ggplot-based plot for objects of class "metaMDS"

Produces a multi-layer ggplot object representing the output of objects produced by metaMDS.

# S3 method for class 'metaMDS'
autoplot(
  object,
  axes = c(1, 2),
  geom = c("point", "text"),
  layers = c("species", "sites"),
  legend.position = "right",
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  ylab,
  xlab,
  ...
)

Arguments

object: an object of class "metaMDS", the result of a call to metaMDS.
axes: numeric; which axes to plot, given as a vector of length 2.
geom: character; which geoms to use for the layers. Can be a vector of length equal to length(display), in which case the ith element of type refers to the ith element of display.
layers: character; which scores to plot as layers
legend.position: character or two-element numeric vector; where to position the legend. See theme for details. Use "none" to not draw the legend.
title: character; subtitle for the plot
subtitle: character; subtitle for the plot
caption: character; caption for the plot
ylab: character; label for the y-axis
xlab: character; label for the x-axis
...: Additional arguments passed to fortify.metaMDS.

Value

Returns a ggplot object.

Details

TODO

Author

Gavin L. Simpson

Examples

## load example data
data(dune)

sol <- metaMDS(dune)
#> Run 0 stress 0.1192678 
#> Run 1 stress 0.1192678 
#> ... New best solution
#> ... Procrustes: rmse 5.475398e-06  max resid 1.631124e-05 
#> ... Similar to previous best
#> Run 2 stress 0.1192679 
#> ... Procrustes: rmse 9.156903e-05  max resid 0.0002801513 
#> ... Similar to previous best
#> Run 3 stress 0.1183186 
#> ... New best solution
#> ... Procrustes: rmse 0.02027291  max resid 0.06497703 
#> Run 4 stress 0.1192678 
#> Run 5 stress 0.1183186 
#> ... Procrustes: rmse 1.154542e-06  max resid 2.883052e-06 
#> ... Similar to previous best
#> Run 6 stress 0.1192678 
#> Run 7 stress 0.1192678 
#> Run 8 stress 0.1183186 
#> ... New best solution
#> ... Procrustes: rmse 2.730997e-06  max resid 8.755205e-06 
#> ... Similar to previous best
#> Run 9 stress 0.2045511 
#> Run 10 stress 0.1183186 
#> ... Procrustes: rmse 2.864314e-06  max resid 6.507562e-06 
#> ... Similar to previous best
#> Run 11 stress 0.1192679 
#> Run 12 stress 0.1183186 
#> ... Procrustes: rmse 4.75061e-06  max resid 1.483607e-05 
#> ... Similar to previous best
#> Run 13 stress 0.1183186 
#> ... Procrustes: rmse 1.209316e-05  max resid 3.823555e-05 
#> ... Similar to previous best
#> Run 14 stress 0.1183186 
#> ... New best solution
#> ... Procrustes: rmse 5.606702e-06  max resid 1.793249e-05 
#> ... Similar to previous best
#> Run 15 stress 0.1192678 
#> Run 16 stress 0.1812933 
#> Run 17 stress 0.1183186 
#> ... New best solution
#> ... Procrustes: rmse 1.13932e-06  max resid 2.133106e-06 
#> ... Similar to previous best
#> Run 18 stress 0.1192678 
#> Run 19 stress 0.1192679 
#> Run 20 stress 0.1192679 
#> *** Best solution repeated 1 times
autoplot(sol)