cca), redundancy analysis (rda) or
constrained analysis of principal coordinates (capscale).## S3 method for class 'cca':
plot(x, choices = c(1, 2), display = c("sp", "wa", "cn"),
scaling = 2, type, ...)
## S3 method for class 'cca':
text(x, display = "sites", choices = c(1, 2), scaling = 2,
mul.arrow = 1, head.arrow = 0.05, ...)
## S3 method for class 'cca':
points(x, display = "sites", choices = c(1, 2), scaling = 2,
mul.arrow = 1, head.arrow = 0.05, ...)
## S3 method for class 'cca':
scores(x, choices=c(1,2), display=c("sp","wa","cn"),scaling=2, ...)cca result object.sp for species scores, wa for site scores, lc
for linear constraints or ``LC scores'', or bp for biplot
arrows or cn for centrotext
for text labels, points for points, and none for
setting frames only. If omitted, text is selected for
smaller data sets, and points for larg2) or site (1) scores are scaled by eigenvalues, and
the other set of scores is left unscaled, or with 3 both are
scaled symmetrically by square root oplot function returns invisibly a plotting structure which
can be used by function identify.ordiplot to identify
the points or other functions in the ordiplot family.plot function will be used for cca and
rda. This produces a quick, standard plot with current
scaling. The plot function sets colours (col), plotting
characters (pch) and character sizes (cex) to
certain standard values. For a fuller control of produced plot, it is
best to call plot with type="none" first, and then add
each plotting item separately using text.cca or
points.cca functions. These use the default settings of standard
text and points functions and accept all
their parameters, allowing thus a full user control of produced plots.
Environmental variables receive a special treatment. With
display="bp", arrows will be drawn. These are labelled with
text and unlabelled with points. The basic plot
function uses a simple (but not very clever) heuristics for adjusting
arrow lengths to plots, but with points.cca and text.cca
the user must give the expansion factor in
mul.arrow. The behaviour is still more peculiar with
display="cn" which requests centroids of levels of
factor variables (these are available only if there were
factors and a formula interface was used in cca or
rda). With this option, biplot arrows are plotted in
addition to centroids in cases which do not have a centroid: Continuous
variables are presented with arrows and ordered factors with arrows
and centroids.
If you want to have still a better control of plots, it is better to
produce them using primitive plot commands.. Function
scores helps in extracting the
needed components with the selected scaling.
cca, rda and capscale
for getting something
to plot, ordiplot for an alternative plotting routine
and more support functions, and text,
points and arrows for the basic routines.data(dune)
data(dune.env)
mod <- cca(dune ~ A1 + Moisture + Management, dune.env)
plot(mod, type="n")
text(mod, dis="cn", mul=2)
points(mod, pch=21, col="red", bg="yellow", cex=1.2)
text(mod, "species", col="blue", cex=0.8)Run the code above in your browser using DataLab