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#' Get Meta
#'
#' [getMeta()] returns the inverse, a character vector of string
#' names of *non*-analyte feature columns/variables, which typically
#' correspond to the clinical ("meta") data variables.
#' S3 methods exist for these classes:
#' ```{r method-classes2, echo = FALSE}
#' options(width = 80)
#' methods("getMeta")
#' ```
#'
#' @rdname getAnalytes
#' @return [getMeta()]: a character vector of ADAT clinical ("meta") data names.
#' @return For both, if `n = TRUE`, an integer corresponding to the
#' __length__ of the character vector.
#' @examples
#'
#' # clinical variables
#' mvec <- getMeta(example_data)
#' head(mvec, 10)
#' getMeta(example_data, n = TRUE)
#'
#' # test 'data.frame' and 'character' S3 methods are identical
#' identical(getMeta(example_data), getMeta(names(example_data))) # TRUE
#' @export
getMeta <- function(x, n = FALSE) UseMethod("getMeta")
#' @noRd
#' @export
getMeta.default <- function(x, n) {
stop(
"Couldn't find a S3 method for this class object: ", .value(class(x)),
call. = FALSE
)
}
#' @noRd
#' @export
getMeta.data.frame <- function(x, n = FALSE) {
getMeta(names(x), n = n)
}
#' @noRd
#' @export
getMeta.soma_adat <- getMeta.data.frame
#' @noRd
#' @export
getMeta.list <- getMeta.data.frame
#' @noRd
#' @export
getMeta.matrix <- function(x, n = FALSE) {
getMeta(colnames(x), n = n)
}
#' @noRd
#' @export
getMeta.character <- function(x, n = FALSE) {
lgl <- !is.apt(x)
if ( n ) {
sum(lgl)
} else {
x[lgl]
}
}
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