0063 Move examples for internal functions to unit tests

NAMESPACE

@@ -17,7 +17,6 @@ export(derive_blfl)
 export(derive_seq)
 export(derive_study_day)
 export(domain_example)
-export(dtc_timepart)
 export(fmt_cmp)
 export(generate_oak_id_vars)
 export(hardcode_ct)

R/cnd_df.R

@@ -48,10 +48,6 @@
 #' @seealso [is_cnd_df()], [get_cnd_df_cnd()], [get_cnd_df_cnd_sum()],
 #'   [rm_cnd_df()].
 #'
-#' @examples
-#' df <- data.frame(x = 1:3, y = letters[1:3])
-#' sdtm.oak:::new_cnd_df(dat = df, cnd = c(FALSE, NA, TRUE))
-#'
 #' @keywords internal
 new_cnd_df <- function(dat, cnd, .warn = TRUE) {
   admiraldev::assert_data_frame(dat)
@@ -98,13 +94,6 @@ new_cnd_df <- function(dat, cnd, .warn = TRUE) {
 #' @seealso [new_cnd_df()], [get_cnd_df_cnd()], [get_cnd_df_cnd_sum()],
 #'   [rm_cnd_df()].
 #'
-#' @examples
-#' df <- data.frame(x = 1:3, y = letters[1:3])
-#' sdtm.oak:::is_cnd_df(df)
-#'
-#' cnd_df <- sdtm.oak:::new_cnd_df(dat = df, cnd = c(FALSE, NA, TRUE))
-#' sdtm.oak:::is_cnd_df(cnd_df)
-#'
 #' @keywords internal
 is_cnd_df <- function(dat) {
   inherits(dat, "cnd_df")
@@ -123,13 +112,6 @@ is_cnd_df <- function(dat) {
 #' @seealso [new_cnd_df()], [is_cnd_df()], [get_cnd_df_cnd_sum()],
 #'   [rm_cnd_df()].
 #'
-#' @examples
-#' df <- data.frame(x = 1:3, y = letters[1:3])
-#' sdtm.oak:::get_cnd_df_cnd(df)
-#'
-#' cnd_df <- sdtm.oak:::new_cnd_df(dat = df, cnd = c(FALSE, NA, TRUE))
-#' sdtm.oak:::get_cnd_df_cnd(cnd_df)
-#'
 #' @keywords internal
 get_cnd_df_cnd <- function(dat) {
   if (is_cnd_df(dat)) {
@@ -151,13 +133,6 @@ get_cnd_df_cnd <- function(dat) {
 #'
 #' @seealso [new_cnd_df()], [is_cnd_df()], [get_cnd_df_cnd()], [rm_cnd_df()].
 #'
-#' @examples
-#' df <- data.frame(x = 1:3, y = letters[1:3])
-#' sdtm.oak:::get_cnd_df_cnd_sum(df)
-#'
-#' cnd_df <- sdtm.oak:::new_cnd_df(dat = df, cnd = c(FALSE, NA, TRUE))
-#' sdtm.oak:::get_cnd_df_cnd_sum(cnd_df)
-#'
 #' @keywords internal
 get_cnd_df_cnd_sum <- function(dat) {
   if (is_cnd_df(dat)) {
@@ -178,13 +153,6 @@ get_cnd_df_cnd_sum <- function(dat) {
 #' @seealso [new_cnd_df()], [is_cnd_df()], [get_cnd_df_cnd()],
 #'   [get_cnd_df_cnd_sum()].
 #'
-#' @examples
-#' df <- data.frame(x = 1:3, y = letters[1:3])
-#' cnd_df <- sdtm.oak:::new_cnd_df(dat = df, cnd = c(FALSE, NA, TRUE))
-#'
-#' sdtm.oak:::is_cnd_df(cnd_df)
-#' sdtm.oak:::is_cnd_df(sdtm.oak:::rm_cnd_df(cnd_df))
-#'
 #' @keywords internal
 rm_cnd_df <- function(dat) {
   if (is_cnd_df(dat)) {
@@ -290,41 +258,6 @@ ctl_new_rowid_pillar.cnd_df <- function(controller, x, width, ...) {
 #'
 #' @returns A logical vector reflecting matching rows in `dat`.
 #'
-#' @examples
-#' # Create a sample data frame
-#' df <- data.frame(
-#'   x = c(1, 2, NA_integer_, 4, 5),
-#'   y = c(TRUE, FALSE, TRUE, FALSE, TRUE),
-#'   z = c("a", "b", "a", "b", "a")
-#' )
-#'
-#' # Simple condition on one column
-#' sdtm.oak:::eval_conditions(df, x > 2)
-#'
-#' # Combined conditions on multiple columns
-#' sdtm.oak:::eval_conditions(df, x > 2 & y)
-#' sdtm.oak:::eval_conditions(df, x > 2, y)
-#'
-#' # Using conditions with NA handling
-#' df_with_na <- data.frame(
-#'   x = c(1, 2, NA, 4, 5),
-#'   y = c(TRUE, FALSE, TRUE, FALSE, TRUE)
-#' )
-#' sdtm.oak:::eval_conditions(df_with_na, x > 2, .na = FALSE)
-#'
-#' # The environment where `eval_conditions()` is called is also inspected
-#' # when evaluating conditions in `...`.
-#' w <- 1
-#' sdtm.oak:::eval_conditions(df, x > w)
-#'
-#' # Using an environment
-#' env <- rlang::env(w = 2)
-#' sdtm.oak:::eval_conditions(df, x > w, .env = env)
-#'
-#' # In place of an environment, you may alternatively pass a list or data frame.
-#' sdtm.oak:::eval_conditions(df, x > w, .env = list(w = 3))
-#' sdtm.oak:::eval_conditions(df, x > w, .env = tibble::tibble(w = 4))
-#'
 #' @keywords internal
 eval_conditions <- function(dat,
                             ...,
@@ -405,15 +338,6 @@ condition_add <- function(dat, ..., .na = NA, .dat2 = rlang::env()) {
 #' @param .after Control where new columns should appear, i.e. after which
 #'   columns.
 #'
-#' @examples
-#' df <- tibble::tibble(x = 1L:3L, y = letters[x])
-#' cnd_df <- condition_add(df, x > 1L, y %in% c("a", "b"))
-#'
-#' # Because `cnd_df` is a conditioned data frame, dplyr::mutate() generic
-#' # dispatches this S3 method and mutates only the second row, as that is the
-#' # only record that fulfills simultaneously `x > 1L` and `y %in% c("a", "b")`.
-#' dplyr::mutate(cnd_df, z = "match")
-#'
 #' @inheritParams dplyr::mutate
 #' @importFrom dplyr mutate
 #' @keywords internal

R/ct.R

@@ -13,21 +13,6 @@
 #' @param set A scalar character (string), one of: `"all"` (default), `"ct_clst"`,
 #'   `"from"` or `"to"`.
 #'
-#' @examples
-#' # These two calls are equivalent and return all required variables in a
-#' # controlled terminology data set.
-#' ct_spec_vars()
-#' ct_spec_vars("all")
-#'
-#' # "Codelist code" variable name.
-#' ct_spec_vars("ct_clst")
-#'
-#' # "From" variables
-#' ct_spec_vars("from")
-#'
-#' # The "to" variable.
-#' ct_spec_vars("to")
-#'
 #' @keywords internal
 #' @export
 ct_spec_vars <- function(set = c("all", "ct_clst", "from", "to")) {
@@ -71,25 +56,6 @@ ct_spec_vars <- function(set = c("all", "ct_clst", "from", "to")) {
 #' @returns The function throws an error if `ct_spec` is not a valid controlled
 #'   terminology data set; otherwise, `ct_spec` is returned invisibly.
 #'
-#' @examples
-#' # If `ct_spec` is a valid controlled terminology then it is returned invisibly.
-#' ct_spec_01 <- read_ct_spec_example("ct-01-cm")
-#' all.equal(ct_spec_01, sdtm.oak:::assert_ct_spec(ct_spec_01))
-#'
-#' # A minimal set of variables needs to be present in `ct_spec` for it to pass the
-#' # assertion; `sdtm.oak:::ct_spec_vars()` defines their names.
-#' (req_vars <- sdtm.oak:::ct_spec_vars())
-#'
-#' # Other (facultative) variables also present in the controlled terminology
-#' # example.
-#' (opt_vars <- setdiff(colnames(ct_spec_01), req_vars))
-#'
-#' # With only the mandatory variables, the assertion still passes.
-#' sdtm.oak:::assert_ct_spec(ct_spec_01[req_vars])
-#'
-#' # Not having the required variables results in an error.
-#' try(sdtm.oak:::assert_ct_spec(ct_spec_01[opt_vars]))
-#'
 #' @keywords internal
 assert_ct_spec <- function(ct_spec, optional = FALSE) {
   admiraldev::assert_data_frame(
@@ -128,21 +94,6 @@ assert_ct_spec <- function(ct_spec, optional = FALSE) {
 #'   given the controlled terminology data set; otherwise, `ct_clst` is returned
 #'   invisibly.
 #'
-#' @examples
-#' # Load a controlled terminology example.
-#' (ct_spec <- read_ct_spec_example("ct-01-cm"))
-#'
-#' # Should work fine.
-#' sdtm.oak:::assert_ct_clst(ct_spec = ct_spec, ct_clst = "C71113")
-#'
-#' # In certain cases, you might allow `ct_clst` to be `NULL` as to indicate absence,
-#' # in that case, set `optional` to `TRUE` to make `assert_ct_clst()` more
-#' # forgiving.
-#' sdtm.oak:::assert_ct_clst(ct_spec = ct_spec, ct_clst = NULL, optional = TRUE)
-#'
-#' # Otherwise it would err.
-#' try(sdtm.oak:::assert_ct_clst(ct_spec = ct_spec, ct_clst = NULL, optional = FALSE))
-#'
 #' @keywords internal
 assert_ct_clst <- function(ct_spec, ct_clst, optional = FALSE) {
   is_ct_spec_missing <- is.null(ct_spec)
@@ -206,18 +157,6 @@ assert_ct_clst <- function(ct_spec, ct_clst, optional = FALSE) {
 #' @returns A [tibble][tibble::tibble-package] with two columns, `from` and
 #'   `to`, indicating the mapping of values, one per row.
 #'
-#' @examples
-#' # Read in a bundled controlled terminology spec example (ex. 01).
-#' (ct_spec_01 <- read_ct_spec_example("ct-01-cm"))
-#'
-#' # Generate mappings from the terminology specification.
-#' sdtm.oak:::ct_mappings(ct_spec = ct_spec_01)
-#'
-#' # Take a glimpse at those mappings where an actual recoding happens.
-#' sdtm.oak:::ct_mappings(ct_spec = ct_spec_01) |>
-#'   dplyr::filter(from != to) |>
-#'   print(n = 20)
-#'
 #' @importFrom rlang .data
 #' @keywords internal
 ct_mappings <- function(ct_spec, from = ct_spec_vars("from"), to = ct_spec_vars("to")) {

R/derive_blfl.R

@@ -9,19 +9,6 @@
 #'
 #' @return Character vector containing ISO8601 dates.
 #'
-#' @examples
-#' ## Partial or missing dates set to NA by default
-#' sdtm.oak:::dtc_datepart(
-#'   c(NA, "", "2021", "2021-12", "2021-12-25", "2021-12-25T12:00:00")
-#' )
-#' # |-->  c(NA, NA, NA, NA, "2021-12-25", "2021-12-25")
-#'
-#' ## Prevent partial or missing dates from being set to NA
-#' sdtm.oak:::dtc_datepart(
-#'   c(NA, "", "2021", "2021-12", "2021-12-25", "2021-12-25T12:00:00"),
-#'   partial_as_na = FALSE
-#' )
-#' # |--> c(NA, "", "2021", "2021-12", "2021-12-25", "2021-12-25")
 #' @keywords internal
 dtc_datepart <- function(dtc, partial_as_na = TRUE) {
   # Assert that dtc is a character vector
@@ -51,36 +38,9 @@ dtc_datepart <- function(dtc, partial_as_na = TRUE) {
 #'   seconds should be ignored (default is `TRUE`).
 #'
 #' @return Character vector containing ISO 8601 times.
-#' @export
 #'
 #' @keywords internal
-#' ## Partial or missing times set to NA and seconds ignored by default
-#' sdtm.oak:::dtc_timepart(
-#'   c(NA, "", "2021-12-25", "2021-12-25T12", "2021-12-25T12:30", "2021-12-25T12:30:59")
-#' )
-#' # |--> c(NA, NA, NA, NA, "12:30", "12:30")
-#'
-#' ## Prevent partial or missing times from being set to NA
-#' sdtm.oak:::dtc_timepart(
-#'   c(NA, "", "2021-12-25", "2021-12-25T12", "2021-12-25T12:30", "2021-12-25T12:30:59"),
-#'   partial_as_na = FALSE
-#' )
-#' # |--> c(NA, "", "", "12", "12:30", "12:30")
-#'
-#' ## Do not ignore seconds, partial or missing times set to NA
-#' sdtm.oak:::dtc_timepart(
-#'   c(NA, "", "2021-12-25", "2021-12-25T12", "2021-12-25T12:30", "2021-12-25T12:30:59"),
-#'   ignore_seconds = FALSE
-#' )
-#' # |--> c(NA, NA, NA, NA, NA, "12:30:59")
-#'
-#' ## Do not ignore seconds and prevent partial or missing times from being set to NA
-#' sdtm.oak:::dtc_timepart(
-#'   c(NA, "", "2021-12-25", "2021-12-25T12", "2021-12-25T12:30", "2021-12-25T12:30:59"),
-#'   partial_as_na = FALSE,
-#'   ignore_seconds = FALSE
-#' )
-#' # |--> c(NA, "", "", "12", "12:30", "12:30:59")
+
 dtc_timepart <- function(dtc, partial_as_na = TRUE, ignore_seconds = TRUE) {
   # Assert that dtc is a character vector
   admiraldev::assert_character_vector(dtc)

R/derive_seq.R

@@ -80,17 +80,6 @@ derive_seq <-
 #'
 #' @returns A logical vector.
 #'
-#' @examples
-#' # A valid SEQ name.
-#' sdtm.oak:::is_seq_name("AESEQ")
-#'
-#' # Not valid sequence number (`--SEQ`) variable names.
-#' # Case matters.
-#' sdtm.oak:::is_seq_name("AEseq")
-#'
-#' # A valid name has to end in "SEQ".
-#' sdtm.oak:::is_seq_name("AESEQUENCE")
-#'
 #' @keywords internal
 is_seq_name <- function(x) {
   stringr::str_detect(x, "SEQ$")