r4ss colname change: Gender to sex

nmfs-fish-tools · Aug 5, 2024 · 1dfb163 · 1dfb163
1 parent 2389804
commit 1dfb163
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Showing 7 changed files with 33 additions and 33 deletions.
diff --git a/R/initOM.R b/R/initOM.R
@@ -540,7 +540,7 @@ rm_sample_struct_hist <- function(sample_struct_hist, dat) {
     compare_obj = sample_struct_hist,
     name_in_obj = "lencomp",
     colnames = c(
-      "Yr", "Seas", "FltSvy", "Gender",
+      "Yr", "Seas", "FltSvy", "sex",
       "Part"
     )
   )
@@ -549,7 +549,7 @@ rm_sample_struct_hist <- function(sample_struct_hist, dat) {
     compare_obj = sample_struct_hist,
     name_in_obj = "agecomp",
     colnames = c(
-      "Yr", "Seas", "FltSvy", "Gender",
+      "Yr", "Seas", "FltSvy", "sex",
       "Part", "Ageerr", "Lbin_lo",
       "Lbin_hi"
     )
@@ -564,7 +564,7 @@ rm_sample_struct_hist <- function(sample_struct_hist, dat) {
     return_obj = dat,
     compare_obj = sample_struct_hist,
     name_in_obj = "MeanSize_at_Age_obs",
-    colnames = c("Yr", "Seas", "FltSvy", "Gender", "Part", "AgeErr", "N_")
+    colnames = c("Yr", "Seas", "FltSvy", "sex", "Part", "AgeErr", "N_")
   )
   dat
 }

diff --git a/R/manipulate_EM.R b/R/manipulate_EM.R
@@ -78,7 +78,7 @@ get_EM_dat <- function(OM_dat, EM_dat, do_checks = TRUE) {
     lcomps <- lapply(dat, function(x) {
       tmp <- combine_cols(
         x, "lencomp",
-        c("Yr", "Seas", "FltSvy", "Gender", "Part")
+        c("Yr", "Seas", "FltSvy", "sex", "Part")
       )
     })
     matches_l <- which(lcomps[[1]][, "combo"] %in% lcomps[[2]][, "combo"])
@@ -89,7 +89,7 @@ get_EM_dat <- function(OM_dat, EM_dat, do_checks = TRUE) {
     acomps <- lapply(dat, function(x) {
       tmp <- combine_cols(
         x, "agecomp",
-        c("Yr", "Seas", "FltSvy", "Gender", "Part", "Lbin_lo", "Lbin_hi")
+        c("Yr", "Seas", "FltSvy", "sex", "Part", "Lbin_lo", "Lbin_hi")
       )
     })
     matches_a <- which(acomps[[1]][, "combo"] %in% acomps[[2]][, "combo"])
@@ -111,7 +111,7 @@ get_EM_dat <- function(OM_dat, EM_dat, do_checks = TRUE) {
     size_at_age <- lapply(dat, function(x) {
       tmp <- combine_cols(
         x, "MeanSize_at_Age_obs",
-        c("Yr", "Seas", "FltSvy", "Gender", "Part", "Ageerr")
+        c("Yr", "Seas", "FltSvy", "sex", "Part", "Ageerr")
       )
     })
     matches_size_at_age <- which(size_at_age[[1]][, "combo"] %in% size_at_age[[2]][, "combo"])
@@ -231,14 +231,14 @@ add_new_dat <- function(OM_dat,
         by_val <- switch(df_name,
           "catch" = c("year", "seas", "fleet"),
           "CPUE" = c("year", "seas", "index"),
-          "lencomp" = c("Yr", "Seas", "FltSvy", "Gender", "Part"),
+          "lencomp" = c("Yr", "Seas", "FltSvy", "sex", "Part"),
           "agecomp" = c(
-            "Yr", "Seas", "FltSvy", "Gender", "Part", "Ageerr",
+            "Yr", "Seas", "FltSvy", "sex", "Part", "Ageerr",
             "Lbin_lo", "Lbin_hi"
           ),
           "meanbodywt" = c("Year", "Seas", "Fleet", "Partition", "Type"),
           "MeanSize_at_Age_obs" = c(
-            "Yr", "Seas", "FltSvy", "Gender", "Part",
+            "Yr", "Seas", "FltSvy", "sex", "Part",
             "AgeErr"
           )
         )

diff --git a/R/red_noise_funcs.R b/R/red_noise_funcs.R
@@ -36,9 +36,9 @@ calc_comp_var <- function(data_obs, data_exp, bins, fleets = NULL, years = NULL,
 
   # Check if select genders are specified if not select all genders in the input composition data frame
   if (!is.null(genders)) {
-    genders <- genders[is.element(genders, unique(data_obs[["Gender"]]))]
+    genders <- genders[is.element(genders, unique(data_obs[["sex"]]))]
   } else {
-    genders <- unique(data_obs[["Gender"]])
+    genders <- unique(data_obs[["sex"]])
   }
 
   # Check if select fleets are specified if not select all fleets in the input composition data frame
@@ -50,8 +50,8 @@ calc_comp_var <- function(data_obs, data_exp, bins, fleets = NULL, years = NULL,
 
   # Subset the input observed and selected data to retain only the year, season, gender, and fleet
   # elements specified above
-  data_obs <- data_obs[is.element(data_obs[["Yr"]], years) & is.element(data_obs[["FltSvy"]], fleets) & is.element(data_obs[["Seas"]], seasons) & is.element(data_obs[["Gender"]], genders) & data_obs[["Yr"]] > 0, ]
-  data_exp <- data_exp[is.element(data_exp[["Yr"]], years) & is.element(data_exp[["FltSvy"]], fleets) & is.element(data_exp[["Seas"]], seasons) & is.element(data_exp[["Gender"]], genders) & data_exp[["Yr"]] > 0, ]
+  data_obs <- data_obs[is.element(data_obs[["Yr"]], years) & is.element(data_obs[["FltSvy"]], fleets) & is.element(data_obs[["Seas"]], seasons) & is.element(data_obs[["sex"]], genders) & data_obs[["Yr"]] > 0, ]
+  data_exp <- data_exp[is.element(data_exp[["Yr"]], years) & is.element(data_exp[["FltSvy"]], fleets) & is.element(data_exp[["Seas"]], seasons) & is.element(data_exp[["sex"]], genders) & data_exp[["Yr"]] > 0, ]
 
   # If merge fleets was set as true change all fleets to 0 so that data will be aggregated across them all
   if (merge_fleets == TRUE) {
@@ -63,8 +63,8 @@ calc_comp_var <- function(data_obs, data_exp, bins, fleets = NULL, years = NULL,
   # If merge genders was set as true change all genders to 0 so that data will be aggregated across them all
   if (merge_genders == TRUE) {
     genders <- 0
-    data_obs[["Gender"]] <- 0
-    data_exp[["Gender"]] <- 0
+    data_obs[["sex"]] <- 0
+    data_exp[["sex"]] <- 0
   }
 
   # If merge seasons was set as true change all seasons to 0 so that data will be aggregated across them all
@@ -90,8 +90,8 @@ calc_comp_var <- function(data_obs, data_exp, bins, fleets = NULL, years = NULL,
       for (l in 1:length(seasons)) {
         Comp_uncert[[2]][[i]][[j]][[l]] <- list()
         # For each fleet, gender, and season combination subset the data for analysis
-        sub_dat_obs <- data_obs[data_obs[["FltSvy"]] == fleets[i] & data_obs[["Gender"]] == genders[j] & data_obs[["Seas"]] == seasons[l], ((length(data_obs[1, ]) - length(bins) + 1):length(data_obs[1, ]))]
-        sub_dat_exp <- data_exp[data_exp[["FltSvy"]] == fleets[i] & data_exp[["Gender"]] == genders[j] & data_obs[["Seas"]] == seasons[l], ((length(data_exp[1, ]) - length(bins) + 1):length(data_exp[1, ]))]
+        sub_dat_obs <- data_obs[data_obs[["FltSvy"]] == fleets[i] & data_obs[["sex"]] == genders[j] & data_obs[["Seas"]] == seasons[l], ((length(data_obs[1, ]) - length(bins) + 1):length(data_obs[1, ]))]
+        sub_dat_exp <- data_exp[data_exp[["FltSvy"]] == fleets[i] & data_exp[["sex"]] == genders[j] & data_obs[["Seas"]] == seasons[l], ((length(data_exp[1, ]) - length(bins) + 1):length(data_exp[1, ]))]
 
         # Calculate the total observed and expected samples to allow scaling and unlisting of matrix data
         total_obs <- apply(sub_dat_obs, 1, sum)
@@ -227,9 +227,9 @@ Sim_comp <- function(Comp_uncert, data_exp, bins, years = NULL, seasons = NULL,
   }
 
   if (!is.null(genders)) {
-    genders <- genders[is.element(genders, unique(data_exp[["Gender"]]))]
+    genders <- genders[is.element(genders, unique(data_exp[["sex"]]))]
   } else {
-    genders <- unique(data_exp[["Gender"]])
+    genders <- unique(data_exp[["sex"]])
   }
 
   if (!is.null(fleets)) {
@@ -240,7 +240,7 @@ Sim_comp <- function(Comp_uncert, data_exp, bins, years = NULL, seasons = NULL,
 
   # Subset the expected data to only include the selected fleet, year, season, gender range and the replicate this as the
   # observed data object to be filled with new random observations
-  data_exp <- data_exp[is.element(data_exp[["Yr"]], years) & is.element(data_exp[["FltSvy"]], fleets) & is.element(data_exp[["Seas"]], seasons) & is.element(data_exp[["Gender"]], genders) & data_exp[["Yr"]] > 0, ]
+  data_exp <- data_exp[is.element(data_exp[["Yr"]], years) & is.element(data_exp[["FltSvy"]], fleets) & is.element(data_exp[["Seas"]], seasons) & is.element(data_exp[["sex"]], genders) & data_exp[["Yr"]] > 0, ]
   data_obs <- data_exp
 
   # offset assumes that the observed composition bins are represented buy the final columns of the data frame
@@ -252,7 +252,7 @@ Sim_comp <- function(Comp_uncert, data_exp, bins, years = NULL, seasons = NULL,
     # For each of fleet, season, and gender select the corresponding reference link to the uncertainty list object
     fleet_ref <- which(Comp_uncert[[1]][[1]] == data_obs[["FltSvy"]][i])
     season_ref <- which(Comp_uncert[[1]][[2]] == data_obs[["Seas"]][i])
-    gender_ref <- which(Comp_uncert[[1]][[3]] == data_obs[["Gender"]][i])
+    gender_ref <- which(Comp_uncert[[1]][[3]] == data_obs[["sex"]][i])
     # Extract the variance and bias information for the referenced fleet, gender, season
     sub_var <- Comp_uncert[[2]][[fleet_ref]][[gender_ref]][[season_ref]][[2]]
     sub_bias <- Comp_uncert[[2]][[fleet_ref]][[gender_ref]][[season_ref]][[3]]

diff --git a/R/sample_struct.R b/R/sample_struct.R
@@ -24,7 +24,7 @@ convert_to_r4ss_names <- function(sample_struct,
                                       # currently SSMSE only allows repeating the same sample sizes.
                                       "year", "month", "fleet", "sex", "part", "ageerr", "N_"
                                       # Tags releases
-                                      # "Area", "Yr", "Season", "Gender", "Age", "Nrelease",
+                                      # "Area", "Yr", "Season", "sex", "Age", "Nrelease",
                                       # Morph comp
                                     ),
                                     sample_struct_name = c(
@@ -191,7 +191,7 @@ create_sample_struct <- function(dat, nyrs, rm_NAs = FALSE) {
         }
         if (name %in% c("lencomp", "agecomp", "MeanSize_at_Age_obs")) {
           # Sex
-          sex_col <- grep("Sex|Gender", colnames(df),
+          sex_col <- grep("Sex|sex", colnames(df),
             ignore.case = TRUE,
             value = TRUE
           )
@@ -417,7 +417,7 @@ get_full_sample_struct <- function(sample_struct,
           )
           x[["Sex"]] <- NA
           for (i in unique(x[["FltSvy"]])) {
-            tmp_sx <- unique(tmp_dat[tmp_dat[[flt_colname]] == i, "Gender"])
+            tmp_sx <- unique(tmp_dat[tmp_dat[[flt_colname]] == i, "sex"])
             if (length(tmp_sx) == 1) {
               x[x[["FltSvy"]] == i, "Sex"] <- tmp_sx
             } else {

diff --git a/tests/testthat/test-extendOM.R b/tests/testthat/test-extendOM.R
@@ -40,12 +40,12 @@ extend_vals <- list(
   ),
   lencomp = data.frame(
     Yr = 101:103, Seas = 1, FltSvy = 1,
-    Gender = 0, Part = 0,
+    sex = 0, Part = 0,
     Nsamp = c(25, 50, 100)
   ),
   agecomp = data.frame(
     Yr = 101:104, Seas = 1, FltSvy = 2,
-    Gender = 0, Part = 0, Ageerr = 1,
+    sex = 0, Part = 0, Ageerr = 1,
     Lbin_lo = -1, Lbin_hi = -1,
     Nsamp = c(25, 50, 100, 150)
   )

diff --git a/tests/testthat/test-initOM.R b/tests/testthat/test-initOM.R
@@ -42,13 +42,13 @@ test_that("create_OM can modify model", {
     new_dat[["CPUE"]][, c("year", "seas", "index")],
     unique(new_dat[["CPUE"]][, c("year", "seas", "index")])
   )
-  cols_lencomp <- c("Yr", "Seas", "FltSvy", "Gender", "Part")
+  cols_lencomp <- c("Yr", "Seas", "FltSvy", "sex", "Part")
   expect_equal(
     new_dat[["lencomp"]][, cols_lencomp],
     unique(new_dat[["lencomp"]][, cols_lencomp])
   )
   cols_agecomp <- c(
-    "Yr", "Seas", "FltSvy", "Gender", "Part", "Ageerr", "Lbin_lo",
+    "Yr", "Seas", "FltSvy", "sex", "Part", "Ageerr", "Lbin_lo",
     "Lbin_hi"
   )
   expect_equal(

diff --git a/tests/testthat/test-sample_struct.R b/tests/testthat/test-sample_struct.R
@@ -25,11 +25,11 @@ test_that("assumptions about r4ss colnames are true.", {
     CPUE = data.frame(year = c(102, 105), seas = 7, index = 2, se_log = 0.2),
     lencomp = data.frame(
       Yr = c(102, 105), Seas = 1, FltSvy = 1,
-      Gender = 0, Part = 0, Nsamp = 125
+      sex = 0, Part = 0, Nsamp = 125
     ),
     agecomp = data.frame(
       Yr = c(102, 105), Seas = 1, FltSvy = 2,
-      Gender = 0, Part = 0, Ageerr = 1,
+      sex = 0, Part = 0, Ageerr = 1,
       Lbin_lo = -1, Lbin_hi = -1, Nsamp = 500
     ),
     meanbodywt = data.frame(
@@ -44,7 +44,7 @@ test_that("assumptions about r4ss colnames are true.", {
       Yr = c(1971, 1995),
       Seas = 7,
       FltSvy = c(1, 1, 2, 2),
-      Gender = 3,
+      sex = 3,
       Part = 0,
       AgeErr = 1
     )
@@ -73,11 +73,11 @@ test_that("convert_to_r4ss_names works", {
   expect_equal(names(r4ss_sample_struct[["CPUE"]]), c("year", "seas", "index", "se_log"))
   expect_equal(names(r4ss_sample_struct[["lencomp"]]), c(
     "Yr", "Seas", "FltSvy",
-    "Gender", "Part", "Nsamp"
+    "sex", "Part", "Nsamp"
   ))
   expect_equal(names(r4ss_sample_struct[["agecomp"]]), c(
     "Yr", "Seas", "FltSvy",
-    "Gender", "Part", "Ageerr",
+    "sex", "Part", "Ageerr",
     "Lbin_lo", "Lbin_hi", "Nsamp"
   ))
 })