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. 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?).
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 <mlenn...@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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