geom_quasirandom: Quasirandom points
In csdaw/ggbeeswarm2: Categorical Scatter (Violin Point) Plots

View source: R/geom-quasirandom.R

geom_quasirandom

R Documentation

Quasirandom points

Description

The quasirandom geom is a convenient shortcut for geom_point(position = "quasirandom"). It shifts points to avoid overplotting using the offsetSingleGroup function from the vipor package.

Usage

geom_quasirandom(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  ...,
  method = "quasirandom",
  width = NULL,
  varwidth = FALSE,
  bandwidth = 0.5,
  nbins = NULL,
  dodge.width = NULL,
  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), 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.
`...`	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.
`method`	`string`. Method for arranging points, default is `"quasirandom"`. See details below.
`width`	`numeric`. Maximum spacing away from the centre for each group of points, default is `1`.
`varwidth`	`boolean`. Adjust the width of each group based on the number of points in the group. Default is `FALSE`.
`bandwidth`	`numeric`. Specifies the bandwidth used to calculate the kernel density, default is `1`. Smaller values = tighter fit. larger values = looser fit.
`nbins`	`integer` The number of points used to calculate density (default is `1000` for quasirandom and pseudorandom, and 100 for others).
`dodge.width`	`numeric`. Amount to dodge points from different aesthetic groups, default is `NULL` for no dodging.
`na.rm`	If `FALSE`, the default, missing values are removed with a warning. If `TRUE`, missing values are silently removed.
`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()`.

Details

method: specifies the algorithm used to distribute the points.

"quasirandom": points are distributed within a kernel density estimate of the distribution with offset determined by quasirandom Van de Corput noise.

"pseudorandom": points are distributed within a kernel density estimate of the distribution with offset determined by pseudorandom noise a la jitter.

"maxout": points are distributed within a kernel density with points in a band distributed with highest value points on the outside and lowest in the middle.

"minout": points are distributed within a kernel density with points in a band distributed with highest value points in the middle and lowest on the outside.

"tukey": points are distributed as described in Tukey and Tukey, "Strips displaying empirical distributions: I. textured dot strips".

"tukeyDense": points are distributed as described in Tukey and Tukey but are constrained with the kernel density estimate.