A diagonal is a bezier curve where the control points are moved perpendicularly towards the center in either the x or y direction a fixed amount. The versions provided here calculates horizontal diagonals meaning that the x coordinate is moved to achieve the control point. The geom_diagonal() and stat_diagonal() functions are simply helpers that takes care of calculating the position of the control points and then forwards the actual bezier calculations to geom_bezier().

stat_diagonal(mapping = NULL, data = NULL, geom = "path",
position = "identity", n = 100, strength = 0.5, na.rm = FALSE,
show.legend = NA, inherit.aes = TRUE, ...)

geom_diagonal(mapping = NULL, data = NULL, stat = "diagonal",
position = "identity", n = 100, na.rm = FALSE, strength = 0.5,
show.legend = NA, inherit.aes = TRUE, ...)

stat_diagonal2(mapping = NULL, data = NULL,
geom = "path_interpolate", position = "identity", na.rm = FALSE,
show.legend = NA, n = 100, strength = 0.5, inherit.aes = TRUE,
...)

geom_diagonal2(mapping = NULL, data = NULL, stat = "diagonal2",
position = "identity", arrow = NULL, lineend = "butt",
na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, n = 100,
strength = 0.5, ...)

stat_diagonal0(mapping = NULL, data = NULL, geom = "bezier0",
position = "identity", na.rm = FALSE, show.legend = NA,
inherit.aes = TRUE, strength = 0.5, ...)

geom_diagonal0(mapping = NULL, data = NULL, stat = "diagonal0",
position = "identity", arrow = NULL, lineend = "butt",
na.rm = FALSE, show.legend = NA, inherit.aes = TRUE,
strength = 0.5, ...)

## Arguments

mapping Set of aesthetic mappings created by aes() or 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 geometric object to use display the data Position adjustment, either as a string, or the result of a call to a position adjustment function. The number of points to create for each segment The proportion to move the control point along the x-axis towards the other end of the bezier curve 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. The statistical transformation to use on the data for this layer, as a string. Arrow specification, as created by grid::arrow(). Line end style (round, butt, square).

## Aesthetics

geom_diagonal and geom_diagonal0 understand the following aesthetics (required aesthetics are in bold):

• x

• y

• xend

• yend

• color

• size

• linetype

• alpha

• lineend

geom_diagonal2 understand the following aesthetics (required aesthetics are in bold):

• x

• y

• group

• color

• size

• linetype

• alpha

• lineend

## Computed variables

x, y

The interpolated point coordinates

index

The progression along the interpolation mapped between 0 and 1

## Examples

data <- data.frame(
x = rep(0, 10),
y = 1:10,
xend = 1:10,
yend = 2:11
)

ggplot(data) +
geom_diagonal(aes(x, y, xend = xend, yend = yend)) # The standard version provides an index to create gradients
ggplot(data) +
geom_diagonal(aes(x, y, xend = xend, yend = yend, alpha = stat(index))) # The 0 version uses bezierGrob under the hood for an approximation
ggplot(data) +
geom_diagonal0(aes(x, y, xend = xend, yend = yend)) # The 2 version allows you to interpolate between endpoint aesthetics
data2 <- data.frame(
x = c(data$x, data$xend),
y = c(data$y, data$yend),
group = rep(1:10, 2),
colour = sample(letters[1:5], 20, TRUE)
)
ggplot(data2) +
geom_diagonal2(aes(x, y, group = group, colour = colour)) # Use strength to control the steepness of the central region
ggplot(data, aes(x, y, xend = xend, yend = yend)) +
geom_diagonal(strength = 0.75, colour = 'red') +
geom_diagonal(strength = 0.25, colour = 'blue') 