Merge branch 'main' into sample_type

pfmc-assessments · May 1, 2024 · 5c5dfe5 · 5c5dfe5
2 parents 8d00fcf + d67fde4
commit 5c5dfe5
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Showing 4 changed files with 40 additions and 40 deletions.
diff --git a/R/Biomass.fn.R b/R/Biomass.fn.R
@@ -35,7 +35,7 @@ Biomass.fn <- function(dir = NULL, dat, strat.vars = c("Depth_m", "Latitude_dd")
   if (is.null(dat$cpue_kg_km2)) stop("There must be a column called cpue_kg_km2 in the dataframe")
 
   # Calculate the CPUE in terms of nubmer
-  dat$cpue_km2_count <- (dat$total_catch_numbers / (0.01 * dat$Area_Swept_ha))
+  dat$cpue_km2_count <- (dat$total_catch_numbers / (0.01 * dat$Area_swept_ha))
 
   row.names(strat.df) <- strat.df[, 1] # put in rownmaes to make easier to index later
   numStrata <- nrow(strat.df)
@@ -81,10 +81,10 @@ Biomass.fn <- function(dir = NULL, dat, strat.vars = c("Depth_m", "Latitude_dd")
     }))
 
     stratStats <- data.frame(
-      name = namesStrat, 
-      area = strat.df[namesStrat, 2], 
+      name = namesStrat,
+      area = strat.df[namesStrat, 2],
       ntows = nobs,
-      meanCatchRate = meanCatchRateInStrata, 
+      meanCatchRate = meanCatchRateInStrata,
       varCatchRate = varCatchRateInStrata
     )
 
@@ -125,10 +125,10 @@ Biomass.fn <- function(dir = NULL, dat, strat.vars = c("Depth_m", "Latitude_dd")
     }))
 
     stratStats <- data.frame(
-      name = namesYear, 
-      area = strat.df[ind, 2], 
+      name = namesYear,
+      area = strat.df[ind, 2],
       ntows = nobs,
-      meanCatchRate = meanCatchRateInStrata, 
+      meanCatchRate = meanCatchRateInStrata,
       varCatchRate = varCatchRateInStrata
     )
 
@@ -149,8 +149,8 @@ Biomass.fn <- function(dir = NULL, dat, strat.vars = c("Depth_m", "Latitude_dd")
 
   yrTotal.fn <- function(x) {
     data.frame(
-      Bhat = sum(x$Bhat), 
-      seBhat = sqrt(sum(x$varBhat)), 
+      Bhat = sum(x$Bhat),
+      seBhat = sqrt(sum(x$varBhat)),
       cv = sqrt(sum(x$varBhat)) / sum(x$Bhat))
   }
 

diff --git a/R/Format.AKSlope.fn.R b/R/Format.AKSlope.fn.R
@@ -1,44 +1,44 @@
 #' Rename columns in the AFSC slope survey data file
-#' received prior to the creation of the NWFSC data 
-#' warehouse. This function converts the older data files 
-#' to create the needed column names to work within survey 
+#' received prior to the creation of the NWFSC data
+#' warehouse. This function converts the older data files
+#' to create the needed column names to work within survey
 #' package functions. Output from this function will be list
 #' of containing catch, length, and age data.
 #'
-#' @template dir 
-#' @param datTows A data frame of catch data for the 
+#' @template dir
+#' @param datTows A data frame of catch data for the
 #' AKFSC slope survey with incorrect column names.
 #' prior to the creation of the data warehouse.
-#' @param datL A list of biological data (lengths and ages) 
-#' for the AKFSC slope survey with incorrect column 
+#' @param datL A list of biological data (lengths and ages)
+#' for the AKFSC slope survey with incorrect column
 #' names prior to the creation of the data warehouse.
-#' @param start.year The first year of data to retain within 
+#' @param start.year The first year of data to retain within
 #' the data frame. The first year typically used from this
-#' survey is 1997.  
+#' survey is 1997.
 #' @template verbose
 #'
 #' @author Chantel Wetzel
 #' @export
-#' 
+#'
 #' @examples
 #' \dontrun{
 #'   # load data files for catch and biological data
 #'    load("Tri.Shelf.and.AFSC.Slope.canary.Catch.24.May.11.dmp")
-#'    catch = Tri.Shelf.and.AFSC.Slope.canary.Catch.24.May.11 
+#'    catch = Tri.Shelf.and.AFSC.Slope.canary.Catch.24.May.11
 #'    load("AFSC.Slope.Shelf.sable.bio.5.24.11.dmp")
 #'    bio = AK.Surveys.Bio.sablefish.24.May.11
 #'    # call function and reformat the data
 #'    filter.dat = Format.AKSlope.fn(
-#'      datTows = catch, 
-#'      datL = bio, 
-#'      start.year = 1997) 
+#'      datTows = catch,
+#'      datL = bio,
+#'      start.year = 1997)
 #'    catch = filter.dat$datTows
 #'    len = filter.dat$length
 #'    age = filter.dat$age
 #'  )
 #' }
 #'
-Format.AKSlope.fn <- function(dir = NULL, datTows, datL = NA, 
+Format.AKSlope.fn <- function(dir = NULL, datTows, datL = NA,
   start.year = 1997, verbose = TRUE) {
 
   check_dir(dir = dir, verbose)
@@ -66,12 +66,12 @@ Format.AKSlope.fn <- function(dir = NULL, datTows, datL = NA,
   datTows$Longitude_dd <- (datTows$START_LONGITUDE + datTows$END_LONGITUDE) / 2
   datTows$total_catch_numbers <- datTows$Subsample_count
   datTows$total_catch_wt_kg <- datTows$Subsample_wt_kg
-  datTows$Area_Swept_ha <- (datTows$DISTANCE_FISHED * datTows$NET_WIDTH) / 10 # area swept for each tow in hectare
-  datTows$cpue_kg_km2 <- datTows$Subsample_wt_kg / (0.01 * datTows$Area_Swept_ha)
+  datTows$Area_swept_ha <- (datTows$DISTANCE_FISHED * datTows$NET_WIDTH) / 10 # area swept for each tow in hectare
+  datTows$cpue_kg_km2 <- datTows$Subsample_wt_kg / (0.01 * datTows$Area_swept_ha)
 
   datTows <- datTows[, c(
     "Project", "Trawl_id", "Year", "Pass", "Vessel", "Tow", "Date", "Depth_m", "Longitude_dd", "Latitude_dd",
-    "Area_Swept_ha", "cpue_kg_km2", "Subsample_count", "Subsample_wt_kg",
+    "Area_swept_ha", "cpue_kg_km2", "Subsample_count", "Subsample_wt_kg",
     "total_catch_numbers", "total_catch_wt_kg"
   )]
 

diff --git a/R/SurveyAgeAtLen.fn.R b/R/SurveyAgeAtLen.fn.R
@@ -65,7 +65,7 @@ SurveyAgeAtLen.fn <- function(dir = NULL, datAL, datTows, strat.vars = c("Depth_
   Area_Swept_km2 <- Total_fish_number <- Sub_fish_number <- numeric(dim(datB)[1])
   for (i in 1:length(tows)) {
     find <- which(tows[i] == datTows$Trawl_id)
-    area <- datTows$Area_Swept_ha[find] * 0.01 # km2
+    area <- datTows$Area_swept_ha[find] * 0.01 # km2
     tot.num <- datTows$total_catch_numbers[find]
     sub.num <- datTows$Subsample_count[find]
 
@@ -140,7 +140,7 @@ SurveyAgeAtLen.fn <- function(dir = NULL, datAL, datTows, strat.vars = c("Depth_
     datB[is.na(datB$numF), "numF"] <- 0
   }
 
-  if ("M" %in% sexes_present){  
+  if ("M" %in% sexes_present){
     temp <- TdatL.al[["M"]][, c("Trawl_id", "allLs", "allAs", "num")]
     names(temp) <- c("Trawl_id", "allLs", "allAs", "numM")
     datB <- merge(datB, temp, by = c("Trawl_id", "allLs", "allAs"), all = T)
@@ -282,7 +282,7 @@ SurveyAgeAtLen.fn <- function(dir = NULL, datAL, datTows, strat.vars = c("Depth_
         sum(x$numAll)
       }))
       x <- data.frame(x[rep(1, length(AjhAll)), xcols], area = A.h, AGE = as.numeric(names(AjhAll)), AjhAll = AjhAll, TotalAjhAll = AjhAll)
-      
+
       if ("U" %in% sexes_present){
       AjhU <- unlist(lapply(ages, function(x) {
         sum(x$numU)
@@ -302,7 +302,7 @@ SurveyAgeAtLen.fn <- function(dir = NULL, datAL, datTows, strat.vars = c("Depth_
         sum(x$numM)
       }))
       x <- data.frame(x, AjhM = AjhM, TotalAjhM = AjhM)
-      } 
+      }
 
     } else {
       AjhAll <- unlist(lapply(ages, function(x) {
@@ -314,12 +314,12 @@ SurveyAgeAtLen.fn <- function(dir = NULL, datAL, datTows, strat.vars = c("Depth_
         sum(x$expU / x$areaFished)
       }))
       x <- data.frame(x, AjhU = AjhU / ntows, TotalAjhU = A.h * AjhU / ntows)
-      
+
       AjhF <- unlist(lapply(ages, function(x) {
         sum(x$expF / x$areaFished)
       }))
       x <- data.frame(x, AjhF = AjhF / ntows, TotalAjhF = A.h * AjhF / ntows)
-      
+
       AjhM <- unlist(lapply(ages, function(x) {
         sum(x$expM / x$areaFished)
       }))

diff --git a/R/SurveyLFs.fn.R b/R/SurveyLFs.fn.R
@@ -73,7 +73,7 @@ SurveyLFs.fn <- function(dir = NULL, datL, datTows, strat.vars = c("Depth_m", "L
   missing <- sum(postows[find, "total_catch_numbers"])
   percent <- 100 * round(missing / sum(datTows[, "total_catch_numbers"]), 3)
   if (verbose) {
-    cat("\nThere are", x, "tows where fish were observed but no lengths/ages taken. 
+    cat("\nThere are", x, "tows where fish were observed but no lengths/ages taken.
         These tows contain", missing, "lengths/ages that comprise", percent, "percent of total sampled fish.\n")
   }
 
@@ -92,7 +92,7 @@ SurveyLFs.fn <- function(dir = NULL, datL, datTows, strat.vars = c("Depth_m", "L
   Area_Swept <- Total_fish_number <- Sub_fish_number <- Sexed_fish <- numeric(dim(datB)[1])
   for (i in 1:length(tows)) {
     find <- which(tows[i] == datTows$Trawl_id)
-    area <- datTows$Area_Swept_ha[find] * 0.01 #km2 
+    area <- datTows$Area_swept_ha[find] * 0.01 #km2
     #Alternative: * 10000 square meter
     tot.num <- datTows$total_catch_numbers[find]
     sub.num <- datTows$Subsample_count[find]
@@ -154,13 +154,13 @@ SurveyLFs.fn <- function(dir = NULL, datL, datTows, strat.vars = c("Depth_m", "L
   TdatL.tows <- TdatL.tows[TdatL.tows$Var2 == "TRUE", ]
   if(dim(TdatL.tows)[1] > 0) {
     datB <- data.frame(
-      datB[match(as.character(TdatL.tows$Var1), 
-      as.character(datB$Trawl_id)), ], 
+      datB[match(as.character(TdatL.tows$Var1),
+      as.character(datB$Trawl_id)), ],
       TowExpFactorMF = TdatL.tows$Freq)
     # Find the numerator looking where the number of fish = sexed fish when all fish are sampled (e.g., sexed and unsexed in a fully sampled tow)
     # The previous approach expanded sexed fish relative to the full sample size resulting in expansions when there should not have been
-    datB <- data.frame(datB[match(as.character(TdatL.tows$Var1), 
-      as.character(datB$Trawl_id)), ], 
+    datB <- data.frame(datB[match(as.character(TdatL.tows$Var1),
+      as.character(datB$Trawl_id)), ],
       true_sub_MFfish = TdatL.tows$Freq)
   }
   if (is.null(datB$true_sub_MFfish)) {
@@ -584,7 +584,7 @@ SurveyLFs.fn <- function(dir = NULL, datL, datTows, strat.vars = c("Depth_m", "L
 
   if (verbose && !is.null(dir)) {
     cat("\nNOTE: Files have been saved the the printfolder directory.
-        The first file has the 999 column showing fish smaller or younger than the initial bin. 
+        The first file has the 999 column showing fish smaller or younger than the initial bin.
         Check to make sure there is not a large number of fish smaller or younger than the initial bin.
         The second file has combined the 999 with the first bin and is ready for use in SS.\n")
   }