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#' @include AllClasses.R AllGenerics.R
#' @importFrom dplyr group_by
#' @export
dplyr::group_by
#' group_by TidySet
#'
#' Use group_by to group the TidySet object. You can use activate with
#' group_by or with the whole data.
#' @param .data The TidySet object
#' @param ... The logical predicates in terms of the variables of the sets
#' @return A grouped data.frame (See The dplyr help page)
#' @export
#' @family methods
#' @seealso [dplyr::group_by()] and [activate()]
#' @examples
#' relations <- data.frame(
#' sets = c(rep("a", 5), "b", rep("a2", 5), "b2"),
#' elements = rep(letters[seq_len(6)], 2),
#' fuzzy = runif(12)
#' )
#' a <- tidySet(relations)
#' elements(a) <- cbind(elements(a),
#' type = c(rep("Gene", 4), rep("lncRNA", 2))
#' )
#' group_by(a, elements)
#' @rdname group_by_
#' @export
#' @method group_by TidySet
group_by.TidySet <- function(.data, ...) {
if (is.null(active(.data))) {
dplyr::group_by(as.data.frame(.data), ...)
} else {
dplyr::group_by(slot(.data, active(.data)), ...)
}
}
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