Usage
shardsplot(object, plot.type = c("eight", "four", "points", "n"),
expand = 1, stck = TRUE, grd = FALSE, standardize = FALSE,
data.or = NA, label = FALSE, plot = TRUE, classes = 0,
vertices = TRUE, classcolors = "rainbow", wghts = 0,
xlab = "Dimension 1", ylab = "Dimension 2", xaxs = "i",
yaxs = "i", plot.data.column = NA,
log.classes = FALSE, revert.colors = FALSE, ...)
level_shardsplot(object, par.names, rows = 1:NCOL(object$data),
centers = rep(NA, length(par.names)), class.labels = NA,
revert.colors = rep(FALSE, length(par.names)),
log.classes = rep(FALSE, length(par.names)),
centeredcolors = colorRamp(c("red", "white", "blue")),
mfrow = c(2, 2), plot.type = c("eight", "four", "points", "n"),
expand = 1, stck = TRUE, grd = FALSE, standardize = FALSE,
label = FALSE, plot = TRUE, vertices = TRUE, classcolors = "topo",
wghts = 0, xlab = "Dimension 1", ylab = "Dimension 2",
xaxs = "i", yaxs = "i", ...)
## S3 method for class 'EDAM':
plot(...)
Arguments
object
an object of class EDAM
or som
.
par.names
names used to lable the data columns
rows
vector with indices of colomns to be plotted
centers
vector of type numeric defining the class centers for the data. NA if data does not have a center.
class.labels
matrix of type text and dimension(3, NROW(object$data))
defining the lables to be used for maximum, minimum and central value.
centeredcolors
colors to represent the classes with a central value
mfrow
parameter defining number of plots on a page. see par
plot.type
a character giving the shape of the shards.
Available are eight
and four
for octagons resp. rectangles,
and points
for points. If plot.type
expand
a numeric giving the relative expansion of the axes.
A value greater than one implies smaller shards. Varying expand
can be sensible for visual reasons.
stck
logical. If TRUE
the cells are varied continously corresponding to
the differences of direct neighbors in the origin space.
Within this variation the relative order of the cells is always preserved.
grd
logical. If TRUE
(which automatically sets stck
to TRUE
),
the variation of cells is restricted to their original discrete values.
standardize
logical. If TRUE
, then the measurements in object$preimages
are standardized before calculating Euclidean distances.
Measurements are standardized for each variable by dividing by the variable's
standard
data.or
original data and classes where the first k columns are variables and the (k+1)-th column are the classes.
If defined and class of object
is som
, data.or
is used to assign a class to each codebook. There
a
label
logical. If TRUE
, the shards are labeled by the rownames of the preimages.
plot
logical. If FALSE
, all graphical output is suppressed.
classes
a vector giving alternative classes for objects of class EDAM
; classes
have to be given in
the original order of the data to which EDAM
was applied. vertices
logical. If TRUE
the grid is drawn.
classcolors
colors to represent the classes, or a character giving the colorscale for the classes.
Since now available scales are rainbow
, topo
and gray
.
wghts
an optional vector of length k giving relative weights of the variables
in computing Euclidean distances. Meaningless if object$preimages
is a dissimilarity matrix.
...
further plotting parameters.
plot.data.column
column index defining from data.or
providing the data used to calculate the coloring of the cells.
log.classes
boolean indicating that the data should be transformed with the logarithmic function before calculating the cell coloring
revert.colors
boolean indicating that the colorscale should be reverted.