R statistics/Installation
First of all you need to install R in your system.
R and many of its packages are pre-built and distributed through the CRAN network of mirrors. In addition many Linux distributions pre-package R and a number of the most popular libraries.
Status of "rgrass" packages
See overview here: https://cran.r-project.org/web/packages/rgrass/index.html
Source packages
From the R console first pick a local mirror:
chooseCRANmirror()
you can then see which repos has been picked with
options("repos")
To permanently save the mirror site add it to ~/.Rprofile. For example:
options(repos=c(CRAN="http://cran.stat.auckland.ac.nz"))
and then run install.packages() as in the Quick Start section above.
For more information see http://cran.r-project.org/doc/manuals/R-admin.html
Linux
Debian and Ubuntu
R and a number of pre-build cran packages are already present in the main repositories. Start with:
# apt-get install r-base r-cran-vr r-cran-rodbc r-cran-xml
Once those are installed start "R" at the command prompt and install the rgrass library:
install.packages("rgrass", dependencies = TRUE)
RPM based
- RedHat, Fedora, openSuse, ... and similar distros: take the latest R RPM and install it
R and a number of pre-build cran packages are already present in the main repositories. Start with:
# sudo dnf install R-core R-core-devel R-XML
Once those are installed, start "R" at the command prompt and install the rgrass library:
R
install.packages("rgrass", dependencies = TRUE)
Usage: You have the best user experience if you launch R or RStudio within a running GRASS GIS session (then R automatically recognizes the current settings of the Computational region and "sees" the GRASS maps).
Mac OSX
Start an R session, then
- for install.packages() you might have to rely on building packages from source code. try:
R
install.packages("rgrass", type="source", dependencies = TRUE)
Startup of GRASS from within R:
First you need to find the path to the GRASS binaries: Control-click on the GRASS.app and you'll get a popup menu; select "Show Package Contents" - this opens you to the directory structure. Go to Contents->MacOS which would be "GISBASE"; So, in my case, the "gisBase" parameter is "/HD/Applications/Grass-8.2.app/Contents/MacOS". If you Command-click at the top of the window on the folder icon beside "MacOS" (from the line above this one), you can see the full path.
Now we can run GRASS from within a R session:
library(rgrass)
initGRASS(gisBase ='/Applications/GRASS/GRASS-8.2.app/Contents/MacOS',
location = 'geostat2012_ll', mapset = 'user1',
gisDbase = '/Users/Lars/Documents/Biologi/grassdata', override = TRUE)
Troubleshooting
If you get an error message when trying to call GRASS from R containing this line: dyld: Library not loaded: /usr/local/lib/libintl.8.dylib you need to establish a link from /Applications/Grass/GRASS-8.2.app/Contents/MacOS/lib/libintl.8.dylib to /usr/local/lib. This can be done through Terminal with the command:
sudo ln -s /Applications/Grass/GRASS-8.2.app/Contents/MacOS/lib/libintl.8.dylib /usr/local/lib/
Note: The path to the GRASS-x.x.app and the version number in libintl.X.dylib must reflect your own configuration.
MS Windows
Installation
Run:
install.packages("rgrass", dependencies = TRUE)
or install Task View 'Spatial' - Analysis of Spatial Data
install.packages("ctv")
library("ctv")
install.views("Spatial")
Usage
In winGRASS (standalone installer and OSGeo4W) the installation path of R and RStudio are dynamically loaded into PATH.
- Start winGRASS, bring the winGRASS-windows console in front and type R for opening a R-session (command line mode) inside a GRASS-session.
- Start winGRASS, bring the winGRASS-windows console in front and type RGui for opening a R-session (GUI mode) inside a GRASS-session.