...
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module load libiconv/1.17 udunits gdal/3.6.0 r/4.2.2
source /gpfs/sharedfs1/admin/hpc2.0/apps/gdal/3.6.0/spack/share/spack/setup-env.sh
spack load gdal
module load libcurl/8.6.0
R
> .libPaths("~/rlibs")
> install.packages("RCurl", lib = "~/rlibs", repo = "https://cloud.r-project.org/")
> library(RCurl)
>
> curlVersion()$protocols
[1] "dict" "file" "ftp" "ftps" "gopher" "gophers" "http"
[8] "https" "imap" "imaps" "mqtt" "pop3" "pop3s" "rtsp"
[15] "scp" "sftp" "smb" "smbs" "smtp" "smtps" "telnet"
[22] "tftp" |
SF R package
After building the gdal dependency tree from source, the SF R package has issues pulling from the paths set by the modules loaded on HPC for sqlite3 and proj.
To bypass the issue, certain configure flags need to be set within the R install.packages command that is used to install the SF package.
To install the SF R package under a local HPC directory the following modules would need to be loaded and the following R command to be used:
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module load udunits gdal/3.8.4 r/4.3.2
R
> .libPaths("~/rlibs")
> install.packages("sf", lib = "~/rlibs", type = "source", configure.args = c("--with-sqlite3-lib=/gpfs/sharedfs1/admin/hpc2.0/apps/sqlite/3.45.2/lib", "--with-proj-lib=/gpfs/sharedfs1/admin/hpc2.0/apps/proj/9.4.0/lib64"), repo = "https://cloud.r-project.org/") |
The above install.packages command should be successful.
Once installed, sf should run normally and the configur flags above would no longer need to be used.