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 `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()` 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.
`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 display the data
`position` | Position adjustment, either as a string, or the result of a call to a position adjustment function.
`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, as a string.
`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

- 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

### 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 = ..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')

[Package ggforce version 0.3.2 Index]