Add a plot to annotate observations
cross_mark(
mark,
data = waiver(),
...,
obs_size = 1,
inherit_index = NULL,
inherit_panel = NULL,
inherit_nobs = NULL,
size = NULL,
active = NULL
)
A mark_draw()
object to define how to draw the links. Like
mark_line()
, mark_tetragon()
. Note the names of the pair links will
be used to define the panel names so must be unique.
The dataset to use for the layout. By default,
fortify_matrix()
will convert the data to a matrix. This argument
allows you to change the layout data. If not specified, the original data
will be used.
<dyn-dots> Additional arguments passed to
fortify_matrix()
.
A single numeric value that indicates the size of a single
observation, ranging from (0, 1]
.
A boolean value indicating whether to inherit the
ordering index. If TRUE
, will match the layout ordering index with the
data names.
A boolean value indicating whether to inherit the
panel group. If TRUE
, will match the layout panel with the data names.
A boolean value indicating whether to inherit the
number of observations (nobs). If TRUE
, the data
input must be
compatible with the layout data.
The relative size of the plot, can be specified as a
unit()
. Note that for circle_layout()
, all size values
will be interpreted as relative sizes, as this layout type adjusts based on
the available space in the circular arrangement.
A active()
object that defines the context settings when
added to a layout.
The cross_mark
function initializes a ggplot
object. The underlying data
contains following columns:
.panel
: the panel for the aligned axis. It means x-axis
for vertical
stack layout (including top and bottom annotation), y-axis
for
horizontal stack layout (including left and right annotation).
.names
(vec_names()
) and .index
(vec_size()
/NROW()
): a character names (only
applicable when names exists) and an integer of index of the original
data.
.hand
: A factor with levels c("left", "right")
for horizontal stack
layouts, or c("top", "bottom")
for vertical stack layouts, indicating
the position of the linked observations.
You can use scheme_data()
to modify the internal data if needed.