R: B-splines based on control points

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):

- x

- y

- color

- size

- 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(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 0.1.2 Index]