lake-temperature-process-models

Dependent files from pipeline #1 lake-temperature-model-prep:

• feature_crosswalk.rds and .ind
• lakes_sf.rds and .ind
• NLDAS_grid coords and cell resolution

The following files are dependencies in pipeline #3 lake-temperature-neural-networks:

• feature_nldas_coords.rds and .ind

If any of these files are changed / updated in this pipeline, remember to:

1. copy the update .rds file to the dependent pipeline's drive (which is hyperlinked above) and to ALSO
2. copy the updated .ind file to the dependent pipeline's github repository (which is also hyperlinked above)

end around on the batch jobs

In order to get around the issue with UV being down, my VM being slow, and normal being even slower in batch mode, I set up a single node in normal for interactive mode, and ran scmake in R.

I used rsync to get the new task table up to Yeti:

rsync -avz 3_pb0_src_trg_tasks.yml [email protected]:/cxfs/projects/usgs/water/iidd/data-sci/lake-temp/lake-temperature-process-models/3_pb0_src_trg_tasks.yml

#or
rsync -avz 3_pb0_hyperscales_tasks.yml [email protected]:/cxfs/projects/usgs/water/iidd/data-sci/lake-temp/lake-temperature-process-models/3_pb0_hyperscales_tasks.yml

Used salloc to get 7 hours in interactive (in the end, I needed 5.5hrs to run 450 models):

salloc -A cida -n 1 -p normal -t 7:00:00

then ssh'd into the node I was given, and from there, got into the working directory

ssh n3-98
cd /cxfs/projects/usgs/water/iidd/data-sci/lake-temp/lake-temperature-process-models

As a test of loop_tasks in parallel, I asked for 4 cores

salloc -A cida -n 4 -p normal -t 7:00:00

rsync -avz pb0_src_trg_plan.rds [email protected]:/cxfs/projects/usgs/water/iidd/data-sci/lake-temp/lake-temperature-process-models/pb0_src_trg_plan.rds
rsync -avz hyperscales_pb0_plan.rds  [email protected]:/cxfs/projects/usgs/water/iidd/data-sci/lake-temp/lake-temperature-process-models/hyperscales_pb0_plan.rds

loaded modules on the node and then scipiper::loop_tasks() after installing foreach and doParallel on Yeti:

loop_tasks(task_plan = readRDS('pb0_src_trg_plan.rds'), task_makefile = '3_pb0_src_trg_tasks.yml', n_cores = 4)
#or
loop_tasks(task_plan = readRDS('hyperscales_pb0_plan.rds'), task_makefile = '3_pb0_hyperscales_tasks.yml', n_cores = 8)

setting up Yeti

This project is in /cxfs/projects/usgs/water/iidd/data-sci/lake-temp/lake-temperature-process-models

I have set up the R library dir in /cxfs/projects/usgs/water/iidd/data-sci/lake-temp/lake-temperature-process-models/Rlib and used .Renviron file in the project root to specify R_LIBS=...

For installing packages, I did

module avail #list of all avail
module purge #DON'T DO THIS???
module load legacy # had to do this w/ Yeti refresh
module load R/3.6.3
module load tools/nco-4.7.8-gnu 
module load tools/netcdf-c-4.3.2-intel #tools/netcdf-c-4.6.2-gnu need this because there is a Yeti error where 
#module load gdal/2.2.0-gcc
#module load proj/5.2.0-gcc-7.1.0


#module load tools/nco-4.4.4-gnu ??tools/nco-4.7.8-gnu 
#module load tools/netcdf-4.3.2-gnu ??tools/netcdf-c-4.6.2-gnu

 module list
Currently Loaded Modulefiles:
  1) tools/nco-4.4.4-gnu      3) tools/hdf5-1.8.13-gnu    5) tools/netcdf-4.3.2-gnu
  2) tools/hdf-4.2.10-gnu     4) tools/szip-2.1-gnu
  
  WORKED!!
install.packages("GLMr", repos=c("https://owi.usgs.gov/R",getOption("repos")))

??
module load hdf5/1.8.18-gcc6.1.0
[jread@yeti-login20 lake-temperature-process-models] module load netcdf/4.4.1.1-gcc6.1.0

then R

from R:

install.packages(c('stringi','stringr','dplyr','tidyr','rLakeAnalyzer','lubridate','remotes','ncdf4','readr','feather'))

library(remoates)
install_github('tidyverse/[email protected]')
install_version("vctrs", version = "0.2.4", repos = "http://cran.us.r-project.org")
install_version("tidyr", version = "1.0.0", repos = "http://cran.us.r-project.org")

#remotes::install_github('GLEON/GLM3r')
#remotes::install_github('GLEON/GLMr')
remotes::install_github('usgs-r/glmtools')
#remotes::install_github('mrc-ide/syncr')

This project uses rsync and ssh to pull/push data/predictions from Yeti in the 1_get_lake_attr and 2_model phase. For this to work, SSH keys must be set up for communication with Yeti:

• If you don't yet have a local ssh key pair, use ssh-keygen -t rsa from within a local terminal.
• Copy the public key to Yeti with ssh-copy-id [email protected] (also from within your local terminal). You can then check that you're set up by running ssh [email protected] from a terminal - it should log you in without a password.
• On Windows with RStudio, there will be a problem in that SSH/rsync assume your .ssh folder is at ~/.ssh, but ~ means C:/Users/username within a terminal but C:/Users/username/Documents within RStudio. Therefore you should create a symlink for the .ssh folder by calling ln -s ~/.ssh ~/Documents/.ssh in a bash shell.

my workflow

I build things locally and some (not all) sync to Yeti as part of the process. Seems rsync is faster than the cross-platform ssh package I need to sync nmls and drivers to yeti, then use the "out" job list (rds) to tell yeti what to do When the job list is on yeti, I need to modify the batch file with the same number of array jobs that appear in the job table When the jobs are done, I sync from yeti (see below) the feather files. Then I run a failed job array (same process as above) which picks up maybe a few more lakes when they run again. I don't know why they'd fail the first time but not the second. Doesn't make sense to me and I haven't dug into the lobs.

So, this is clunky and seems that if I used drake instead on Yeti, I would be happier.

Still some pain points with moving files around to and from Yeti. Kinda slow and maybe I should zip files or something (although rsync must be compressing, right?)

sync to yeti

cd 2_prep/sync
rsync -avz .  [email protected]:/cxfs/projects/usgs/water/iidd/data-sci/lake-temp/lake-temperature-process-models/2_prep/sync

# sync the job lists to yeti:
cd 2_prep/out
rsync -avz .  [email protected]:/cxfs/projects/usgs/water/iidd/data-sci/lake-temp/lake-temperature-process-models/2_prep/out

# sync task table to yeti:
rsync -avz 3_pb0_src_trg_tasks.yml [email protected]:/cxfs/projects/usgs/water/iidd/data-sci/lake-temp/lake-temperature-process-models/3_pb0_src_trg_tasks.yml

rsync -avz 3_pb0_hyperscales_tasks.yml [email protected]:/cxfs/projects/usgs/water/iidd/data-sci/lake-temp/lake-temperature-process-models/3_pb0_hyperscales_tasks.yml

sync from yeti

cd 3_run/sync
rsync -avz [email protected]:/cxfs/projects/usgs/water/iidd/data-sci/lake-temp/lake-temperature-process-models/3_run/sync/. .

cd 3_run/out
rsync -avz [email protected]:/cxfs/projects/usgs/water/iidd/data-sci/lake-temp/lake-temperature-process-models/3_run/out/pb0_src_trg_tasks.rds.ind pb0_src_trg_tasks.rds.ind 

rsync -avz [email protected]:/cxfs/projects/usgs/water/iidd/data-sci/lake-temp/lake-temperature-process-models/3_run/out/pb0_hyperscales_tasks.ind pb0_hyperscales_tasks.ind