recode: apply styler::tidyverse_style()

R/checks.R

@@ -117,7 +117,7 @@ check_attr <- function(object, attr = "type", check = NULL, stop = TRUE) {
 #' are_constant(1:10)
 #'
 #' are_binary(c("A", "B", "A"))
-#' 
+#'
 #' is_even(1:5)
 #' is_odd(1:5)
 #' is_odd(c(0, 1.5, 2.5, NA, Inf, NULL))

R/crossbrand.R

@@ -3,12 +3,12 @@
 #'
 #' Given a list of recreated Robyn models, this function optimizes budget
 #' allocation across MMM with respective constraints by maximizing
-#' incremental revenue/conversions. This method assumes each model is 
-#' independent, that can be compared given its spends were cleanly and 
-#' properly split, they modeled the same metric (revenue or conversion) 
-#' and units (currency or type of conversion), and date granularity. 
-#' Recommended to have same channels granularity across markets 
-#' to simplify results readings and application.
+#' incremental revenue/conversions. This method assumes each model is
+#' independent, that can be compared given its spends were cleanly and
+#' properly split, they modeled the same metric (revenue or conversion)
+#' and units (currency or type of conversion), and date granularity.
+#' For best results, ensure channels have similar granularity across
+#' markets to simplify interpretation and application of the outputs.
 #'
 #' @param budget_constr_low,budget_constr_up Numeric vector. Relative minimum
 #' and maximum budgets to consider based on \code{initial_budgets}.
@@ -28,7 +28,7 @@
 #' files <- c("BrandA.json", "BrandB.json", "BrandC.json", "BrandN.json")
 #' models <- lapply(files, function(x) Robyn::robyn_recreate(x))
 #' names(models) <- gsub("\\.json", "", files)
-#' 
+#'
 #' # Calculate cross-brand optimal allocation
 #' res <- robyn_xmodels(
 #'   models,
@@ -78,7 +78,7 @@ robyn_xmodels <- function(
   }
   start_dates <- extract_dates(start_dates, perfs, "start_date", quiet)
   end_dates <- extract_dates(end_dates, perfs, "end_date", quiet)
-  
+
   # Extract initial budgets for the date range
   if (is.null(initial_budgets)) {
     for (i in seq_along(models)) {
@@ -99,7 +99,7 @@ robyn_xmodels <- function(
   } else {
     if (length(initial_budgets) == 1) initial_budgets <- rep(initial_budgets, length(models))
   }
-  
+
   # Total budget across brands
   total_budget <- sum(initial_budgets)
 
@@ -109,14 +109,13 @@ robyn_xmodels <- function(
   stopifnot(length(models) == length(initial_budgets))
 
   # Function to calculate total incremental sales given a budget distribution
-  calculate_isales <- function(
-      models, budgets, isales = TRUE,
-      start_dates = NULL, end_dates = NULL,
-      budget_constr_low = 0.5,
-      budget_constr_up = 1.5,
-      channel_constr_low = budget_constr_low,
-      channel_constr_up = budget_constr_up,
-      quiet = FALSE, ...) {
+  calculate_isales <- function(models, budgets, isales = TRUE,
+                               start_dates = NULL, end_dates = NULL,
+                               budget_constr_low = 0.5,
+                               budget_constr_up = 1.5,
+                               channel_constr_low = budget_constr_low,
+                               channel_constr_up = budget_constr_up,
+                               quiet = FALSE, ...) {
     try_require("Robyn")
     stopifnot(length(models) == length(budgets))
     bas <- list()
@@ -145,15 +144,14 @@ robyn_xmodels <- function(
   }
 
   # Function to be optimized (minimized)
-  objective_function <- function(
-      budgets, total_budget, models,
-      start_dates = NULL, end_dates = NULL,
-      budget_constr_low = 0.5,
-      budget_constr_up = 1.5,
-      channel_constr_low = budget_constr_low,
-      channel_constr_up = budget_constr_up,
-      cores = 10, quiet = FALSE,
-      ...) {
+  objective_function <- function(budgets, total_budget, models,
+                                 start_dates = NULL, end_dates = NULL,
+                                 budget_constr_low = 0.5,
+                                 budget_constr_up = 1.5,
+                                 channel_constr_low = budget_constr_low,
+                                 channel_constr_up = budget_constr_up,
+                                 cores = 10, quiet = FALSE,
+                                 ...) {
     # Value to minimize: penalty (tends to zero) - incremental total sales (max)
     isales <- calculate_isales(
       models, budgets,

R/crossbrand2.R

@@ -1,15 +1,15 @@
 ####################################################################
 #' Cross-MMM Budget Optimization across Channels (fast)
-#' 
+#'
 #' Given a list of recreated Robyn models, this function optimizes budget
 #' allocation across MMM with respective constraints by maximizing
-#' response across all channels. This method assumes each model is 
-#' independent, that can be compared given its spends were cleanly and 
-#' properly split, they modeled the same metric (revenue or conversion) 
-#' and units (currency or type of conversion), and date granularity. 
-#' Recommended to have same channels granularity across markets 
+#' response across all channels. This method assumes each model is
+#' independent, that can be compared given its spends were cleanly and
+#' properly split, they modeled the same metric (revenue or conversion)
+#' and units (currency or type of conversion), and date granularity.
+#' Recommended to have same channels granularity across markets
 #' to simplify results readings and application.
-#' 
+#'
 #' This approach is faster and cleaner compared with previous proposal
 #' using \code{robyn_xmodels()}.
 #'
@@ -21,12 +21,12 @@
 #' specific model. You can specify a single date and will be used in all models.
 #' Default empty value will assume you want all available data and date range.
 #' Must be length 1 or same as \code{models}.
-#' @param channel_constr_low,channel_constr_up Numeric vector. 
+#' @param channel_constr_low,channel_constr_up Numeric vector.
 #' Relative lower and upper constraints per channel compared with mean
-#' spend during the time period defined. 
+#' spend during the time period defined.
 #' If mean was zero for date range, historical mean spend value will be used.
-#' Must have length 1 to replicate for all channels or same length 
-#' (and order )as \code{paid_media_spends}. 
+#' Must have length 1 to replicate for all channels or same length
+#' (and order )as \code{paid_media_spends}.
 #' @return List. Contains optimized allocation results and plots.
 #' @examples
 #' \dontrun{
@@ -50,7 +50,7 @@ robyn_xchannels <- function(
     ...) {
   try_require("Robyn")
   try_require("nloptr")
-  
+
   # Check all models are same type: metric and interval type
   stopifnot(length(unique(unlist(lapply(models, function(x) x$InputCollect$dep_var_type)))) == 1)
   stopifnot(length(unique(unlist(lapply(models, function(x) x$InputCollect$intervalType)))) == 1)

R/family.R

@@ -1,12 +1,12 @@
 ####################################################################
 #' Surnames Order Sequence
-#' 
-#' Generate a sequence of numbers that determines the order in which 
-#' surnames should be listed based on the number of generations of 
-#' ancestors you wish to include. This sequence follows the traditional 
-#' Latin custom of assigning the father's surname first, followed by 
-#' the mother's surname. The same logic extends systematically to higher 
-#' generations, ensuring that the order of surnames remains consistent 
+#'
+#' Generate a sequence of numbers that determines the order in which
+#' surnames should be listed based on the number of generations of
+#' ancestors you wish to include. This sequence follows the traditional
+#' Latin custom of assigning the father's surname first, followed by
+#' the mother's surname. The same logic extends systematically to higher
+#' generations, ensuring that the order of surnames remains consistent
 #' as you move upward through the family tree.
 #'
 #' @param n Integer. Number of generations to include in the sequence.

R/onehotencoding.R

@@ -471,7 +471,7 @@ holidays <- function(countries = "Venezuela",
       } else {
         c("Date", "Holiday", "Holiday.Type")
       }
-      
+
       # the table might contain comment about interstate holidays like
       # '* Observed only in some communities of this state.
       # Hover your mouse over the region or click on the holiday for details.'
@@ -491,7 +491,7 @@ holidays <- function(countries = "Venezuela",
           )
         }
       )
-      
+
       result <- data.frame(
         holiday = holidays$Date,
         holiday_name = holidays$Holiday,
@@ -520,7 +520,7 @@ holidays <- function(countries = "Venezuela",
     results <- results %>%
       filter(!is.na(.data$holiday)) %>%
       cleanNames() %>%
-      as_tibble() 
-    }
+      as_tibble()
+  }
   return(results)
 }

R/wrangling.R

@@ -393,15 +393,15 @@ v2t <- vector2text
 #' formatNum(c(-3:3), sign = TRUE)
 #' @export
 #' @rdname format_string
-formatNum <- function(x, decimals = 2, signif = NULL, 
+formatNum <- function(x, decimals = 2, signif = NULL,
                       type = Sys.getenv("LARES_NUMFORMAT"),
                       pre = "", pos = "", sign = FALSE,
                       abbr = FALSE,
                       ...) {
   if (is.null(x) || !is.numeric(x)) {
     return(x)
   }
-  
+
   # Auxiliary function to save signs
   if (sign) signs <- ifelse(x > 0, "+", "")
 
@@ -418,7 +418,9 @@ formatNum <- function(x, decimals = 2, signif = NULL,
     x <- unlist(lapply(x, function(y) if (is.na(y)) y else num_abbr(y, n = decimals + 1)))
   } else {
     x <- unlist(lapply(x, function(y) {
-      if (is.na(y)) y else {
+      if (is.na(y)) {
+        y
+      } else {
         if (type == 1) {
           y <- format(as.numeric(y), big.mark = ".", decimal.mark = ",", ...)
         } else {