geom_bspline {ggforce}R Documentation

B-splines based on control points

Description

This set of stats and geoms makes it possible to draw b-splines based on a set of control points. As with geom_bezier there exists several versions each having there own strengths. The base version calculates the b-spline as a number of points along the spline and connects these with a path. The *2 version does the same but in addition interpolates aesthetics between each control point. This makes the *2 version considerably slower so it shouldn't be used unless needed. The *0 version uses xsplineGrob with shape = 1 to approximate a b-spline for a high performant version.

Usage

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

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

stat_bspline2(mapping = NULL, data = NULL, geom = "path_interpolate",
  position = "identity", na.rm = FALSE, n = 100, show.legend = NA,
  inherit.aes = TRUE, ...)

geom_bspline2(mapping = NULL, data = NULL, stat = "bspline2",
  position = "identity", arrow = NULL, n = 100, lineend = "butt",
  na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, ...)

stat_bspline0(mapping = NULL, data = NULL, geom = "bspline0",
  position = "identity", na.rm = FALSE, show.legend = NA,
  inherit.aes = TRUE, ...)

geom_bspline0(mapping = NULL, data = NULL, stat = "identity",
  position = "identity", arrow = NULL, lineend = "butt", na.rm = FALSE,
  show.legend = NA, inherit.aes = TRUE, ...)

Arguments

mapping

Set of aesthetic mappings created by aes or aes_. If specified and inherit.aes = TRUE (the default), is combined with the default mapping at the top level of the plot. You only need to supply mapping if there isn't a mapping defined for the plot.

data

A data frame. If specified, overrides the default data frame defined at the top level of the plot.

geom,

stat Override the default connection between geom_arc and stat_arc.

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

na.rm

If FALSE (the default), removes missing values with a warning. If TRUE silently removes missing values.

n

The number of points generated for each spline

show.legend

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.

inherit.aes

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. There are three types of arguments you can use here:

  • Aesthetics: to set an aesthetic to a fixed value, like color = "red" or size = 3.

  • Other arguments to the layer, for example you override the default stat associated with the layer.

  • Other arguments passed on to the stat.

stat

The statistical transformation to use on the data for this layer, as a string.

arrow

specification for arrow heads, as created by arrow()

lineend

Line end style (round, butt, square)

Aesthetics

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

Computed variables

x, y

The coordinates for the path describing the spline

index

The progression along the interpolation mapped between 0 and 1

Author(s)

Thomas Lin Pedersen. The C++ code for De Boor's algorithm has been adapted from Jason Yu-Tseh Chi implementation

References

Holten, D. (2006). Hierarchical edge bundles: visualization of adjacency relations in hierarchical data. IEEE Transactions on Visualization and Computer Graphics, 12(5), 741-748. http://doi.org/10.1109/TVCG.2006.147

Examples

# Define some control points
cp <- data.frame(
  x = c(0, -5, -5, 5, 5, 2.5, 5, 7.5, 5, 2.5, 5, 7.5, 5, -2.5, -5, -7.5, -5,
        -2.5, -5, -7.5, -5),
  y = c(0, -5, 5, -5, 5, 5, 7.5, 5, 2.5, -5, -7.5, -5, -2.5, 5, 7.5, 5, 2.5,
        -5, -7.5, -5, -2.5),
  class = sample(letters[1:3], 21, replace = TRUE)
)

# Now create some paths between them
paths <- data.frame(
  ind = c(7,5,8,8,5,9,9,5,6,6,5,7,7,5,1,3,15,8,5,1,3,17,9,5,1,2,19,6,5,1,4,
          12,7,5,1,4,10,6,5,1,2,20),
  group = c(1,1,1,2,2,2,3,3,3,4,4,4,5,5,5,5,5,6,6,6,6,6,7,7,7,7,7,8,8,8,8,8,
            9,9,9,9,9,10,10,10,10,10)
)
paths$x <- cp$x[paths$ind]
paths$y <- cp$y[paths$ind]
paths$class <- cp$class[paths$ind]

ggplot() +
  geom_bspline(aes(x=x, y=y, group=group, colour = ..index..), data=paths) +
  geom_point(aes(x=x, y=y), data=cp, color='steelblue')

ggplot() +
  geom_bspline2(aes(x=x, y=y, group=group, colour = class), data=paths) +
  geom_point(aes(x=x, y=y), data=cp, color='steelblue')

ggplot() +
  geom_bspline0(aes(x=x, y=y, group=group), data=paths) +
  geom_point(aes(x=x, y=y), data=cp, color='steelblue')
[Package ggforce version 0.1.1 Index]