R: Voronoi tesselation and delaunay triangulation

geom_voronoi {ggforce} | R Documentation

## Voronoi tesselation and delaunay triangulation

### Description

This set of geoms and stats allows you to display voronoi tesselation and delaunay triangulation, both as polygons and as line segments. Furthermore it lets you augment your point data with related summary statistics. The computations are based on the `deldir::deldir()` package.

### Usage

    geom_voronoi_tile(
      mapping = NULL,
      data = NULL,
      stat = "voronoi_tile",
      position = "identity",
      na.rm = FALSE,
      bound = NULL,
      eps = 1e-09,
      max.radius = NULL,
      normalize = FALSE,
      asp.ratio = 1,
      expand = 0,
      radius = 0,
      show.legend = NA,
      inherit.aes = TRUE,
      ...
    )

    geom_voronoi_segment(
      mapping = NULL,
      data = NULL,
      stat = "voronoi_segment",
      position = "identity",
      na.rm = FALSE,
      bound = NULL,
      eps = 1e-09,
      normalize = FALSE,
      asp.ratio = 1,
      show.legend = NA,
      inherit.aes = TRUE,
      ...
    )

    geom_delaunay_tile(
      mapping = NULL,
      data = NULL,
      stat = "delaunay_tile",
      position = "identity",
      na.rm = FALSE,
      bound = NULL,
      eps = 1e-09,
      normalize = FALSE,
      asp.ratio = 1,
      expand = 0,
      radius = 0,
      show.legend = NA,
      inherit.aes = TRUE,
      ...
    )

    geom_delaunay_segment(
      mapping = NULL,
      data = NULL,
      stat = "delaunay_segment",
      position = "identity",
      na.rm = FALSE,
      bound = NULL,
      eps = 1e-09,
      normalize = FALSE,
      asp.ratio = 1,
      show.legend = NA,
      inherit.aes = TRUE,
      ...
    )

    geom_delaunay_segment2(
      mapping = NULL,
      data = NULL,
      stat = "delaunay_segment2",
      position = "identity",
      na.rm = FALSE,
      bound = NULL,
      eps = 1e-09,
      normalize = FALSE,
      asp.ratio = 1,
      n = 100,
      show.legend = NA,
      inherit.aes = TRUE,
      ...
    )

    stat_delvor_summary(
      mapping = NULL,
      data = NULL,
      geom = "point",
      position = "identity",
      na.rm = FALSE,
      bound = NULL,
      eps = 1e-09,
      normalize = FALSE,
      asp.ratio = asp.ratio,
      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), 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)`).
`stat` | The statistical transformation to use on the data for this layer, as a string.
`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.
`bound` | The bounding rectangle for the tesselation or a custom polygon to clip the tesselation to. Defaults to `NULL` which creates a rectangle expanded 10\ vector giving the bounds in the following order: xmin, xmax, ymin, ymax. If supplied as a polygon it should either be a 2-column matrix or a data.frame containing an `x` and `y` column.
`eps` | A value of epsilon used in testing whether a quantity is zero, mainly in the context of whether points are collinear. If anomalous errors arise, it is possible that these may averted by adjusting the value of eps upward or downward.
`max.radius` | The maximum distance a tile can extend from the point of origin. Will in effect clip each tile to a circle centered at the point with the given radius. If `normalize = TRUE` the radius will be given relative to the normalized values
`normalize` | Should coordinates be normalized prior to calculations. If `x` and `y` are in wildly different ranges it can lead to tesselation and triangulation that seems off when plotted without `ggplot2::coord_fixed()`. Normalization of coordinates solves this. The coordinates are transformed back after calculations.
`asp.ratio` | If `normalize = TRUE` the x values will be multiplied by this amount after normalization.
`expand` | A numeric or unit vector of length one, specifying the expansion amount. Negative values will result in contraction instead. If the value is given as a numeric it will be understood as a proportion of the plot area width.
`radius` | As `expand` but specifying the corner radius.
`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.
`n` | The number of points to create for each segment
`geom` | The geometric object to use display the data

### Aesthetics

geom_voronoi_tile and geom_delaunay_tile understand the following aesthetics (required aesthetics are in bold):

- x

- y

- alpha

- color

- fill

- linetype

- size

geom_voronoi_segment, geom_delaunay_segment, and geom_delaunay_segment2 understand the following aesthetics (required aesthetics are in bold):

- x

- y

- alpha

- color

- linetype

- size

### Computed variables

stat_delvor_summary computes the following variables:

x, y

  If `switch.centroid = TRUE` this will be the coordinates for the voronoi tile centroid, otherwise it is the original point

xcent, ycent

  If `switch.centroid = FALSE` this will be the coordinates for the voronoi tile centroid, otherwise it will be `NULL`

xorig, yorig

  If `switch.centroid = TRUE` this will be the coordinates for the original point, otherwise it will be `NULL`

ntri

  Number of triangles emanating from the point

triarea

  The total area of triangles emanating from the point divided by 3

triprop

  `triarea` divided by the sum of the area of all triangles

nsides

  Number of sides on the voronoi tile associated with the point

nedges

  Number of sides of the associated voronoi tile that is part of the bounding box

vorarea

  The area of the voronoi tile associated with the point

vorprop

  `vorarea` divided by the sum of all voronoi tiles

### Examples

    # Voronoi
    # You usually wants all points to take part in the same tesselation so set
    # the group aesthetic to a constant (-1L is just a convention)
    ggplot(iris, aes(Sepal.Length, Sepal.Width, group = -1L)) +
      geom_voronoi_tile(aes(fill = Species)) +
      geom_voronoi_segment() +
      geom_text(aes(label = stat(nsides), size = stat(vorarea)),
        stat = 'delvor_summary', switch.centroid = TRUE
      )

    # Difference of normalize = TRUE (segment layer is calculated without
    # normalisation)
    ggplot(iris, aes(Sepal.Length, Sepal.Width, group = -1L)) +
      geom_voronoi_tile(aes(fill = Species), normalize = TRUE) +
      geom_voronoi_segment()

    # Set a max radius
    ggplot(iris, aes(Sepal.Length, Sepal.Width, group = -1L)) +
      geom_voronoi_tile(aes(fill = Species), colour = 'black', max.radius = 0.25)

    # Set custom bounding polygon
    triangle <- cbind(c(3, 9, 6), c(1, 1, 6))
    ggplot(iris, aes(Sepal.Length, Sepal.Width, group = -1L)) +
      geom_voronoi_tile(aes(fill = Species), colour = 'black', bound = triangle)

    # Use geom_shape functionality to round corners etc
    ggplot(iris, aes(Sepal.Length, Sepal.Width, group = -1L)) +
      geom_voronoi_tile(aes(fill = Species), colour = 'black',
                        expand = unit(-.5, 'mm'), radius = unit(2, 'mm'))

    # Delaunay triangles
    ggplot(iris, aes(Sepal.Length, Sepal.Width)) +
      geom_delaunay_tile(alpha = 0.3, colour = 'black')

    # Use geom_delauney_segment2 to interpolate aestetics between end points
    ggplot(iris, aes(Sepal.Length, Sepal.Width)) +
      geom_delaunay_segment2(aes(colour = Species, group = -1), size = 2,
                             lineend = 'round')

[Package ggforce version 0.3.2 Index]