#' create a plot with inverse empirical cumulative distribution function
#
#' @param mapping Set of aesthetic mappings created by \code{aes} or
#' \code{aes_}. If specified and \code{inherit.aes = TRUE} (the
#' default), it is combined with the default mapping at the top level of the
#' plot. You must supply \code{mapping} if there is no plot mapping.
#' @param data The data to be displayed in this layer. There are three
#' options:
#'
#' If \code{NULL}, the default, the data is inherited from the plot
#' data as specified in the call to \code{ggplot}.
#'
#' A \code{data.frame}, or other object, will override the plot
#' data. All objects will be fortified to produce a data frame. See
#' \code{fortify} for which variables will be created.
#'
#' A \code{function} will be called with a single argument,
#' the plot data. The return value must be a \code{data.frame.}, and
#' will be used as the layer data.
#' @param geom The geometric object to use display the data
#' @param stat The statistical transformation to use on the data for this
#' layer, as a string.
#' @param position Position adjustment, either as a string, or the result of
#' a call to a position adjustment function.
#' @param ... other arguments passed on to layer. These are often aesthetics, used to set an aesthetic to a fixed value, like color = "red" or size = 3. They may also be parameters to the paired geom/stat.
#' @param show.legend logical. Should this layer be included in the legends?
#' \code{NA}, the default, includes if any aesthetics are mapped.
#' \code{FALSE} never includes, and \code{TRUE} always includes.
#' @param inherit.aes If \code{FALSE}, overrides the default aesthetics,
#' rather than combining with them. This is most useful for helper functions
#' that define both data and aesthetics and shouldn't inherit behaviour from
#' the default plot specification, e.g. \code{borders}.
#' @param params Additional parameters to the \code{geom} and \code{stat}.
geom_iecdf <- function(mapping = NULL, data = NULL, geom = "point",
position = "identity", show.legend = NA,
inherit.aes = TRUE, ...) {
layer(
stat = StatIecdf,
data = data,
mapping = mapping,
geom = geom,
position = position,
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(...)
)
}
StatIecdf <- ggproto(
"GeomIecdf", Stat,
compute_group = function(data, scales) {
x <- c(sort(data$x),Inf)
n <- length(x)
if (n < 1)
stop("'x' must have 1 or more non-missing values")
vals <- unique(x)
rval <-
approxfun(
vals, 1 - cumsum(tabulate(match(x, vals))) / n,
method = "constant", yleft = 0, yright = 1, f = 0, ties = "ordered"
)
class(rval) <-
c("ecdf", "stepfun", class(rval))
assign("nobs", n, envir = environment(rval))
attr(rval, "call") <- sys.call()
data.frame(x = sort(x),y = rval(sort(x)))
},
required_aes = c("x")
)
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