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", ...)
scores
knows: any
ordination result in vegan and many others. x
, but you may give here data for other
variables needed in plots. Typically these are environmental data.ordisplom
, special character .
refers to the
ordination result. scores
. scores
. envfit
function displayed in
ordixyplot
. Please note that this needs same choices
as ordixyplot
.panel.xyplot
. In addition ordixyplot
has alternatives "biplot"
and "arrows"
. 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
.scores
methods or
lattice functions.Lattice
objects of class
"trellis"
.
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
.
Lattice
,
xyplot
,
splom
,
cloud
,
panel.splom
,
panel.cloud
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 = "symmetric")
## ... 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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