Greetings - I am using R 2.15.2 on Windows 7 and am seeking help with the
spsample function in R. I have a polygon dataset (n= 5733) and I'm trying
to use the spsample function to sample the polygons to create a point
dataset. I'm using sapply to create the sample based on code I found here:
http:
Sorry for the barrage of emails, but here is a more relevant example
with two parallel solutions:
install.packages("spatial.tools",
repos="http://R-Forge.R-project.org",type="source";)
library(spatial.tools)
# The function passed to rasterEngine does the looping via lapply:
classID_rasterEngine_f
There is typically a diminishing returns with larger and larger
"chunks", but there is a low-end in terms of file size and chunk size
for how much parallel processing helps. However, if you are only
reading and writing once, I don't see too much of an advantage of
loading everything into memory on
Is it so that system.time in this case can strongly depend on how much data is
placed in RAM? In my case, I'm far from being memory limited (RAM = 192 Gb) and
most of the time, it's faster to put everything in memory and then process it.
The major limiting speed factor here is I/O.
yan
Yan Bou
Many thanks Jonathan, Alex and Forrest,
This is very helpful information. I'll see what's the best between calc and
rasterEngine.
Sincerely,
Yan
Yan Boulanger, Chercheur scientifique / Research scientist
Ressources Naturelles Canada, Canadian Forest Service
Centre de Foresterie des Laurenti
Yan:
Looks like you are getting great help with this -- I want to echo
Alex's note that rasterEngine is not a catchall -- for REALLY simple
processes you'll get better performance using calc() or using LESS
workers (which may seem counter intuitive). I'm submitting a paper
this week that showed t
On Wed, Mar 12, 2014 at 11:29 PM, Boulanger, Yan
wrote:
> Actually, I have several rasters of more than 440 000 000 pixels (MODIS
> covering all Canada) and I have a 32-cores machine so I would like to take
> advantage of it! ;-)
>
> Time is money (really?!!)
As mentioned earlier, I would be ca
