stat_heatcircle: Compute circles with correlation-dependent size
In r-link/corrmorant: Flexible Correlation Matrices Based on 'ggplot2'

Description Usage Arguments Details Value See Also

stat_heatcircle() is used to compute bivariate correlations and display them in ggcorrm plots in form of circles whose color and size indicate correlation strength.

stat_heatcircle(
  mapping = NULL,
  data = NULL,
  geom = "ribbon",
  position = "identity",
  show.legend = NA,
  inherit.aes = TRUE,
  corr_method = NULL,
  rmin = 0.1,
  rmax = 0.9,
  scale_by = c("area", "radius"),
  ...
)

`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.
`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()`.
`corr_method`	character string with the correlation method passed to cor(). Can be one of `"pearson"`, `"kendall"` and `"spearman"`. Defaults to `"pearson"` (or is inherited from the setting in `ggcorrm()`).
`rmin`	numeric (0 - 1). Minimum radius for the "heat circles" (as a proportion of panel width). Defaults to 0.1.
`rmax`	numeric (0 - 1). Maximum radius for the "heat circles" (as a proportion of panel width). Defaults to 0.9.
`scale_by`	character. `scale_by = "area"` scales the area of the circles by correlation strength, `scale_by = "radius"` scales by radius. Defaults to "area".
`...`	additional arguments passed to `ggplot2::layer()`.

stat_heatcircle() computes the outlines of circles that are centered around the midpoint of gcorrm facets and whose radius or area is modified in dependence of correlation strength. rmin and rmax allow to modify the range in which the radii of the circles may vary. The circles are displayed using ggplot2::geom_ribbon().

An object of class Layer.

ggplot2::layer(), add_heatcircle()

r-link/corrmorant documentation built on Jan. 10, 2021, 7:26 p.m.