A combination of geom_line()
and geom_ribbon()
with default aesthetics
designed for use with output from point_interval()
.
geom_lineribbon(
mapping = NULL,
data = NULL,
stat = "identity",
position = "identity",
...,
step = FALSE,
orientation = NA,
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.
Other arguments passed to layer()
.
Should the line/ribbon be drawn as a step function? One of: FALSE
(do not draw as a step
function, the default), TRUE
(draw a step function using the "mid"
approach), "mid"
(draw steps midway between adjacent x values), "hv"
(draw horizontal-then-vertical steps), "vh"
(draw as vertical-then-horizontal steps). TRUE
is an alias for "mid"
because for a step function with
ribbons, "mid"
is probably what you want (for the other two step approaches the ribbons at either the
vert first or vert last x value will not be visible).
Whether this geom is drawn horizontally ("horizontal"
) or
vertically ("vertical"
). The default, NA
, automatically detects the orientation based on how the
aesthetics are assigned, and should generally do an okay job at this. When horizontal (resp. vertical),
the geom uses the y
(resp. x
) aesthetic to identify different groups, then for each group uses
the x
(resp. y
) aesthetic and the thickness
aesthetic to draw a function as an slab, and draws
points and intervals horizontally (resp. vertically) using the xmin
, x
, and xmax
(resp.
ymin
, y
, and ymax
) aesthetics. For compatibility with the base
ggplot naming scheme for orientation
, "x"
can be used as an alias for "vertical"
and "y"
as an alias for
"horizontal"
(tidybayes had an orientation
parameter before ggplot did, and I think the tidybayes naming
scheme is more intuitive: "x"
and "y"
are not orientations and their mapping to orientations is, in my
opinion, backwards; but the base ggplot naming scheme is allowed for compatibility).
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()
.
A ggplot2::Geom representing a combined line+uncertainty ribbon geometry which can
be added to a ggplot()
object.
geom_lineribbon
is a combination version of a geom_line()
, and geom_ribbon
designed for use
with output from point_interval()
. This geom sets some default aesthetics equal to the .width
column generated by the point_interval
family of functions, making them
often more convenient than a vanilla geom_ribbon()
+ geom_line()
.
Specifically, geom_lineribbon
acts as if its default aesthetics are
aes(fill = forcats::fct_rev(ordered(.width)))
.
See stat_lineribbon()
for a version that does summarizing of samples into points and intervals
within ggplot. See geom_pointinterval()
for a similar geom intended
for point summaries and intervals. See geom_ribbon()
and geom_line()
for the geoms this is
based on.
# NOT RUN {
library(dplyr)
library(ggplot2)
theme_set(theme_ggdist())
tibble(x = 1:10) %>%
group_by_all() %>%
do(tibble(y = rnorm(100, .$x))) %>%
median_qi(.width = c(.5, .8, .95)) %>%
ggplot(aes(x = x, y = y, ymin = .lower, ymax = .upper)) +
# automatically uses aes(fill = forcats::fct_rev(ordered(.width)))
geom_lineribbon() +
scale_fill_brewer()
# }
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