fixing function to get_amak_dat

content/AFSC-BSAI_AtkaMackerel.qmd

@@ -46,19 +46,10 @@ FIMS_commit <- substr(packageDescription("FIMS")$GithubSHA1, 1, 7)
 
 ## Simplifications to the original assessment
 
-The model presented in this case study was changed substantially from the operational version and should not be considered reflective of the pollock stock. This is intended as a demonstration and nothing more.
+The model presented in this case study was changed substantially from the operational version and should not be considered reflective of the BSAI Atka mackerel stock. 
 
 To get the opertional model to more closely match FIMS I:
-* Removed bias correction in log-normal index likelihoods
-* Simplified catchability of survey 3 to be constant in time (removed random walk)
-* Updated maturity to be parametric rather than empirical
-* Used constant weight at age for all sources: spawning, fishery, surveys, and biomass calculations. The same matrix was used throughout.
-* Changee timing to be Jan 1 for spawning and all surveys
-* Removed prior on catchability for survey 2
-* Removed time-varying fisheries selectivity (constant double logistic)
-* Took off normalization of selectivity
-* Removed age accumulation for fishery age compositions
-
+* stumbled lots
 
 ## Script to prepare data for building FIMS object
 ```{r}
@@ -68,8 +59,8 @@ To get the opertional model to more closely match FIMS I:
 
 ## define the dimensions and global variables
 #  Opent the original AMAK file
-atka_dat <- readRDS("data_files/atka_dat.RDS")
-atka_rep <- readRDS("data_files/atka_rep.RDS")
+atka_dat <- readRDS(here::here("content","data_files","atka_dat.RDS"))
+atka_rep <- readRDS(here::here("content","data_files","atka_rep.RDS"))
 ## define the dimensions and global variables
 years <- atka_dat$styr:atka_dat$endyr
 nyears <- length(years)
@@ -92,6 +83,7 @@ ages <- 1:nages
 
 
 How I simplified my assessment:
+* Haven't got there yet...
 
 
 ## Script that sets up and runs the model
@@ -125,83 +117,76 @@ estimate_recdevs <- TRUE
 
 # q: What is the definition of the standard deviation of the index data?
 # a: The standard deviation of the index data is the standard deviation of the log-transformed index data. This is the standard deviation of the log-transformed index data, not the standard deviation of the index data itself. The standard deviation of the index data is the standard deviation of the index data itself.
-fimsdat<-atka_dat
-get_amak_data <- function(rdat){
+get_amak_data <- function(rdat,rrep){
 ## put into fims friendly form
-res <- data.frame(type = character(),
+  res <- data.frame(type = character(),
                   name = character(),
                   age = integer(),
                   datestart = character(),
                   dateend = character(),
                   value = double(),
                   unit = character(),
                   uncertainty = double())
-landings <- data.frame(type = "landings",
+  landings <- data.frame(type = "landings",
                        name = "fleet1",
                        age = NA,
-                       datestart = paste0(seq(fimsdat$styr, fimsdat$endyr), "-01-01"),
-                       dateend = paste0(seq(fimsdat$styr, fimsdat$endyr), "-12-31"),
-                       value = as.numeric(fimsdat$catch),
+                       datestart = paste0(seq(rdat$styr, rdat$endyr), "-01-01"),
+                       dateend = paste0(seq(rdat$styr, rdat$endyr), "-12-31"),
+                       value = as.numeric(rdat$catch),
                        unit = "t",
-                       uncertainty = fimsdat$catch_cv)
-  # Now do same loop but fill in where data exists
-# [1] "styr"                "endyr"               "rec_age"             "n_ages"              "number_length_inter"
-#[6] "Length_bins"         "nfsh"                "catch"               "catch_cv"            "n_ages_fsh"         
-#[11] "n_lengths_fsh"       "yrs_ages_fsh"        "sample_ages_fsh"     "page_fsh"            "wt_age_fsh"         
-#[16] "nind"                "nobs_ind"            "yrs_ind"             "month_ind"           "biom_ind"           
-#[21] "biom_std"            "n_ages_ind"          "n_lengths_ind"       "yrs_ages_ind"        "sample_ages_ind"    
-#[26] "page_ind"            "wt_age_ind"          "wt_age_pop"          "maturity"            "spmonth"            
-#[31] "age_err"            
+                       uncertainty = rdat$catch_cv)
 ##  need to fill missing years with -999 so it's ignored in FIMS
-indtmp <- 0*fimsdat$catch-999
-indtmp[which(years %in% fimsdat$yrs_ind )] <- fimsdat$biom_ind
+  indtmp <- 0*rdat$catch-999
+  indtmp[which(years %in% rdat$yrs_ind )] <- rdat$biom_ind
 #indtmp
-CVtmp <- rep(1, length=nyears) # actually SE in log space
-CVtmp[which(years %in% fimsdat$yrs_ind)] <- fimsdat$biom_std/fimsdat$biom_ind
+  CVtmp <- rep(1, length=nyears) # actually SE in log space
+  CVtmp[which(years %in% rdat$yrs_ind)] <- rdat$biom_std/rdat$biom_ind
 ## repeat with fish catch at age, using expected in missing years
 #names(atka_rep)
-caa <- 0*atka_rep$N[,-1]-999
-caa[which(years %in% fimsdat$yrs_ages_fsh), ] <- fimsdat$page_fsh
+caa <- 0*rrep$N[,-1]-999
+caa[which(years %in% rdat$yrs_ages_fsh), ] <- rdat$page_fsh
 Ncaa <- rep(1, nyears)
-Ncaa[which(years %in% fimsdat$yrs_ages_fsh)] <- fimsdat$sample_ages_fsh
-paa2 <-  0*atka_rep$N[,-1]-999
-paa2[which(years %in% fimsdat$yrs_ages_ind), ] <- fimsdat$page_ind
+Ncaa[which(years %in% rdat$yrs_ages_fsh)] <- rdat$sample_ages_fsh
+paa2 <-  0*rrep$N[,-1]-999
+paa2[which(years %in% rdat$yrs_ages_ind), ] <- rdat$page_ind
 Npaa2 <- rep(1, nyears)
-Npaa2[which(years %in% fimsdat$yrs_ages_ind)] <- fimsdat$sample_ages_ind
+Npaa2[which(years %in% rdat$yrs_ages_ind)] <- rdat$sample_ages_ind
 index <- data.frame(type = "index",
                     name = "survey",
                     age = NA,
-                    datestart = paste0(seq(fimsdat$styr, fimsdat$endyr), "-01-01"),
-                    dateend = paste0(seq(fimsdat$styr, fimsdat$endyr), "-12-31"),
+                    datestart = paste0(seq(rdat$styr, rdat$endyr), "-01-01"),
+                    dateend = paste0(seq(rdat$styr, rdat$endyr), "-12-31"),
                     value = ifelse(indtmp>0, indtmp, indtmp),
                     unit = "",
                     uncertainty = CVtmp)
 ## these have -999 for missing data years
 catchage <- data.frame(type = "age",
                        name = "fleet1",
                        age = rep(seq(1,nages), nyears),
-                       datestart = rep(paste0(seq(fimsdat$styr, fimsdat$endyr), "-01-01"), each=nages),
-                       dateend = rep(paste0(seq(fimsdat$styr, fimsdat$endyr), "-12-31"), each=nages),
+                       datestart = rep(paste0(seq(rdat$styr, rdat$endyr), "-01-01"), each=nages),
+                       dateend = rep(paste0(seq(rdat$styr, rdat$endyr), "-12-31"), each=nages),
                        value = as.numeric(t(caa)),
                        unit = "",
                        uncertainty = rep(Ncaa, each=nages))
 indexage <- data.frame(
           type = "age",
           name = "survey",
           age = rep(seq(1, nages), nyears),
-          datestart = rep(paste0( seq(fimsdat$styr, fimsdat$endyr), "-01-01" ), each = nages),
-          dateend = rep(paste0( seq(fimsdat$styr, fimsdat$endyr), "-12-31" ), each = nages),
+          datestart = rep(paste0( seq(rdat$styr, rdat$endyr), "-01-01" ), each = nages),
+          dateend = rep(paste0( seq(rdat$styr, rdat$endyr), "-12-31" ), each = nages),
           value = as.numeric(t(paa2)),
           unit = "",
           uncertainty = rep(Npaa2, each = nages)
 )
 ## indexage=indexage2
 ## index=index2
 res <- rbind(res, landings, index, catchage, indexage)
-## rm(landings, index, catchage, indexage)
+return(res)
+}
+fimsdat<-get_amak_data(atka_dat,atka_rep)
 
 
-age_frame <- FIMS::FIMSFrameAge(res)
+age_frame <- FIMS::FIMSFrameAge(fimsdat)
 fishery_catch <- FIMS::m_landings(age_frame)
 fishery_agecomp <- FIMS::m_agecomp(age_frame, "fleet1")
 survey_index <- FIMS::m_index(age_frame, "survey")