R/subsetting.R

In extraoperators: Extra Binary Relational and Logical Operators

#' @name subsetting
#' @rdname subsetting
#'
#' @title Several ways to subset based on logical range comparison helpers
#'
#' @param e1 A number of vector to be evaluated and subset
#' @param e2 A vector of one or two numbers used to denote the
#'   limits for logical comparison.
#'
#' @return A subset of \code{e1} that meets the logical conditions.
NULL

#' @rdname subsetting
#' @export
#' @examples
#'
#' 1:5 %sgele% c(2, 4)
#' 1:5 %sgele% c(4, 2) # order does not matter uses min / max
`%sgele%` <- function(e1, e2) {
  stopifnot(identical(length(e2), 2L))
  stopifnot(!anyNA(e2))

  e1[e1 >= min(e2) & e1 <= max(e2)]
}

#' @rdname subsetting
#' @export
#' @examples
#'
#' 1:5 %sgel% c(2, 4)
#' 1:5 %sgel% c(4, 2) # order does not matter uses min / max
`%sgel%` <- function(e1, e2) {
  stopifnot(identical(length(e2), 2L))
  stopifnot(!anyNA(e2))

  e1[e1 >= min(e2) & e1 < max(e2)]
}

#' @rdname subsetting
#' @export
#' @examples
#'
#' 1:5 %sgle% c(2, 4)
#' 1:5 %sgle% c(4, 2) # order does not matter uses min / max
`%sgle%` <- function(e1, e2) {
  stopifnot(identical(length(e2), 2L))
  stopifnot(!anyNA(e2))

  e1[e1 > min(e2) & e1 <= max(e2)]
}

#' @rdname subsetting
#' @export
#' @examples
#'
#' 1:5 %sgl% c(2, 4)
#' 1:5 %sgl% c(4, 2) # order does not matter uses min / max
`%sgl%` <- function(e1, e2) {
  stopifnot(identical(length(e2), 2L))
  stopifnot(!anyNA(e2))
  e1[e1 > min(e2) & e1 < max(e2)]
}

#' @rdname subsetting
#' @export
#' @examples
#'
#' 1:5 %sge% 2
#' 1:5 %sge% 4
`%sge%` <- function(e1, e2) {e1[e1 >= e2]}

#' @rdname subsetting
#' @export
#' @examples
#'
#' 1:5 %sg% 2
#' 1:5 %sg% 4
`%sg%` <- function(e1, e2) {e1[e1 > e2]}

#' @rdname subsetting
#' @export
#' @examples
#'
#' 1:5 %sle% 2
#' 1:5 %sle% 4
`%sle%` <- function(e1, e2) {e1[e1 <= e2]}

#' @rdname subsetting
#' @export
#' @examples
#'
#' 1:5 %sl% 2
#' 1:5 %sl% 4
`%sl%` <- function(e1, e2) {e1[e1 < e2]}

#' @rdname subsetting
#' @export
#' @examples
#'
#' 1:5 %sin% c(2, 99)
#' c("jack", "jill", "john", "jane") %sin% c("jill", "jane", "bill")
`%sin%` <- function(e1, e2) {e1[e1 %in% e2]}

#' @rdname subsetting
#' @export
#' @examples
#'
#' 1:5 %s!in% c(2, 99)
#' c("jack", "jill", "john", "jane") %s!in% c("jill", "jane", "bill")
`%s!in%` <- function(e1, e2) {e1[e1 %!in% e2]}

#' @rdname subsetting
#' @export
`%snin%` <- `%s!in%` ## this is an alias


#' @rdname subsetting
#' @export
#' @examples
#'
#' 1:5 %s==% 1:5
#' 1:5 %s==% c(1:4, 1)
`%s==%` <- function(e1, e2) {e1[e1 == e2]}

#' @rdname subsetting
#' @export
#' @examples
#'
#' 1:5 %s!=% 1:5
#' 1:5 %s!=% c(1:4, 1)
`%s!=%` <- function(e1, e2) {e1[e1 != e2]}


#' @rdname subsetting
#' @export
#' @examples
#' ## define a variable
#' sample_data <- c(1, 3, 9, 5, NA, -9)
#'
#' ## suppose that we expect that values should fall in [1, 10]
#' ## unless they are special character, -9 used for unknown / refused
#' sample_data %sc% "( >= 1 & <= 10 ) | == -9"
#'
#' ## we might expect some missing values and be OK as long as
#' ## above conditions are met or values are missing
#' sample_data %sc% "( >= 1 & <= 10 ) | == -9 | is.na"
#'
#' ## equally we might be expecting NO missing values
#' ## and want missing values to come up as FALSE
#' sample_data %sc% "(( >= 1 & <= 10 ) | == -9) & !is.na"
#'
#' ## clean up
#' rm(sample_data)
`%sc%`  <- function(e1, e2) {
  e1[e1 %c% e2]
}


#' @rdname subsetting
#' @export
#' @examples
#' ## define a variable
#' sample_data <- c(1, 3, 9, 5, -9)
#'
#' sample_data %se% "(-8, 1] | [2, 9)"
#'
#' ## clean up
#' rm(sample_data)
`%se%`  <- function(e1, e2) {
  e1[e1 %e% e2]
}