Chinook FRAM Post-processing

The framr package expedites Chinook FRAM post-processing tasks with framr::sps and framr::ayock_split.

Assuming the package and dependencies are installed (see Installation), then begin by loading the functions.

library(framr)

sps

The sps() function uses R and the RDCOMClient library to manipulate existing Excel files - no actual calculations are performed.

It is important to note that the TAMM(s) should already have the appropriate “starting block” values on the SPS Abundance Iterations sheet.

The function expects a single argument consisting of a file path or character vector of paths for the TAMMs in which SPS iterations are to be performed.

It is preferable to provide full file paths to reduce confusion, though relative paths could work if the directory with the target TAMMs is the current working directory.

Matching a regular expression within a target directory is a convenient way to build the input file paths for multiple TAMMs.

Running the function should result in Excel opening and “flickering” through the desired files; nothing is returned on completion.

dir_tamms <- "path/to/tamms/of/interest"

tamms <- list.files(dir_tamms, pattern = "year_or_some_file_name_REGEX.xlsx", full.names = T)

sps(tamm_file_paths = tamms)

While the RDCOMClient package is maintained, it will be inefficient to replicate the Chinook TAMM sheet “SPS Abundance Iterations” functionality in R, particularly if TAMM2FRAM progresses.

ayock_split

In addition to TAMM file paths, the ayock_split() function to perform “North/South Ayock Splits” requires a Mortality table from a Chinook FRAM project database. This path can be declared globally and then passed into the function.

The function extracts and summarizes the Chinook FRAM timestep 3 AEQ mortalities of HC FF in NT A12 sport, moving the NS and MSF components into the appropriate TAMM sheets & cells.

db <- "O:/chin_2021/Chinook_NOF_2021_FRAM_Database.mdb"

ayock_split(db = db, tamm_file_paths = tamms)

The function reads the RunName string(s) written by FRAM into the “TAMX!B2” cell on the files of interest, and then uses these values to get the associated RunID values. These are used to filter the Mortality table (in addition to hard-coded stock, fishery and timestep conditions).

Again, successful completion does not return anything to the R session, although a tibble of metadata and values is printed to the console.