hakedataUSA

The goal of {hakedataUSA} is to provide code to extract and workup the U.S. data for the assessment of Pacific Hake.

Instructions

1. First, you must update data-raw/quotas.csv to include the sector-specific quotas. These values are used when processing the data, mainly for the creation of figures. Then, from within R, source data-raw/quotas.R and the internal data object will be updated and ready for use. Commit both data-raw/quotas.csv and data-quotas.rda to the repository and push.

2. Next, load the package. This can be accomplished through GitHub (first chunk) or using a local clone (second chunk).

   chooseCRANmirror(ind = 1)
   # install.packages("pak")
   pak::pak("pacific-hake/hakedataUSA")
   library(hakedataUSA)

   chooseCRANmirror(ind = 1)
   stopifnot(basename(getwd()) == "hakedataUSA")
   devtools::load_all()

3. The path to where all of the raw output will be saved is stored in an internal function, i.e., hakedata_wd(). Try it out, see if it works for you. If it does not work, then you will need to alter the function, which is stored in R/hakedata-R. The function should result in a path ending with data-tables inside of your cloned version of pacific-hake/hake-assessment.

4. The remainder of the code will pull from the data bases and set up the input files.

pull_database()
process_database()

write_bridging(
  dir_input = fs::path(dirname(hakedata_wd()), "models", "2022.01.10_base"),
  dir_output = fs::path(dirname(hakedata_wd()), "models", "2023", "01-version", "02-bridging-models")
)

Issues

Please contact [email protected] if there are issues with the code. Note that the databases will only be accessible to U.S. members of the JTC.