Fix codebase from variety of issues

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: stockplotr
 Title: Tables and Figures for Stock Assessments
-Version: 0.7.0
+Version: 0.9.0
 Authors@R: c(
     person("Samantha", "Schiano", , "samantha.schiano@noaa.gov", role = c("aut", "cre"),
            comment = c(ORCID = "0009-0003-3744-6428")),
@@ -48,6 +48,7 @@ Imports:
     prodlim,
     quarto,
     scales,
+    stats,
     stringr,
     tibble,
     tidyr,

R/convert_output.R

@@ -4,7 +4,7 @@
 #'
 #' @param file Assessment model output file path
 #' @param model Assessment model used in evaluation ("ss3", "bam",
-#'  "asap", "fims", "amak", "ms-java", "wham", "mas").
+#'  "fims").
 #' @param fleet_names Names of fleets in the assessment model as
 #'  shortened in the output file. If fleet names are not properly read, then
 #'  indicate the fleets names as an acronym in a vector
@@ -1745,8 +1745,9 @@ convert_output <- function(
     #### JABBA ####
   } else if (tolower(model) == "jabba") {
     cli::cli_abort("JABBA output not currently compatible.")
+    #### FIMS ####
   } else if (model == "fims") {
-    if (grepl(".RDS", file)) {
+    if (is.character(file) && length(file) == 1) {
       fims_output <- readRDS(file)
     } else {
       fims_output <- file
@@ -1761,7 +1762,7 @@ convert_output <- function(
     cli::cli_abort(c(
       message = "Output file not compatible.",
       "i" = "`model` entered as {model}.",
-      "i" = "Accepted `model` options: SS3, BAM, WHAM, AMAK, JABBA."
+      "i" = "Accepted `model` options: ss3, bam, or fims."
     ))
   }
 

R/plot_natural_mortality.R

@@ -64,7 +64,12 @@ plot_natural_mortality <- function(
     facet = c(group, facet)
   )
 
-  processed_data <- processing[[1]]
+  processed_data <- processing[[1]] 
+  if (is.null(group)) {
+    processed_data <- processed_data |>
+      dplyr::mutate(group_var = "1") # set group var without anything since we are using group as age
+  }
+
   if (!is.null(processing[[3]])) facet <- processing[[3]]
   # make sure group is the one input by user
   if (!is.null(group)) {

R/plot_spawning_biomass.R

@@ -4,7 +4,7 @@
 #' also be made relative to this reference line rather than in absolute units.
 #'
 #' @param dat A data frame or names list of data frames (input as `list()`)
-#' returned from \link[asar]{convert_output}. The first data frame in the list
+#' returned from \link[stockplotr]{convert_output}. The first data frame in the list
 #' is used in calculation of a reference line if one is present
 #' @param geom A string stating the geom used for the plot. Default is "line".
 #' Options include "line", "point", or "area"
@@ -117,7 +117,7 @@ plot_spawning_biomass <- function(
   # Filter data for spawning biomass
   prepared_data <- filter_data(
     dat = dat,
-    label_name = "spawning_biomass$",
+    label_name = "^spawning_biomass$",
     geom = geom,
     era = era,
     group = group,
@@ -166,7 +166,8 @@ plot_spawning_biomass <- function(
     geom = geom,
     ylab = spawning_biomass_label,
     group = group,
-    facet = facet,
+    # add check in case facet is returned as character(0)
+    facet = if (length(facet) > 0) facet else NULL,
     ...
   )
   # Add reference line

R/process_data.R

@@ -241,21 +241,27 @@ process_data <- function(
     # check if value varies in ANY year
     # pivot data for 1st indexed data and check if all the same
     if (length(index_variables) > 0) {
-      pivot_data <- data |>
-        dplyr::select(tidyselect::any_of(c("year", "age", "estimate", index_variables))) |>
-        tidyr::pivot_wider(
-          id_cols = c(year),
-          names_from = tidyselect::any_of(index_variables),
-          values_from = estimate
-        ) |>
-        suppressWarnings()
-      column_data <- pivot_data[-1]
+      # if (index_variables == "age" | index_variables == "year") {
+      #   # if age or year is the only other index variable, then get data so there is a single column as expected in column_data
+      #   pivot_data <- data
+      #   column_data <- pivot_data[["estimate"]]
+      # } else {
+        pivot_data <- data |>
+          dplyr::select(tidyselect::any_of(c("year", "age", "estimate", index_variables))) |>
+          tidyr::pivot_wider(
+            id_cols = c(year),
+            names_from = tidyselect::any_of(index_variables),
+            values_from = estimate
+          ) |>
+          suppressWarnings()
+        column_data <- pivot_data[-1]
+      # }
     } else {
       # Look at group_var and identify if there is a needed grouping or can just plot one year
       pivot_data <- data |>
         dplyr::select(tidyselect::any_of(c("year", "age", "estimate", "group_var"))) |>
         tidyr::pivot_wider(
-          id_cols = c(year),
+          id_cols = if ("year" %in% colnames(data)) "year" else NULL,
           names_from = group_var,
           values_from = estimate
         ) |>
@@ -352,7 +358,7 @@ process_table <- function(
     mod_data <- dplyr::filter(dat, model == mod)
     mod_index <- check_grouping(mod_data)
     mod_names <- rep(mod, length(mod_index))
-    mod_index <- setNames(mod_index, mod_names)
+    mod_index <- stats::setNames(mod_index, mod_names)
     index_variables <- c(index_variables, mod_index)
   }
 
@@ -409,7 +415,7 @@ process_table <- function(
           mod_data <- dplyr::filter(dat, model == mod)
           mod_index <- check_grouping(mod_data)
           mod_names <- rep(mod, length(mod_index))
-          mod_index <- setNames(mod_index, mod_names)
+          mod_index <- stats::setNames(mod_index, mod_names)
           index_variables <- c(index_variables, mod_index)
         }
 
@@ -495,7 +501,7 @@ process_table <- function(
     table_list[[mod]] <- table_data
 
     # This feels like backward progress
-    id_group_list[[mod]] <- lapply(setNames(mod_id_group, mod_id_group), function(x) {
+    id_group_list[[mod]] <- lapply(stats::setNames(mod_id_group, mod_id_group), function(x) {
       unique(mod_dat[[x]])
     })
   } # close loop

R/stockplotr-package.R

@@ -14,6 +14,9 @@ globvar <- c(
   "type", "uncertainty", "uncertainty_label", "val", "where", "year",
   ":=", "Year", "avg", "estimate_orig", "interm", "season", "tables_dir", "time", "total_fish",
   "years_per_year", ".data", "cohort", "era", "expected_recruitment", "group_var", "model",
-  "plot_data", "quantile", "rda_dir", "reorder", "total_estimate", "zvar", "filter_data"
+  "plot_data", "quantile", "rda_dir", "reorder", "total_estimate", "zvar", "filter_data",
+  "Component", "age_bins", "alt_label", "final_df", "init", "keyword", "len_bins",
+  "like", "match_key", "morph", "nsim", "output", "output_order", "parm_stdev", "seas",
+  "sexes", "subseas", "unique_count", "value", "yr"
 )
 if (getRversion() >= "2.15.1") utils::globalVariables(globvar)

R/utils_plot.R

@@ -183,7 +183,7 @@ plot_timeseries <- function(
   }
 
   # Check if facet(s) are desired
-  if (!is.null(facet)) {
+  if (!is.null(facet) & length(facet) > 0) {
     facet <- paste("~", paste(facet, collapse = " + "))
     facet_formula <- stats::reformulate(facet)
 

R/utils_table.R

@@ -305,7 +305,7 @@ merge_error <- function(table_data, uncert_lab, fleets, label, unit_label) {
 
       # Rename final df with cleaned names
       tab_dat <- tab_dat |>
-        dplyr::rename(any_of(rename_map_final)) |>
+        dplyr::rename(dplyr::any_of(rename_map_final)) |>
         dplyr::rename_with(~ gsub("_", " - ", .)) # |>
       # not sure if we want to keep this or not
       # dplyr::select(where(~!all(is.na(.)) | !all(. == "-"))) # remove columns that are all NA or all "-"))

data-raw/DATASET.R

@@ -2,8 +2,8 @@
 # Path to SS3 output file
 EX_REPORT_PATH <- file.path("inst", "extdata", "Report.sso")
 # Install asar
-devtools::install_github("nmfs-ost/asar")
+devtools::install_github("nmfs-ost/stockplotr")
 # Convert output
-example_data <- asar::convert_output(EX_REPORT_PATH)
+example_data <- stockplotr::convert_output(EX_REPORT_PATH)
 # Save object as rda into raw_data
 usethis::use_data(example_data, overwrite = TRUE)