knitr::opts_chunk$set( collapse = TRUE, eval = F, comment = "#>" )
library(gfdata) library(groundfishr) # globals ---- year = 2021 species <- "SABL" rec_age <- 3 plus_age <- 42 TAC <- c(14957, 15068, 18293) # TAC from last 3 years (year-3, year-2, year-1) admb_home <- "C:/Program Files (x86)/ADMB-12.1" # more common to be "C/ADMB" model_name <- "sabl" dat_name <- "sabl_2021" afsc_user = "your_user_name" afsc_pwd = "your_password" akfin_user = "your_user_name" akfin_pwd = "your_password" mcmc = 1e+06 mcsave = 2000 # data ---- # setup folders setup(year) # raw data query sablefish(year, akfin_user, akfin_pwd, afsc_user, afsc_pwd) # clean and process data ---- # catch clean_catch(year = year, TAC = TAC) # survey biomass ts_biomass(year) # this is the design-based model, must provide separate file for VAST output # biological data age_error( species = species, year = year, admb_home = admb_home) # file in data/user_input folder size_at_age(year, admb_home, rec_age, lenbins = NULL) fish_age_comp(year, rec_age, plus_age) ts_age_comp(year, rec_age, plus_age) fsh_length_comp(year, rec_age) ts_length_comp(year) saa(year, admb_home, rec_age) waa(year, admb_home, rec_age) # create data file in the "db" folder concat_dat(year, "db", rec_age, plus_age) # change the survey to the VAST estimated ts_biomass(year, "VAST_estimate.csv") # file in data/user_input folder concat_dat(year, "vast", rec_age, plus_age) run_admb(year, model, model_name, mcmc, mcsave) # cleanup output ---- process_results(year, model = "db", model_name, data_name, rec_age, plus_age, mcmc = mcmc, mcsave = mcsave) process_results(year, model = "vast", model_name, data_name, rec_age, plus_age, mcmc = mcmc, mcsave = mcsave) # create base plots and tables base_plots(year, model, model_name, rec_age) base_tables(year, model, model_name)
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