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working_groups:ukurbangroup [2022/09/19 11:28]
acriado 		working_groups:ukurbangroup [2022/09/19 11:34]
acriado
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 module load RStudio/1.1.463-foss-2015a module load RStudio/1.1.463-foss-2015a
 module load R/3.6.1-foss-2015a-bare module load R/3.6.1-foss-2015a-bare
-module load GDAL/2.2.1-foss-2015a-GEOS-3.8.0 
-module load PROJ/6.1.1-foss-2015a 
-module load GEOS/3.8.0-foss-2015a 
-module load HDF5/1.10.5-foss-2015a 
 rstudio & rstudio &
 </code> </code>
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 To launch it in the workstation, you have to configure your //bashrc//: To launch it in the workstation, you have to configure your //bashrc//:
  
-  * <code bash>+  * Open your bashrc: 
 +<code bash>
 vi ~/.bashrc vi ~/.bashrc
- </code> +</code> 
-Open the Rstudio application:+ 
 +  * Save the modules:
 <code bash> <code bash>
-  * source ~/.bashrc+module load RStudio/1.1.463-foss-2015a 
 +module load R/3.6.1-foss-2015a-bare
 </code> </code>
-Open the Rstudio application:+ 
 +  * Save your bashrc:
 <code bash> <code bash>
-  * Launch the script :  +source ~/.bashrc
 </code> </code>
-Rscript [script]+  * Launch the script:
 <code bash> <code bash>
 +Rscript [script]
 +</code>
  
 ===== First Steps : understanding the scripts =====  ===== First Steps : understanding the scripts ===== 
Line 149: Line 151:
   * //#SBATCH --time=48:00:00// : if the user wants to apply for the first time (the secondary operations are not made yet) a whole year correction using all the applications available, with approximately between 30 and 50 cores for the parallelization. In this case, due to the high computational requirements of the job, we also recommend constraining the memory to "high": //#SBATCH --constraint=highmem//. For example, calculating the daily mean values of caliope urban during a whole year takes 6h of computational time using 50 cores.   * //#SBATCH --time=48:00:00// : if the user wants to apply for the first time (the secondary operations are not made yet) a whole year correction using all the applications available, with approximately between 30 and 50 cores for the parallelization. In this case, due to the high computational requirements of the job, we also recommend constraining the memory to "high": //#SBATCH --constraint=highmem//. For example, calculating the daily mean values of caliope urban during a whole year takes 6h of computational time using 50 cores.
   * //#SBATCH --time=01:00:00// : if the user wants to apply, without secondary operations and during a whole year, the applications of //UK// and //cross//, with approximately 30 cores for the parallelization.   * //#SBATCH --time=01:00:00// : if the user wants to apply, without secondary operations and during a whole year, the applications of //UK// and //cross//, with approximately 30 cores for the parallelization.
 +
 +The user has to charge the model in the //bashrc// (referred to the machine):
 +  * Open your bashrc:
 +<code bash>
 +vi ~/.bashrc
 +</code>
 +
 +  * Save the modules:
 +<code bash>
 +module load R
 +</code>
 +
 +  * Save your bashrc:
 +<code bash>
 +source ~/.bashrc
 +</code>
 +
  
 To submit the job regarding this methodology, the user only has to launch its own //[name].sh// archive with the Rscript //kriging_repository.R// followed by the configuration file. As an example: To submit the job regarding this methodology, the user only has to launch its own //[name].sh// archive with the Rscript //kriging_repository.R// followed by the configuration file. As an example:
working_groups/ukurbangroup.txt · Last modified: 2022/09/23 09:10 by acriado

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