math.ethz.ch
> >> Message-ID:
> >> <e12429640801150627q7266a599g77a3df9744edb153 at mail.gmail.com>
> >> 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: <vacates at patiencegroup.com>
> >> Subject: [R-sig-Geo] I Would Dream
> >> To: r-sig-geo at stat.math.ethz.ch
> >> Message-ID: <478CFA8C.7030508 at patiencegroup.com>
> >> 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" <giohappy at gmail.com>
> >> Subject: [R-sig-Geo] R from cgi and Xvfb
> >> To: r-sig-geo at stat.math.ethz.ch
> >> Message-ID:
> >> <e12429640801160204h3532ddb9t624b4f6ef658c975 at mail.gmail.com>
> >> 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" <hengl at science.uva.nl>
> >> Subject: Re: [R-sig-Geo] regression kriging in gstat with skewed
> >> distributions
> >> To: "'G. Allegri'" <giohappy at gmail.com>
> >> Cc: r-sig-geo at stat.math.ethz.ch
> >> Message-ID: <001401c85827$bdac65a0$3a871291 at pcibed193>
> >> Content-Type: text/plain; charset="windows-1250"
> >>
> >>
> >> Dear Giovanni,
> >>
> >> Logit transformation can be automatically applied to any variables which
> >> has a lower and upper
> >> physical limits (e.g. 0-100%). In R, you can transform a variable to
> >> logits by e.g.:
> >>
> >>
> >>> points = read.dbf("points.dbf")
> >>> points$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: r-sig-geo-bounces at stat.math.ethz.ch
> >> [mailto:r-sig-geo-bounces at stat.math.ethz.ch] On Behalf Of
> >> G. Allegri
> >> Sent: dinsdag 15 januari 2008 15:28
> >> To: r-sig-geo at stat.math.ethz.ch
> >> 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
> >> R-sig-Geo at stat.math.ethz.ch
> >> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> >>
> >>
> >>
> >> ------------------------------
> >>
> >> _______________________________________________
> >> R-sig-Geo mailing list
> >> R-sig-Geo at stat.math.ethz.ch
> >> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> >>
> >>
> >> End of R-sig-Geo Digest, Vol 53, Issue 14
> >>
> >> _______________________________________________
> >> R-sig-Geo mailing list
> >> R-sig-Geo at stat.math.ethz.ch
> >> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> >>
> >>
> >
> > _______________________________________________
> > R-sig-Geo mailing list
> > R-sig-Geo at stat.math.ethz.ch
> > 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
>
>
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