mirror of
https://github.com/agdamsbo/REDCapCAST.git
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250 lines
6.0 KiB
R
250 lines
6.0 KiB
R
#' Convert labelled vectors to factors while preserving attributes
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#'
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#' This extends [forcats::as_factor()] as well as [haven::as_factor()], by appending
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#' original attributes except for "class" after converting to factor to avoid
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#' ta loss in case of rich formatted and labelled data.
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#'
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#' Please refer to parent functions for extended documentation.
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#'
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#' @param x Object to coerce to a factor.
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#' @param ... Other arguments passed down to method.
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#' @export
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#' @examples
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#' # will preserve all attributes but class
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#' c(1, 4, 3, "A", 7, 8, 1) |> as_factor()
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#' structure(c(1, 2, 3, 2, 10, 9),
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#' labels = c(Unknown = 9, Refused = 10)
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#' ) |>
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#' as_factor()
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#'
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#' structure(c(1, 2, 3, 2, 10, 9),
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#' labels = c(Unknown = 9, Refused = 10),
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#' class = "haven_labelled"
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#' ) |>
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#' as_factor()
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#'
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#' @importFrom forcats as_factor
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#' @importFrom rlang check_dots_used
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#' @export
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#' @name as_factor
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as_factor <- function(x, ...) {
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rlang::check_dots_used()
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UseMethod("as_factor")
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}
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#' @rdname as_factor
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#' @export
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as_factor.logical <- function(x, ...) {
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labels <- get_attr(x)
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x <- forcats::as_factor(x, ...)
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set_attr(x, labels[-match("class", names(labels))])
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}
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#' @rdname as_factor
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#' @export
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as_factor.numeric <- function(x, ...) {
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labels <- get_attr(x)
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x <- forcats::as_factor(x, ...)
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set_attr(x, labels[-match("class", names(labels))])
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}
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#' @rdname as_factor
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#' @export
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as_factor.character <- function(x, ...) {
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labels <- get_attr(x)
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x <- forcats::as_factor(x, ...)
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set_attr(x, labels[-match("class", names(labels))])
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}
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#' @rdname as_factor
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#' @export
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as_factor.haven_labelled <- function(x, ...) {
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labels <- get_attr(x)
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x <- haven::as_factor(x, ...)
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set_attr(x, labels[-match("class", names(labels))])
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}
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#' @export
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#' @rdname as_factor
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as_factor.labelled <- as_factor.haven_labelled
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#' Get named vector of factor levels and values
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#'
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#' @param data factor
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#' @param label character string of attribute with named vector of factor labels
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#'
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#' @return named vector
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#' @export
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#'
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#' @examples
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#' structure(c(1, 2, 3, 2, 10, 9),
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#' labels = c(Unknown = 9, Refused = 10),
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#' class = "haven_labelled"
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#' ) |> as_factor() |> named_levels()
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named_levels <- function(data, label = "labels",na.label=NULL, na.value=99) {
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stopifnot(is.factor(data))
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if (!is.null(na.label)){
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attrs <- attributes(data)
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lvls <- as.character(data)
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lvls[is.na(lvls)] <- na.label
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vals <- as.numeric(data)
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vals[is.na(vals)] <- na.value
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lbls <- data.frame(
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name = lvls,
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value = vals
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) |> unique() |>
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(\(d){
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stats::setNames(d$value, d$name)
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})() |>
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sort()
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data <- do.call(structure,
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c(list(.Data=match(vals,lbls)),
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attrs[-match("levels", names(attrs))],
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list(levels=names(lbls),
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labels=lbls)))
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}
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d <- data.frame(
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name = levels(data)[data],
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value = as.numeric(data)
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) |>
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unique()
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## Applying labels
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attr_l <- attr(x = data, which = label, exact = TRUE)
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if (length(attr_l) != 0) {
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d$value[match(names(attr_l), d$name)] <- unname(attr_l)
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}
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out <- stats::setNames(d$value, d$name)
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## Sort if levels are numeric
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## Else, they appear in order of appearance
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if (identical(
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levels(data),
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suppressWarnings(as.character(as.numeric(levels(data))))
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)) {
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out <- out |> sort()
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}
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out
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}
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#' Allows conversion of factor to numeric values preserving original levels
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#'
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#' @param data vector
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#'
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#' @return numeric vector
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#' @export
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#'
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#' @examples
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#' c(1, 4, 3, "A", 7, 8, 1) |>
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#' as_factor() |> fct2num()
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#'
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#' structure(c(1, 2, 3, 2, 10, 9),
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#' labels = c(Unknown = 9, Refused = 10),
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#' class = "haven_labelled"
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#' ) |>
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#' as_factor() |>
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#' fct2num()
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#'
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#' structure(c(1, 2, 3, 2, 10, 9),
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#' labels = c(Unknown = 9, Refused = 10)
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#' ) |>
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#' as_factor() |>
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#' fct2num()
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fct2num <- function(data) {
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stopifnot(is.factor(data))
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as.numeric(named_levels(data))[match(data, names(named_levels(data)))]
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}
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#' Extract attribute. Returns NA if none
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#'
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#' @param data vector
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#' @param attr attribute name
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#'
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#' @return character vector
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#' @export
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#'
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#' @examples
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#' attr(mtcars$mpg, "label") <- "testing"
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#' sapply(mtcars, get_attr)
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#' lapply(mtcars, \(.x)get_attr(.x, NULL))
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#' mtcars |>
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#' numchar2fct(numeric.threshold = 6) |>
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#' ds2dd_detailed()
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get_attr <- function(data, attr = NULL) {
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if (is.null(attr)) {
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attributes(data)
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} else {
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a <- attr(data, attr, exact = TRUE)
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if (is.null(a)) {
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NA
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} else {
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a
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}
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}
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}
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#' Set attributes for named attribute. Appends if attr is NULL
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#'
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#' @param data vector
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#' @param label label
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#' @param attr attribute name
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#'
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#' @return vector with attribute
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#' @export
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#'
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set_attr <- function(data, label, attr = NULL) {
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if (is.null(attr)) {
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## Has to be list...
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stopifnot(is.list(label))
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## ... with names
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stopifnot(length(label)==length(names(label)))
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attributes(data) <- c(attributes(data),label)
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} else {
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attr(data, attr) <- label
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}
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data
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}
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#' Finish incomplete haven attributes substituting missings with values
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#'
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#' @param data haven labelled variable
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#'
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#' @return named vector
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#' @export
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#'
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#' @examples
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#' ds <- structure(c(1, 2, 3, 2, 10, 9),
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#' labels = c(Unknown = 9, Refused = 10),
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#' class = "haven_labelled"
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#' )
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#' haven::is.labelled(ds)
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#' attributes(ds)
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#' ds |> haven_all_levels()
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haven_all_levels <- function(data) {
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stopifnot(haven::is.labelled(data))
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if (length(attributes(data)$labels) == length(unique(data))) {
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out <- attributes(data)$labels
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} else {
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att <- attributes(data)$labels
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out <- c(unique(data[!data %in% att]), att) |>
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stats::setNames(c(unique(data[!data %in% att]), names(att)))
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}
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out
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}
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# readr::read_rds("/Users/au301842/PAaSO/labelled_test.rds") |> ds2dd_detailed()
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#' sample(c(TRUE,FALSE,NA),20,TRUE) |> set_attr("hidden","status") |> trial_fct() |> named_levels(na.label = "Missing") |> sort()
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# trial_fct <- function(x){
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# labels <- get_attr(x)
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# x <- factor(x, levels = c("FALSE", "TRUE"))
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# set_attr(x, labels[-match("class", names(labels))])
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# }
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