Functions ordicloud, ordisplom and ordixyplot
provide an interface to plot ordination results using Trellis
functions cloud, splom
and xyplot in package lattice.
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", ...)The function return Lattice objects of class
"trellis".
An ordination result that scores knows: any
ordination result in vegan and many others.
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 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 character . refers to the
ordination result.
The kind of scores: an argument passed to
scores.
The axes selected: an argument passed to
scores.
The names of the panel and prepanel functions.
The aspect of the plot (passed to the lattice function).
Result of envfit function displayed in
ordixyplot. Please note that this needs same choices
as ordixyplot.
The type of plot. This knows the same alternatives as
panel.xyplot. In addition ordixyplot
has alternatives "biplot", "arrows" and
"polygon". The first displays fitted vectors and factor
centroids of envfit, or in constrained ordination, the
biplot arrows and factor centroids if envfit is not
given. The second (type = "arrows") is a trellis variant of
ordiarrows and draws arrows by groups. The
line parameters are controlled by
trellis.par.set for superpose.line,
and the user can set length, angle and ends
parameters of panel.arrows. The last one
(type = "polygon") draws a polygon enclosing all points in
a panel over a polygon enclosing all points in the data. The
overall polygon is controlled by
trellis.par.set for plot.polygon,
and each panel polygon is controlled by superpose.polygon.
Arguments passed to scores methods or
lattice functions.
Jari Oksanen
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.
data(dune, 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 with polygons
ordixyplot(ord, data=dune.env, form = CA1 ~ CA2 | Management,
groups=Manure, type = c("p","polygon"))
## Choose a different scaling
ordixyplot(ord, scaling = "symmetric")
## ... Slices of third axis
ordixyplot(ord, form = CA1 ~ CA2 | equal.count(CA3, 4),
type = c("g","p", "polygon"))
## Display environmental 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"))
Run the code above in your browser using DataLab