style and docs: run devtools::document() and styler::style_pkg()

R/create_default_parameters.R

@@ -61,16 +61,15 @@
 #'   )
 #' }
 create_default_parameters <- function(
-  data,
-  fleets,
-  recruitment = list(
-    form = "BevertonHoltRecruitment",
-    process_distribution = c(log_devs = "DnormDistribution")
-  ),
-  # TODO: Rename EWAAgrowth to not use an acronym
-  growth = list(form = "EWAAgrowth"),
-  maturity = list(form = "LogisticMaturity")
-) {
+    data,
+    fleets,
+    recruitment = list(
+      form = "BevertonHoltRecruitment",
+      process_distribution = c(log_devs = "DnormDistribution")
+    ),
+    # TODO: Rename EWAAgrowth to not use an acronym
+    growth = list(form = "EWAAgrowth"),
+    maturity = list(form = "LogisticMaturity")) {
   # FIXME: use default values if there are no fleets info passed into the
   # function or a fleet is not present but it has data? Maybe we don't want the
   # latter because it could be that we want to drop a fleet from a model but we
@@ -256,8 +255,7 @@ create_default_DoubleLogistic <- function() {
 #' of selectivity.
 #' @noRd
 create_default_selectivity <- function(
-  form = c("LogisticSelectivity", "DoubleLogisticSelectivity")
-) {
+    form = c("LogisticSelectivity", "DoubleLogisticSelectivity")) {
   # Input checks
   form <- rlang::arg_match(form)
   # NOTE: All new forms of selectivity must be placed in the vector of default
@@ -442,10 +440,9 @@ create_default_BevertonHoltRecruitment <- function(data) {
 #' A list of default parameters for DnormDistribution.
 #' @noRd
 create_default_DnormDistribution <- function(
-  value = 0.1,
-  data,
-  input_type = c("data", "process")
-) {
+    value = 0.1,
+    data,
+    input_type = c("data", "process")) {
   # Input checks
   input_type <- rlang::arg_match(input_type)
 
@@ -486,10 +483,9 @@ create_default_DnormDistribution <- function(
 #' A list of default parameters for DlnormDistribution.
 #' @noRd
 create_default_DlnormDistribution <- function(
-  value = 0.1,
-  data,
-  input_type = c("data", "process")
-) {
+    value = 0.1,
+    data,
+    input_type = c("data", "process")) {
   # Input checks
   # TODO: Determine if value can be a vector?
   if (!is.numeric(value) || any(value <= 0, na.rm = TRUE)) {
@@ -538,10 +534,9 @@ create_default_DlnormDistribution <- function(
 #' A list with the default parameters for recruitment.
 #' @noRd
 create_default_recruitment <- function(
-  recruitment,
-  data,
-  input_type = "BevertonHoltRecruitment"
-) {
+    recruitment,
+    data,
+    input_type = "BevertonHoltRecruitment") {
   # Input checks
   if (!is.list(recruitment)) {
     cli::cli_abort(c(

R/distribution_formulas.R

@@ -252,13 +252,12 @@ get_expected_name <- function(family, data_type) {
 #' )
 #' }
 initialize_data_distribution <- function(
-  module,
-  family,
-  sd = list(value = 1, estimated = FALSE),
-  # FIXME: Move this argument to second to match where par is in
-  # initialize_process_distribution
-  data_type = c("index", "agecomp", "lengthcomp")
-) {
+    module,
+    family,
+    sd = list(value = 1, estimated = FALSE),
+    # FIXME: Move this argument to second to match where par is in
+    # initialize_process_distribution
+    data_type = c("index", "agecomp", "lengthcomp")) {
   data_type <- rlang::arg_match(data_type)
   # FIXME: Make the available families a data object
   # Could also make the matrix of distributions available per type as a
@@ -345,12 +344,11 @@ initialize_data_distribution <- function(
 #' @keywords distribution
 #' @export
 initialize_process_distribution <- function(
-  module,
-  par,
-  family,
-  sd = list(value = 1, estimated = FALSE),
-  is_random_effect = FALSE
-) {
+    module,
+    par,
+    family,
+    sd = list(value = 1, estimated = FALSE),
+    is_random_effect = FALSE) {
   # validity check on user input
   args <- list(family = family, sd = sd)
   check_distribution_validity(args)

R/fimsfit.R

@@ -337,13 +337,12 @@ is.FIMSFits <- function(x) {
 #' @keywords fit_fims
 #' @export
 FIMSFit <- function(
-  input,
-  obj,
-  opt = list(),
-  sdreport = list(),
-  timing = c("time_total" = as.difftime(0, units = "secs")),
-  version = utils::packageVersion("FIMS")
-) {
+    input,
+    obj,
+    opt = list(),
+    sdreport = list(),
+    timing = c("time_total" = as.difftime(0, units = "secs")),
+    version = utils::packageVersion("FIMS")) {
   # What we aspire the estimate table to look like
   estimates_outline <- dplyr::tibble(
     label = character(),

R/fimsframe.R

@@ -805,12 +805,11 @@ FIMSFrame <- function(data) {
 
 # Unexported functions ----
 create_missing_data <- function(
-  data,
-  bins,
-  years,
-  column,
-  types = c("landings", "index")
-) {
+    data,
+    bins,
+    years,
+    column,
+    types = c("landings", "index")) {
   use_this_data <- data |>
     dplyr::group_by(type, name)
   out_data <- if (missing(bins)) {

R/initialize_modules.R

@@ -206,11 +206,10 @@ initialize_module <- function(parameters, data, module_name) {
 #' The initialized distribution module as an object.
 #' @noRd
 initialize_distribution <- function(
-  module_input,
-  distribution_name,
-  distribution_type = c("data", "process"),
-  linked_ids
-) {
+    module_input,
+    distribution_name,
+    distribution_type = c("data", "process"),
+    linked_ids) {
   # Input checks
   # Check if distribution_name is provided
   if (is.null(distribution_name)) {