This geom makes it possible to add a layer showing edge presence as a density
map. Each edge is converted to
n points along the line and a jitter is
applied. Based on this dataset a two-dimensional kernel density estimation is
applied and plotted as a raster image. The density is mapped to the alpha
level, making it possible to map a variable to the fill.
geom_edge_density( mapping = NULL, data = get_edges("short"), position = "identity", show.legend = NA, n = 100, ... )
Position adjustment, either as a string, or the result of a call to a position adjustment function.
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
The number of points to estimate in the x and y direction, i.e. the resolution of the raster.
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_edge_density understand the following aesthetics. Bold aesthetics are
automatically set, but can be overridden.
x y xend yend edge_fill filter
The coordinates for each pixel in the raster
The density associated with the pixel
In order to avoid excessive typing edge aesthetic names are
automatically expanded. Because of this it is not necessary to write
edge_colour within the
aes() call as
automatically be renamed appropriately.
require(tidygraph) gr <- create_notable('bull') %>% activate(edges) %>% mutate(class = sample(letters[1:3], n(), replace = TRUE)) ggraph(gr, 'stress') + geom_edge_density(aes(fill = class)) + geom_edge_link() + geom_node_point() #> Warning: Raster pixels are placed at uneven horizontal intervals and will be shifted. Consider using geom_tile() instead. #> Warning: Raster pixels are placed at uneven vertical intervals and will be shifted. Consider using geom_tile() instead.