edits from Test df to array

NEWS.md

@@ -1,5 +1,7 @@
 # serocalculator (development version)
 
+* created unit test for `df_to_array()`
+* fixed `dplyr::select()` deprecation warning in `df_to_array()`
 * Generalized `get_()` methods from `pop_data`-specific to `default`.
 
 # serocalculator 1.2.0

R/df_to_array.R

@@ -8,7 +8,7 @@
 #'
 #' @keywords internal
 #'
-df.to.array <- function(
+df.to.array <- function( # nolint: object_name_linter
     df,
     dim_var_names,
     value_var_name = "value") {
@@ -18,10 +18,14 @@ df.to.array <- function(
 
 #' Convert a data.frame (or tibble) into a multidimensional array
 #'
-#' @param df a [data.frame()] (or [tibble::tibble()]) in long format (each row contains one value for the intended array)
-#' @param dim_var_names a [character()] vector of variable names in `df`. All of these variables should be factors, or a warning will be produced.
-#' @param value_var_name a [character()] variable containing a variable name from `df` which contains the values for the intended array.
-#' @return an [array()] with dimensions defined by the variables in `df` listed in `dim_var_names`
+#' @param df a [data.frame()] (or [tibble::tibble()]) in long format
+#' (each row contains one value for the intended array)
+#' @param dim_var_names a [character()] vector of variable names in `df`.
+#' All of these variables should be factors, or a warning will be produced.
+#' @param value_var_name a [character()] variable containing a variable name
+#' from `df` which contains the values for the intended array.
+#' @return an [array()] with dimensions defined by the variables in `df`
+#' listed in `dim_var_names`
 #'
 #' @examples
 #' library(dplyr)
@@ -33,7 +37,9 @@ df.to.array <- function(
 #'     cols = c("Sepal.Length", "Sepal.Width", "Petal.Width", "Petal.Length")
 #'   ) %>%
 #'   mutate(parameter = factor(parameter, levels = unique(parameter)))
-#' arr <- df %>% serocalculator:::df_to_array(dim_var_names = c("parameter", "Species"))
+#' arr <- df %>%
+#'   serocalculator:::df_to_array(
+#'      dim_var_names = c("parameter", "Species"))
 #' ftable(arr[,,1:5])
 #' @noRd
 df_to_array <- function(
@@ -77,6 +83,6 @@ df_to_array <- function(
     )
 
   df %>%
-    mutate(.by = all_of(dim_var_names), obs = 1:n()) %>%
+    mutate(.by = all_of(dim_var_names), obs = row_number()) %>%
     xtabs(formula = formula(xtabs_formula))
 }

tests/testthat/test-df_to_array.R

@@ -4,9 +4,15 @@ test_that("df_to_array() produces consistent results", {
   df <- iris %>%
     tidyr::pivot_longer(
       names_to = "parameter",
-      cols = c("Sepal.Length", "Sepal.Width", "Petal.Width", "Petal.Length")
+      cols = c(
+        "Sepal.Length",
+        "Sepal.Width",
+        "Petal.Width",
+        "Petal.Length"
+      )
     ) %>%
     mutate(parameter = factor(parameter, levels = unique(parameter)))
-  arr <- df %>% serocalculator:::df_to_array(dim_var_names = c("parameter", "Species"))
+  arr <- df %>%
+    serocalculator:::df_to_array(dim_var_names = c("parameter", "Species"))
   arr %>% expect_snapshot_value(style = "serialize")
 })