ordixyplot: Trellis (Lattice) Plots for Ordination

Description

Functions ordicloud, ordisplom and ordixyplot provide an interface to plot ordination results using Trellis functions cloud, splom and xyplot in package lattice.

Usage

ordixyplot(x, data = NULL, formula, display = "sites", choices = 1:3,
    panel = "panel.ordi", aspect = "iso", envfit,
    type = c("p", "biplot"), ...)
ordisplom(x, data=NULL, formula = NULL,  display = "sites", choices = 1:3,
    panel = "panel.ordi", type = "p",  ...)
ordicloud(x, data = NULL, formula, display = "sites", choices = 1:3, 
    panel = "panel.ordi3d", prepanel = "prepanel.ordi3d",  ...)

Arguments

An ordination result that scores knows: any ordination result in vegan and many others.

data

Optional data to amend ordination results. The ordination results are found from x, but you may give here data for other variables needed in plots. Typically these are environmental data.

formula

Formula to define the plots. A default formula will be used if this is omitted. The ordination axes must be called by the same names as in the ordination results (and these names vary among methods). In ordisplom, special char

display

The kind of scores: an argument passed to scores.

choices

The axes selected: an argument passed to scores.

panel, prepanel

The names of the panel and prepanel functions.

aspect

The aspect of the plot (passed to the lattice function).

envfit

Result of envfit function displayed in ordixyplot. Please note that this needs same choices as ordixyplot.

type

The type of plot. This knows the same alternatives as panel.xyplot. In addition ordixyplot has alternatives "biplot" and "arrows". The first di

...

Arguments passed to scores methods or lattice functions.

Value

The function return Lattice objects of class "trellis".

Details

The functions provide an interface to the corresponding lattice functions. All graphical parameters are passed to the lattice function so that these graphs are extremely configurable. See Lattice and xyplot, splom and cloud for details, usage and possibilities.

The argument x must always be an ordination result. The scores are extracted with vegan function scores so that these functions work with all vegan ordinations and many others.

The formula is used to define the models. All functions have simple default formulae which are used if formula is missing. If formula is omitted in ordisplom it produces a pairs plot of ordination axes and variables in data. If formula is given, ordination results must be referred to as . and other variables by their names. In other functions, the formula must use the names of ordination scores and names of data.

The ordination scores are found from x, and data is optional. The data should contain other variables than ordination scores to be used in plots. Typically, they are environmental variables (typically factors) to define panels or plot symbols.

The proper work is done by the panel function. The layout can be changed by defining own panel functions. See panel.xyplot, panel.splom and panel.cloud for details and survey of possibilities.

Ordination graphics should always be isometric: same scale should be used in all axes. This is controlled (and can be changed) with argument aspect in ordixyplot. In ordicloud the isometric scaling is defined in panel and prepanel functions. You must replace these functions if you want to have non-isometric scaling of graphs. You cannot select isometric scaling in ordisplom.

Examples

Run this code

data(dune)
data(dune.env)
ord <- cca(dune)
## Pairs plots
ordisplom(ord)
ordisplom(ord, data=dune.env, choices=1:2)
ordisplom(ord, data=dune.env, form = ~ . | Management, groups=Manure)
## Scatter plot
ordixyplot(ord, data=dune.env, form = CA1 ~ CA2 | Management,
  groups=Manure)
## Choose a different scaling
ordixyplot(ord, scaling = 3)
## ... Slices of third axis
ordixyplot(ord, form = CA1 ~ CA2 | equal.count(CA3, 4), type = c("g","p"))
## Display environemntal variables
ordixyplot(ord, envfit = envfit(ord ~ Management + A1, dune.env, choices=1:3))
## 3D Scatter plots
ordicloud(ord, form = CA2 ~ CA3*CA1, groups = Manure, data = dune.env)
ordicloud(ord, form = CA2 ~ CA3*CA1 | Management, groups = Manure,
   data = dune.env, auto.key = TRUE, type = c("p","h"))

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