The goal of {hakedataUSA} is to provide code to extract and workup the U.S. data for the assessment of Pacific Hake.
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.
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()
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.
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")
)
Please contact kelli.johnson@noaa.gov if there are issues with the code. Note that the databases will only be accessible to U.S. members of the JTC.