Switch to parallelly and made functions hpc-friendly #24
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Moving package structure to devel
* changing from monthly to seasonal frequency (`htr_seasonal_frequency`) * shifting years forward or backward (`htr_shift_years`)
- Showing levels for each of the models to determine the level bounds of the depth domains needed by the user - Calculate the vertical weighted mean for each of the depth domains
Adding HPC functionality in the ff functions: -htr_merge_files -htr_slice_periods -changed to parallelly -hpc can either be "parallel" where each job runs things parallel for the different models, or "array" where each job runs things independently in each array -for hpc = array, the input is a specific file, which is fed into the R function using the SLURM script -for hpc = parallel, the input, like when hpc = NA (or system), is the input directory
- parallelly update - will only run function in parallel if hpc != "array" - if hpc == "array", function will just run as is
- changed some lines for hpc == "array" where to get the full path for each of the files
For some reason hpc == "array" didn't work??
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Switched over from
paralleltoparallelly, primarily to use the functionparallelly:availableCores(method = "Slurm", omit = n)Created new functionality for the hpc, where a parameter now exists for the hpc
hpc == NA, then everything runs as ishpc == "array", then you are running a job array in the hpc, and for most of the functions, you are passing over a single filehpc == "parallel", then you are running a job that uses a ton of CPUs and you will be running something on the HPC how you would run it on your system. Not ideal for UQ's Bunya