rgrass7 and snow
On Fri, 22 Apr 2016, Dr Didier G. Leibovici wrote:
Yes but then how the clusters use a different one i.e. how did you write your initGRASS()
I think that if you play around with execGRASS(), you'll find that your
temporary location has a PERMANENT mapset, and a working mapset. Look at
the directory to which you pointed home=; those two directories should be
present. Maybe use list.files(). Then use execGRASS("g.mapset",
mapset="<new0>", flags="c") to create one and switch to it. I guess you'd
need as many new mapsets as cores, and a vector of mapset names. Remember
that you can use g.mapsets to see or change your mapset search path, and
you can use the @mapset notation for any vector or raster, so the nodes
can each have their own spaces. Maybe use g.copy to copy data out to nodes
to avoid race conditions if reading from the same GRASS database file by
multiple nodes.
It would be useful to have an example of what you need to do, simulation
being fairly obvious, but I think r.in.gdal will be problematic, better to
read once and copy out to the simulation mapsets by repeated g.copy. The
more limited the use of initGRASS on each core, probably the better.
Hope this helps,
Roger
thanks On 22/04/2016 18:27, Rainer M Krug wrote:
"Dr Didier G. Leibovici" <didier.leibovici at nottingham.ac.uk> writes:
can you paste the call to create n mapsets. thanks
You can create a mapset with g.mapset -c mapset=THE_NAME_OF_THE_MAPSET You can do this in a loop in an R script, or bash script - whatever you are more familiar with. Rainer
On 22/04/2016 17:37, Rainer M Krug wrote: "Dr Didier G. Leibovici" <didier.leibovici at nottingham.ac.uk> writes: On 22/04/2016 16:21, Rainer M Krug wrote: Le vendredi 22 avril 2016, Dr Didier G. Leibovici <didier.leibovici at nottingham.ac.uk> a ?crit : Hi, we are trying to use 'grass' in parallel programming with 'snow' The code does multiple simulations of a r.viewshed resampling the points generating the viewshed. (I guess the other solution would be to have an equivalent of r.viewshed in an R library or script) ... I think the problems are to do with the gisDbase ... Testing with 2 clusters we start with:
> clusterCall(cl,initGRASS,"/usr/lib/grass70",home=getwd(),
gisDbase="GRASS_TEMP", override=TRUE )
[[1]]
gisdbase GRASS_TEMP
location file5edb6bf06d70
mapset file5edb4b0cda81
rows 1
columns 1
north 1
south 0
west 0
east 1
nsres 1
ewres 1
projection NA
[[2]]
gisdbase GRASS_TEMP
location file5edb6bf06d70
mapset file5edb4b0cda81
then read a DEM
clusterCall(cl,execGRASS,"r.in.gdal", flags="o",
parameters=list(input=baseDemFilename, output="DEM"))
clusterCall(cl,execGRASS, "g.region", parameters=list(raster="DEM"))
and then loop on the sampled points ... involving
execGRASS("r.viewshed", parameters = list(input = "DEM", output =
"cumulativeViewshed", max_distance=maxDistance, coordinates =
as.integer(coords[i,])), flags = c("overwrite" , "b","quiet"))
and cumulating the viewshed (reading the ouput using
readRAST("cumulativeViewshed")), all this (loop over the points)within a
function simul() called
by a
parSapply(cl,1:nDsimul,simul)
Here is the error
Error in checkForRemoteErrors(val) :
2 nodes produced errors; first error: no such file:
GRASS_TEMP/file5edb6bf06d70/file5edb4b0cda81/.tmp/geoprocessing/cumulativeViewshed
Calls: parSapply ... clusterApply -> staticClusterApply ->
checkForRemoteErrors
any idea?
The problem is likely that you are working in parallel in the same map set. I would suggest to use a separate Mauser for each parallel task to write to,
read from a different map set which no parallel task is writing to, and finally, after all threads are finished, you can collect the results from each thread
in one map set and delete the temporary map sets.
Cheers,
Rainer
Yes all the problem is there for each cluster to work on a separate GRASS_TEMP
( we have verified that it was running with I cl only!)
Can we generate randomly the location or mapset so they will not collapse onto the same?
I used a setup for parallel processing (simulating spread under
different scenarios), where I had
1) one locaction in which everything happened, which contained:
2) one mapset which was read-only for each parallel task
3) one mapset for each task in which the results were written; this was
a folder, which was created for each parallel task
4) one mapset into which the individual simulation tasks were analysed into.
So finally, I had a mapset for each simulation, and one in which the
analysis was.
So yes, why shouldn't you be able to create a mapset per task? You can
do it during the initialization by using GRASS.
Hope this helps,
Rainer
DIdier
thanks,
DIdier
--
Dr Didier G. Leibovici
d-d'ye ley-bow-v-c
Senior Research Fellow
Geocomputational Modelling & Geospatial Statistics
Nottingham Geospatial Institute
University of Nottingham, UK
+44 (0)115 84 13924
http://www.nottingham.ac.uk/ngi/people/didier.leibovici
Google+ didier.leibovici at gmail.com
Skype didierleibovici
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_______________________________________________ R-sig-Geo mailing list R-sig-Geo at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo -- Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology, UCT), Dipl. Phys. (Germany) Centre of Excellence for Invasion Biology Stellenbosch University South Africa Tel : +33 - (0)9 53 10 27 44 Cell: +33 - (0)6 85 62 59 98 Fax (F): +33 - (0)9 58 10 27 44 Fax (D): +49 - (0)3 21 21 25 22 44 email: Rainer at krugs.de Skype: RMkrug
-- Dr Didier G. Leibovici d-d'ye ley-bow-v-c Senior Research Fellow Geocomputational Modelling & Geospatial Statistics Nottingham Geospatial Institute University of Nottingham, UK +44 (0)115 84 13924 http://www.nottingham.ac.uk/ngi/people/didier.leibovici Google+ didier.leibovici at gmail.com Skype didierleibovici [[alternative HTML version deleted]]
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