Add Fitted Vectors to Ordination plots — StatVectorfit • ggvegan

Fits arrows to show the direction of fastest increase in continuous environmental variables in ordination space.The arrows are scaled relative to their correlation coefficient, and they can be added to an ordination plot with geom_ordi_arrow().

stat_vectorfit(
  mapping = NULL,
  data = NULL,
  geom = "text",
  position = "identity",
  na.rm = FALSE,
  show.legend = FALSE,
  inherit.aes = TRUE,
  edata = NULL,
  formula = NULL,
  arrowmul = NULL,
  ...
)

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)).

geom

The geometric object to use to display the data for this layer. When using a stat_*() function to construct a layer, the geom argument can be used to override the default coupling between stats and geoms. The geom argument accepts the following:

A Geom ggproto subclass, for example GeomPoint.
A string naming the geom. To give the geom as a string, strip the function name of the geom_ prefix. For example, to use geom_point(), give the geom as "point".
For more information and other ways to specify the geom, see the layer geom 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.

na.rm

Remove missing values (Not Yet Implemented).

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().

edata

Environmental data where the continuous variables are found.

formula

Formula to select variables from edata. If missing, all continuos variables of edata are used.

arrowmul

Multiplier to arrow length. If missing, the multiplier is selected automatically so that arrows fit the current graph.

...

Other arguments passed to the functions.

Examples

library("vegan")
library("ggplot2")
data(mite, mite.env)
m <- metaMDS(mite, trace = FALSE, trymax = 100)

## add fitted vectors for continuous variables
ordiggplot(m) +
  geom_ordi_point("sites") +
  geom_ordi_arrow("sites", stat = "vectorfit", edata = mite.env)
#> Warning: The following aesthetics were dropped during statistical transformation:
#> SubsDens, WatrCont, Substrate, Shrub, and Topo.
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
#>   variable into a factor?
#> Warning: The following aesthetics were dropped during statistical transformation:
#> SubsDens, WatrCont, Substrate, Shrub, and Topo.
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
#>   variable into a factor?


## can be faceted
ordiggplot(m) + geom_ordi_point("sites") +
  geom_ordi_arrow("sites", stat = "vectorfit", edata = mite.env) +
  facet_wrap(mite.env$Topo)
#> Warning: The following aesthetics were dropped during statistical transformation:
#> SubsDens, WatrCont, Substrate, and Shrub.
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
#>   variable into a factor?
#> Warning: The following aesthetics were dropped during statistical transformation:
#> SubsDens, WatrCont, Substrate, and Shrub.
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
#>   variable into a factor?
#> Warning: The following aesthetics were dropped during statistical transformation:
#> SubsDens, WatrCont, Substrate, and Shrub.
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
#>   variable into a factor?
#> Warning: The following aesthetics were dropped during statistical transformation:
#> SubsDens, WatrCont, Substrate, and Shrub.
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
#>   variable into a factor?