This set of geoms and stats allows you to display voronoi tesselation and
delaunay triangulation, both as polygons and as line segments. Furthermore
it lets you augment your point data with related summary statistics. The
computations are based on the deldir::deldir()
package.
geom_voronoi_tile(
mapping = NULL,
data = NULL,
stat = "voronoi_tile",
position = "identity",
na.rm = FALSE,
bound = NULL,
eps = 1e-09,
max.radius = NULL,
normalize = FALSE,
asp.ratio = 1,
expand = 0,
radius = 0,
show.legend = NA,
inherit.aes = TRUE,
...
)
geom_voronoi_segment(
mapping = NULL,
data = NULL,
stat = "voronoi_segment",
position = "identity",
na.rm = FALSE,
bound = NULL,
eps = 1e-09,
normalize = FALSE,
asp.ratio = 1,
show.legend = NA,
inherit.aes = TRUE,
...
)
geom_delaunay_tile(
mapping = NULL,
data = NULL,
stat = "delaunay_tile",
position = "identity",
na.rm = FALSE,
bound = NULL,
eps = 1e-09,
normalize = FALSE,
asp.ratio = 1,
expand = 0,
radius = 0,
show.legend = NA,
inherit.aes = TRUE,
...
)
geom_delaunay_segment(
mapping = NULL,
data = NULL,
stat = "delaunay_segment",
position = "identity",
na.rm = FALSE,
bound = NULL,
eps = 1e-09,
normalize = FALSE,
asp.ratio = 1,
show.legend = NA,
inherit.aes = TRUE,
...
)
geom_delaunay_segment2(
mapping = NULL,
data = NULL,
stat = "delaunay_segment2",
position = "identity",
na.rm = FALSE,
bound = NULL,
eps = 1e-09,
normalize = FALSE,
asp.ratio = 1,
n = 100,
show.legend = NA,
inherit.aes = TRUE,
...
)
stat_delvor_summary(
mapping = NULL,
data = NULL,
geom = "point",
position = "identity",
na.rm = FALSE,
bound = NULL,
eps = 1e-09,
normalize = FALSE,
asp.ratio = 1,
show.legend = NA,
inherit.aes = TRUE,
...
)
Set of aesthetic mappings created by aes()
. If specified and
inherit.aes = TRUE
(the default), it is combined with the default mapping
at the top level of the plot. You must supply mapping
if there is no plot
mapping.
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, either as a ggproto
Geom
subclass or as a string naming the
stat stripped of the stat_
prefix (e.g. "count"
rather than
"stat_count"
)
Position adjustment, either as a string naming the adjustment
(e.g. "jitter"
to use position_jitter
), or the result of a call to a
position adjustment function. Use the latter if you need to change the
settings of the adjustment.
If FALSE
, the default, missing values are removed with
a warning. If TRUE
, missing values are silently removed.
The bounding rectangle for the tesselation or a custom polygon
to clip the tesselation to. Defaults to NULL
which creates a rectangle
expanded 10\
vector giving the bounds in the following order: xmin, xmax, ymin, ymax. If
supplied as a polygon it should either be a 2-column matrix or a data.frame
containing an x
and y
column.
A value of epsilon used in testing whether a quantity is zero, mainly in the context of whether points are collinear. If anomalous errors arise, it is possible that these may averted by adjusting the value of eps upward or downward.
The maximum distance a tile can extend from the point of
origin. Will in effect clip each tile to a circle centered at the point with
the given radius. If normalize = TRUE
the radius will be given relative to
the normalized values
Should coordinates be normalized prior to calculations. If
x
and y
are in wildly different ranges it can lead to
tesselation and triangulation that seems off when plotted without
ggplot2::coord_fixed()
. Normalization of coordinates solves this.
The coordinates are transformed back after calculations.
If normalize = TRUE
the x values will be multiplied by this
amount after normalization.
A numeric or unit vector of length one, specifying the expansion amount. Negative values will result in contraction instead. If the value is given as a numeric it will be understood as a proportion of the plot area width.
As expand
but specifying the corner radius.
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.
The number of points to create for each segment
The geometric object to use to display the data, either as a
ggproto
Geom
subclass or as a string naming the geom stripped of the
geom_
prefix (e.g. "point"
rather than "geom_point"
)
geom_voronoi_tile and geom_delaunay_tile understand the following aesthetics (required aesthetics are in bold):
x
y
alpha
color
fill
linetype
size
geom_voronoi_segment, geom_delaunay_segment, and geom_delaunay_segment2 understand the following aesthetics (required aesthetics are in bold):
x
y
alpha
color
linetype
size
stat_delvor_summary computes the following variables:
If switch.centroid = TRUE
this will be the coordinates for
the voronoi tile centroid, otherwise it is the original point
If switch.centroid = FALSE
this will be the
coordinates for the voronoi tile centroid, otherwise it will be NULL
If switch.centroid = TRUE
this will be the
coordinates for the original point, otherwise it will be NULL
Number of triangles emanating from the point
The total area of triangles emanating from the point divided by 3
triarea
divided by the sum of the area of all
triangles
Number of sides on the voronoi tile associated with the point
Number of sides of the associated voronoi tile that is part of the bounding box
The area of the voronoi tile associated with the point
vorarea
divided by the sum of all voronoi tiles
# Voronoi
# You usually wants all points to take part in the same tesselation so set
# the group aesthetic to a constant (-1L is just a convention)
ggplot(iris, aes(Sepal.Length, Sepal.Width, group = -1L)) +
geom_voronoi_tile(aes(fill = Species)) +
geom_voronoi_segment() +
geom_text(aes(label = after_stat(nsides), size = after_stat(vorarea)),
stat = 'delvor_summary', switch.centroid = TRUE
)
#> Warning: `stat_voronoi_tile()` is dropping duplicated points
#> Warning: `stat_voronoi_segment()` is dropping duplicated points
#> Warning: `stat_delvor_summary()` is dropping duplicated points
# Difference of normalize = TRUE (segment layer is calculated without
# normalisation)
ggplot(iris, aes(Sepal.Length, Sepal.Width, group = -1L)) +
geom_voronoi_tile(aes(fill = Species), normalize = TRUE) +
geom_voronoi_segment()
#> Warning: `stat_voronoi_tile()` is dropping duplicated points
#> Warning: `stat_voronoi_segment()` is dropping duplicated points
# Set a max radius
ggplot(iris, aes(Sepal.Length, Sepal.Width, group = -1L)) +
geom_voronoi_tile(aes(fill = Species), colour = 'black', max.radius = 0.25)
#> Warning: `stat_voronoi_tile()` is dropping duplicated points
# Set custom bounding polygon
triangle <- cbind(c(3, 9, 6), c(1, 1, 6))
ggplot(iris, aes(Sepal.Length, Sepal.Width, group = -1L)) +
geom_voronoi_tile(aes(fill = Species), colour = 'black', bound = triangle)
#> Warning: `stat_voronoi_tile()` is dropping duplicated points
# Use geom_shape functionality to round corners etc
ggplot(iris, aes(Sepal.Length, Sepal.Width, group = -1L)) +
geom_voronoi_tile(aes(fill = Species), colour = 'black',
expand = unit(-.5, 'mm'), radius = unit(2, 'mm'))
#> Warning: `stat_voronoi_tile()` is dropping duplicated points
# Delaunay triangles
ggplot(iris, aes(Sepal.Length, Sepal.Width)) +
geom_delaunay_tile(alpha = 0.3, colour = 'black')
#> Warning: `stat_delaunay_tile()` is dropping duplicated points
# Use geom_delauney_segment2 to interpolate aestetics between end points
ggplot(iris, aes(Sepal.Length, Sepal.Width)) +
geom_delaunay_segment2(aes(colour = Species, group = -1), size = 2,
lineend = 'round')
#> Warning: `stat_delaunay_segment2()` is dropping duplicated points