[GRASS-dev] R and GRASS integration
Rainer M Krug
Rainer at krugs.de
Wed Jan 6 09:24:58 PST 2016
Paulo van Breugel <p.vanbreugel at gmail.com> writes:
> On Wed, Jan 6, 2016 at 10:27 AM, Rainer M Krug <Rainer at krugs.de>
> wrote:
>
> Paulo van Breugel <p.vanbreugel at gmail.com> writes:
>
> > I by any stretch of imagination a developer, but I did use the
> > combination of shell or pythons script with R, basically
> following the
> > approach you described, having a python or shell script write a
> R
> > script to a text file and run it. I think it can work well, and
> not
> > that much harder to maintain. But I also would be very
> interested to
> > learn how to do this better. I also would be interested to see
> the
> > randomForest scripts you mentioned Steven, are you already
> sharing it
> > somewhere?
> >
> > As you mentioned, there are probably many people using / writing
> R
> > scripts that interact with GRASS. For some it will be easier, or
> it
> > may be more logical for them, to turn these into R packages
> rather
> > than writing a GRASS addon.
>
> I am one of those. I have thought about making a GRASS (or QGIS)
> addon /
> plugin, but I stayed with the R package. I have a complete
> simulation
> written in R which uses spatial data from GRASS, does simulations,
> and
> returns the results to GRASS.
>
>
> To run the simulations in itself is a three liner in R.
>
> > It would be nice if there would be some kind of repository where
> > people share such code (github perhaps?). I am sure there are
> existing
> > ones on e.g., github, so perhaps just a GRASS-wiki page listing
> > existing repositories would be enough. I know there is
> > https://grasswiki.osgeo.org/wiki/R_statistics, but I don't think
> there
> > is an place on the GRASS website, wiki or trac to share/list R
> code?
> > Would this be of interest to create such page (on the Wiki
> perhaps?).
>
> Different people use different repos (I use e.g. github and
> gitlab) so
> creating another place where I should publish my code would be not
> really an option. What would be an idea to make it easy (probably
> even
> easier even than editing a wiki page?) to add a repo to a list of
> projects which integrate R in GRASS or GRASS in R, and which could
> indicate the last commit to aser if the repos are current or just
> archives from e.g. papers or finished projects.
>
>
> +1 That would be something quick to implement. However, what form did
> you have in mind, if not a wiki page? I wouldn't mind creating such
> page, but perhaps first some further ideas on the best form from
> others as well.
I thought about a field, where I just add the link to the repository and
some info (Author, short description, possibly License type, ...) and
this is automatically added to the page including information from the
repo like last updated, link to the README, ... But this might be
getting to complicated. But I know it from my side - editing a wiki page
is often a "will do later" thing.
Also a system where there is an form where one fills in the info and it
is emailed to somebody to add it to the wiki would work.
>
> My repo is private at the moment, but I plan to make it open in
> the next
> few weeks.
>
> A brief presentation about a very similar simulation model can be
> found at
>
> https://github.com/rkrug/INTECOL_2013_Optimizing
>
>
>
>
> Thanks for sharing, interesting. Looking forwards seeing some further
> code
Thanks - I will keep you posted.
Coming back to the initial question:
What we would need in the meantime is possibly a discussion, on how R
functions could be used in an automated way - i.e. something along the
lines of an R package, which contains a set of defined functions like:
getFunctionNames() :: which returns the function names which can be
called from GRASS
getFunctionInterface(functionName) :: which returns the arguments of the
function functionName (similar to the interfaceDescription (I think it
is called differently) in GRASS commands)
would make it possible to just
1) load any R package which has these functions
2) and get all function names and arguments needed
3) and just call the R function in an easy way like
g.call.R package=PACKAGENAME function=FUNCTIONNAME
arguments="arguments for the R function)
The function could than be executed by using either a relatively simple python or
direct Rscript approach.
Also, one could even dynamically load an R package and construct all the
calls including help, so they could be called by using
g.call.R.PACKAGENAME.FUNCTIONNAME arg1=ARG1 arg2=ARG2
From the R side, this would be relatively easy to include, (there are
the packages rgrass7 and spgrass6 to interact with GRASS 7 and 6) and it
I think that it should not be to difficult to implement on the GRASS side.
This would than be very similar to the approach which rgrass7 (and
spgrass6) are using by querying the interface and than doing the
checking, and if everything seems consistent, call the GRASS command.
Just some thoughts,
Rainer
>
> My gitlab repos (most or all private at the moment) are at
>
> https://gitlab.com/rkrug/asm
>
> and the simulation is at (also still private but it will change
> soon)
>
> https://gitlab.com/rkrug/asm
>
> For reference, my github page is at
>
> https://github.com/rkrug
>
> Cheers,
>
> Rainer
>
>
>
>
> >
> > Paulo
> >
> >
> > On 04-01-16 16:14, Steven Pawley wrote:
> >> Thank you Moritz,
> >>
> >> Yes I have also had difficulties with Rpy2 apart from on
> >> Linux. Also, Rpy2 is quite onerous in terms of effort required
> to
> >> integrate R scripts into Python. Your solution certainly works,
> but
> >> as you mentioned it makes the R script harder to maintain.
> PypeR is
> >> another alternative and is straightforward to install and is
> simpler
> >> from a user perspective.
> >>
> >> I would also be interested in hearing opinions from 'true'
> >> developers who have much greater expertise than myself in this
> area.
> >>
> >> Kind regards,
> >>
> >> Steve
> >>
> >>> On Jan 4, 2016, at 2:31 AM, Moritz Lennert
> <mlennert at club.worldonline.be> wrote:
> >>>
> >>>> On 04/01/16 10:28, Moritz Lennert wrote:
> >>>>> On 03/01/16 23:54, Steven Pawley wrote:
> >>>>> Like many R-GRASS users, I have a collection of R scripts
> that
> >>>>> interact with GRASS to perform various workflows. I have
> debated
> >>>>> about converting these to Python using Rpy2, although this
> package
> >>>>> can be a difficult to install on all platforms and depends
> on
> >>>>> specific versions of R and Python. I noticed that Moritz
> Lennert
> >>>>> recently developed a GRASS add on which consists of simply
> writing
> >>>>> out the R commands to a temporary script for R to run.
> >>>> [...]
> >>>>> Does this represent a desirable or even acceptable approach
> for
> >>>>> embedding R scripts into grass add ons, or is Rpy2 the
> 'official'
> >>>>> approach.
> >>>> I wouldn't consider my approach in any way official, but
> AFAIK, rpy2
> >>>> does not have any "official" status in GRASS either. In my
> particular
> >>>> case (v.class.mlR) this was a quick and dirty hack for a
> course I had to
> >>>> teach. The difficulty of getting rpy2 installed on the lab
> machines on
> >>>> short notice was one of the motivations not to use it. I also
> agree that
> >>>> dependency on rpy2 can be a nuisance and has caused me some
> headaches
> >>>> with other modules, before. However, the approach I used (and
> others
> >>>> have used before) is a bit unwieldy and makes maintaining
> such modules a
> >>>> bit of a pain.
> >>>>
> >>>> So, I'm curious to hear the opinions of others...
> >>> See [1] for a related issue.
> >>>
> >>> Moritz
> >>>
> >>> [1] https://trac.osgeo.org/grass/ticket/1290
> >> _______________________________________________
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> >> grass-dev at lists.osgeo.org
> >> http://lists.osgeo.org/mailman/listinfo/grass-dev
> >
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>
>
> --
> Rainer M. Krug
> email: Rainer<at>krugs<dot>de
> PGP: 0x0F52F982
>
>
>
--
Rainer M. Krug
email: Rainer<at>krugs<dot>de
PGP: 0x0F52F982
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