R/filter.R

In twolodzko/lolplyr: Adapting dplyr for lists-of-lists

#' Evaluate logical predicates for each element of the list
#'
#' @param .data a list.
#' @param \dots logical predicates defined in terms of the variables in
#'              \code{.data}.
#'
#' @examples
#'
#' as_lol(mtcars) %>%
#'   check_cond_and(cyl == 4, mpg > 30)
#'
#' as_lol(mtcars) %>%
#'   check_cond_or(cyl == 4, mpg > 30)
#'
#' @export

check_cond_and <- function(.data, ...) UseMethod("check_cond_and")

#' @export

check_cond_and.list <- function(.data, ...) {
  dots <- quos(...)
  map_lgl(.data, function(.x) {
    all(unlist(try_eval(dots, data = as.list(.x))))
  })
}

#' @rdname check_cond_and
#' @export

check_cond_or <- function(.data, ...) UseMethod("check_cond_or")

#' @export

check_cond_or.list <- function(.data, ...) {
  dots <- quos(...)
  map_lgl(.data, function(.x) {
    any(unlist(try_eval(dots, data = as.list(.x))))
  })
}


#' Return entries with matching conditions
#'
#' \code{filter_and} joins conditions with logical AND,
#' while \code{filter_or} joins conditions with logical OR.
#' \code{filter} is a wrapper around \code{filter_and} function.
#'
#' @param .data a list.
#' @param \dots logical predicates defined in terms of the variables in
#'              \code{.data}. Only entries where the condition evaluate to
#'              \code{TRUE} are kept.
#'
#' @seealso \code{\link[dplyr]{filter}}, \code{\link{check_cond_and}}
#'
#' @examples
#'
#' as_lol(mtcars) %>%
#'  filter(cyl == 4, mpg > 30) %>%
#'  summarise(
#'    cyl_range = range(cyl),
#'    min_mpg = min(mpg)
#'  )
#'
#' as_lov(mtcars) %>%
#'   filter(mpg > 30)
#'
#' @export

filter_and <- function(.data, ...) UseMethod("filter_and")

#' @export

filter_and.list <- function(.data, ...) {
  .data[check_cond_and(.data, ...)]
}

#' @rdname filter_and
#' @export

filter_or <- function(.data, ...) UseMethod("filter_or")

#' @export

filter_or.list <- function(.data, ...) {
  .data[check_cond_or(.data, ...)]
}

#' @rdname filter_and
#' @export

filter.list <- function(.data, ...) {
  filter_and(.data, ...)
}