ggforce (version 0.4.1)

geom_bspline: 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 grid::xsplineGrob() with shape = 1 to approximate a b-spline.

Usage

stat_bspline(
  mapping = NULL,
  data = NULL,
  geom = "path",
  position = "identity",
  na.rm = FALSE,
  n = 100,
  type = "clamped",
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)
geom_bspline(
  mapping = NULL,
  data = NULL,
  stat = "bspline",
  position = "identity",
  arrow = NULL,
  n = 100,
  type = "clamped",
  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,
  type = "clamped",
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)
geom_bspline2(
  mapping = NULL,
  data = NULL,
  stat = "bspline2",
  position = "identity",
  arrow = NULL,
  n = 100,
  type = "clamped",
  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,
  type = "clamped",
  ...
)
geom_bspline0(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  arrow = NULL,
  lineend = "butt",
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  type = "clamped",
  ...
)

Arguments

mapping

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.

data

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)).

geom

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")

position

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.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

n

The number of points generated for each spline

type

Either 'clamped' (default) or 'open'. The former creates a knot sequence that ensures the splines starts and ends at the terminal control points.

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. It can also be a named logical vector to finely select the aesthetics to display.

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(). 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.

stat

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")

arrow

Arrow specification, as created by grid::arrow().

lineend

Line end style (round, butt, square).

Aesthetics

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

• x

• y

• color

• linewidth

• linetype

• alpha

• lineend

Computed variables

x, y

The coordinates for the path describing the spline

index

The progression along the interpolation mapped between 0 and 1

Author

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

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

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

ggplot(paths) +
  geom_bspline0(aes(x = x, y = y, group = group)) +
  geom_point(aes(x = x, y = y), data = cp, color = 'steelblue')