geom_vector: Vectors from the origin
In corybrunson/ordr: A Tidyverse Extension for Ordinations and Biplots

geom_vector

R Documentation

Vectors from the origin

Description

geom_vector() renders arrows from the origin to points, optionally with text radiating outward.

Usage

geom_vector(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  arrow = default_arrow,
  lineend = "round",
  linejoin = "mitre",
  vector_labels = TRUE,
  ...,
  label.colour = NULL,
  label.color = NULL,
  label.alpha = NULL,
  parse = FALSE,
  check_overlap = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

`mapping`	Set of aesthetic mappings created by `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. When using a `⁠geom_*()⁠` function to construct a layer, the `stat` argument can be used the override the default coupling between geoms and stats. The `stat` argument accepts the following: A `Stat` ggproto subclass, for example `StatCount`. A string naming the stat. To give the stat as a string, strip the function name of the `stat_` prefix. For example, to use `stat_count()`, give the stat as `"count"`. For more information and other ways to specify the stat, see the layer stat documentation.
`position`	A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The `position` argument accepts the following: The result of calling a position function, such as `position_jitter()`. This method allows for passing extra arguments to the position. A string naming the position adjustment. To give the position as a string, strip the function name of the `position_` prefix. For example, to use `position_jitter()`, give the position as `"jitter"`. For more information and other ways to specify the position, see the layer position documentation.
`arrow`	Specification for arrows, as created by `grid::arrow()`, or else `NULL` for no arrows.
`lineend`	Line end style (round, butt, square).
`linejoin`	Line join style (round, mitre, bevel).
`vector_labels`	Logical; whether to include labels radiating outward from the vectors.
`...`	Additional arguments passed to `ggplot2::layer()`.
`label.colour`, `label.color`, `label.alpha`	Default aesthetics for labels. Set to NULL to inherit from the data's aesthetics.
`parse`	If `TRUE`, the labels will be parsed into expressions and displayed as described in `?plotmath`.
`check_overlap`	If `TRUE`, text that overlaps previous text in the same layer will not be plotted. `check_overlap` happens at draw time and in the order of the data. Therefore data should be arranged by the label column before calling `geom_text()`. Note that this argument is not supported by `geom_label()`.
`na.rm`	Passed to `ggplot2::layer()`.
`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

Vectors are positions relative to some common reference point, in this case the origin; they comprise direction and magnitude. Vectors are usually represented with arrows rather than markers (points).

Vectors are commonly used to represent numerical variables in biplots, as by Gabriel (1971) and Greenacre (2010). Gardner & le Roux (2002) refer to these as Gabriel biplots. This layer, with optional radiating text labels, is adapted from ggbiplot() in the off-CRAN extensions of the same name (Vu, 2014; Telford, 2017; Gegzna, 2018).

Value

A ggproto layer.

Biplot layers

ggbiplot() uses ggplot2::fortify() internally to produce a single data frame with a .matrix column distinguishing the subjects ("rows") and variables ("cols"). The stat layers stat_rows() and stat_cols() simply filter the data frame to one of these two.

The geom layers ⁠geom_rows_*()⁠ and ⁠geom_cols_*()⁠ call the corresponding stat in order to render plot elements for the corresponding factor matrix. ⁠geom_dims_*()⁠ selects a default matrix based on common practice, e.g. points for rows and arrows for columns.

Aesthetics

geom_vector() understands the following aesthetics (required aesthetics are in bold):

x
y
alpha
colour
linetype
label
size
angle
hjust
vjust
family
fontface
lineheight
group

References

Gabriel KR (1971) "The biplot graphic display of matrices with application to principal component analysis". Biometrika 58(3), 453–467. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1093/biomet/58.3.453")}

Greenacre MJ (2010) Biplots in Practice. Fundacion BBVA, ISBN: 978-84-923846. https://www.fbbva.es/microsite/multivariate-statistics/biplots.html

Gardner S, le Roux N (2002) "Biplot Methodology for Discriminant Analysis Based upon Robust Methods and Principal Curves". Classification, Clustering, and Data Analysis: Recent Advances and Applications: 169–176. https://link.springer.com/chapter/10.1007/978-3-642-56181-8_18

Vincent Q. Vu (2014). ggbiplot: A 'ggplot2' based biplot. R package version 0.55. https://github.com/vqv/ggbiplot, experimental branch

Richard J Telford (2017). ggbiplot: A 'ggplot2' based biplot. R package version 0.6. https://github.com/richardjtelford/ggbiplot (fork), experimental branch

Vilmantas Gegzna (2018). ggbiplot: A 'ggplot2' based biplot. R package version 0.55. https://github.com/forked-packages/ggbiplot (fork), experimental branch

Examples

# multidimensional scaling of covariances
ability.cov$cov |> 
  cov2cor() |>
  eigen() |> getElement("vectors") |> 
  as.data.frame() |> 
  transform(test = rownames(ability.cov$cov)) ->
  ability_cor_eigen
ability_cor_eigen |> 
  ggplot(aes(-V1, V2, label = test)) +
  coord_square() + theme_void() +
  geom_vector(check_overlap = TRUE) +
  scale_y_continuous(expand = expansion(mult = .2)) +
  ggtitle("Ability and intelligence test covariances")
# multidimensional scaling of correlations
ability.cov$cov |> 
  eigen() |> getElement("vectors") |> 
  as.data.frame() |> 
  transform(test = rownames(ability.cov$cov)) ->
  ability_cor_eigen
ability_cor_eigen |> 
  ggplot(aes(-V1, -V2, label = test)) +
  coord_square() + theme_void() +
  geom_vector(check_overlap = TRUE) +
  geom_unit_circle() +
  expand_limits(x = c(-1, 1), y = c(-1, 1)) +
  ggtitle("Ability and intelligence test covariances")

corybrunson/ordr documentation built on Feb. 24, 2025, 6:34 a.m.