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# rle utilities for bit and ff
# (c) 2007-2009 Jens Oehlschägel
# Licence: GPL2
# Provided 'as is', use at your own risk
# Created: 2007-09-03
# Last changed: 2007-10-25
# source("D:/mwp/eanalysis/bit/R/rle.R")
#' Hybrid Index, C-coded utilities
#'
#' These C-coded utilitites speed up index preprocessing considerably.
#'
#' `intrle` is by factor 50 faster and needs less RAM (2x its input
#' vector) compared to [rle()] which needs 9x the RAM of its input
#' vector. This is achieved because we allow the C-code of `intrle` to
#' break when it turns out, that rle-packing will not achieve a compression
#' factor of 3 or better.
#'
#' `intisasc` is a faster version of [is.unsorted()]: it checks whether `x` is sorted.
#'
#' `intisdesc` checks for being sorted descending and by default default assumes that the
#' input `x` contains no NAs.
#'
#' `na.method="none"` treats `NAs` (the smallest integer) like every other integer and
#' hence returns either `TRUE` or `FALSE` `na.method="break"` checks for `NAs` and
#' returns either `NA` as soon as `NA` is encountered. `na.method="skip"` checks for
#' `NAs` and skips over them, hence decides the return value only on the basis of
#' non-NA values.
#'
#'
#' @param x an integer vector
#' @param na.method one of "none", "break", "skip", see details. The strange defaults stem
#' from the initial usage.
#' @return
#' - `intrle` returns an object of class [rle()] or NULL, if rle-compression is not
#' efficient (compression factor <3 or `length(x) < 3`).
#' - `intisasc` returns one of `FALSE, NA, TRUE`
#' - `intisdesc` returns one of `FALSE, TRUE` (if the input contains NAs, the output is
#' undefined)
#' @author Jens Oehlschlägel
#' @seealso [ff::hi()], [rle()], [is.unsorted()],
#' [ff::is.sorted.default()]
#' @keywords IO data
#' @examples
#'
#' intrle(sample(1:10))
#' intrle(diff(1:10))
#' intisasc(1:10)
#' intisasc(10:1)
#' intisasc(c(NA, 1:10))
#' intisdesc(1:10)
#' intisdesc(c(10:1, NA))
#' intisdesc(c(10:6, NA, 5:1))
#' intisdesc(c(10:6, NA, 5:1), na.method="skip")
#' intisdesc(c(10:6, NA, 5:1), na.method="break")
#'
#' @export
# -- fast and efficient rle ------------------
# integer only
# returns rle object only if n>2 && rle is efficient
# (length(values) + lengths(lengths)) <= length(x)
# returns NULL if n<3 || rle is inefficient
intrle <- function(x) {
stopifnot(is.integer(x))
.Call(C_R_int_rle, x)
}
# -- check for sorting and NAs, 0s can be checked later when sorted ------------------
#' @describeIn intrle check whether integer vector is ascending
#' @export
intisasc <- function(x, na.method=c("none", "break", "skip")[2]) {
stopifnot(is.integer(x))
if (na.method == "break")
.Call(C_R_int_is_asc_break, x)
else if (na.method == "none")
.Call(C_R_int_is_asc_none, x)
else
.Call(C_R_int_is_asc_skip, x)
}
#' @describeIn intrle check whether integer vector is descending
#' @export
intisdesc <- function(x, na.method=c("none", "break", "skip")[1]) {
stopifnot(is.integer(x))
if (na.method == "none")
.Call(C_R_int_is_desc_none, x)
else if (na.method == "break")
.Call(C_R_int_is_desc_break, x)
else
.Call(C_R_int_is_desc_skip, x)
}
# -- basic sequence packing and unpacking ---------------------------------------------------
#' Hybrid Index, rle-pack utilities
#'
#' Basic utilities for rle packing and unpacking and apropriate methods for
#' [rev()] and [unique()].
#'
#'
#' @param x in 'rlepack' an integer vector, in the other functions an object of
#' class 'rlepack'
#' @param pack FALSE to suppress packing
#' @param incomparables just to keep R CMD CHECK quiet (not used)
#' @param ... just to keep R CMD CHECK quiet (not used)
#' @return A list with components:
#' - first: the first element of the packed sequence
#' - dat: either an object of class [rle()] or the complete input vector `x` if
#' rle-packing is not efficient
#' - last: the last element of the packed sequence
#'
#' @author Jens Oehlschlägel
#' @seealso [ff::hi()], [intrle()], [rle()], [rev()], [unique()]
#' @keywords IO data
#' @examples
#'
#' x <- rlepack(rep(0L, 10))
#'
#' @export
rlepack <- function(x, ...) UseMethod("rlepack")
#' @rdname rlepack
#' @export
rlepack.integer <- function(x, pack = TRUE, ...) {
stopifnot(is.integer(x))
n <- length(x)
if (n > 1L) {
if (pack)
# returns NULL if rle is inefficient, old condition was 2*length(r$lengths)<n
r <- intrle(diff(x))
else
r <- NULL
out = list(first=x[1], dat=if (is.null(r)) x else r, last=x[n])
} else if (n == 1) {
out = list(first=x[1], dat=x, last=x[1])
} else {
out = list(first=NA_integer_, dat=x, last=NA_integer_)
}
class(out) <- "rlepack"
out
}
#' @rdname rlepack
#' @export
rleunpack <- function(x) UseMethod("rleunpack")
#' @rdname rlepack
#' @export
rleunpack.rlepack <- function(x) {
if (inherits(x$dat, "rle"))
as.integer(cumsum(c(x$first, rep(x$dat$values, x$dat$lengths))))
else
x$dat
}
#' @rdname rlepack
#' @export
rev.rlepack <- function(x) {
if (inherits(x$dat, "rle")) {
x$dat$values <- -rev(x$dat$values)
x$dat$lengths <- rev(x$dat$lengths)
} else {
x$dat <- rev(x$dat)
}
buf <- x$first
x$first <- x$last
x$last <- buf
x
}
# beware: only for sorted input identical with unique()
# beware: rlepack(unique(x)) is faster than unique(rlepack(x))
# we use this only in hi() and as.hi.default()
#' @rdname rlepack
#' @export
unique.rlepack <- function(x, incomparables = FALSE, ...) {
if (inherits(x$dat, "rle")) {
tab <- tabulate(sign(x$dat$values) + 2L, nbins=3L)
if (tab[1] && tab[3])
x <- rlepack(unique(rleunpack(x)))
else if (tab[2]) {
x$dat$lengths <- x$dat$lengths[x$dat$values != 0]
x$dat$values <- x$dat$values[x$dat$values != 0]
}
# else nothing to do: no repeated values
} else {
x$dat <- unique(x$dat)
}
x
}
# beware: only for sorted input identical with unique()
# beware: returns TRUE/FALSE, not position of first duplicate
#' @rdname rlepack
#' @export
anyDuplicated.rlepack <- function(x, incomparables = FALSE, ...) {
if (!inherits(x$dat, "rle"))
return(anyDuplicated(x$dat))
tab <- tabulate(sign(x$dat$values) + 2L, nbins=3L)
if (tab[1] && tab[3])
return(anyDuplicated(rleunpack(x)))
if (!tab[2])
return(0L)
w <- .Call(C_R_first_zero, x$dat$values)
if (!w)
return(0L)
if (w <= 1L)
return(2L)
sum(x$dat$lengths[1:(w - 1L)]) + 2L
}
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