experimental
geom_hilo_linerange(
mapping = NULL,
data = NULL,
stat = "identity",
position = "identity",
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE,
...
)
The data to be displayed in this layer. There are three options:
If NULL
, the default, the data is inherited from the plot
data as specified in the call to ggplot()
.
A data.frame
, or other object, will override the plot
data. All objects will be fortified to produce a data frame. See
fortify()
for which variables will be created.
A function
will be called with a single argument,
the plot data. The return value must be a data.frame
, and
will be used as the layer data. A function
can be created
from a formula
(e.g. ~ head(.x, 10)
).
The statistical transformation to use on the data for this layer, as a string.
Position adjustment, either as a string, or the result of a call to a position adjustment function.
If FALSE
, the default, missing values are removed with
a warning. If TRUE
, missing values are silently removed.
logical. Should this layer be included in the legends?
NA
, the default, includes if any aesthetics are mapped.
FALSE
never includes, and TRUE
always includes.
It can also be a named logical vector to finely select the aesthetics to
display.
If 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. borders()
.
Other arguments passed on to layer()
. These are
often aesthetics, used to set an aesthetic to a fixed value, like
colour = "red"
or size = 3
. They may also be parameters
to the paired geom/stat.
geom_hilo_linerange()
displays the interval defined by a hilo object. The
luminance of the shaded area indicates its confidence level. The shade colour
can be controlled by the fill
aesthetic, however the luminance will be
overwritten to represent the confidence level.
geom_hilo_ribbon()
for continuous hilo intervals (ribbons)
# NOT RUN {
dist <- dist_normal(1:3, 1:3)
library(ggplot2)
ggplot(
data.frame(x = rep(1:3, 2), interval = c(hilo(dist, 80), hilo(dist, 95)))
) +
geom_hilo_linerange(aes(x = x, hilo = interval))
# }
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