Membership plots are a graphical visualization of cross-membership of
many individuals in many categories. Although Venn diagrams work well
for this purpose when there are three or four categories, they can be
difficiult to interpet, or even impossible to draw, with more
categories. In this case, membership plots are more useful.
Usage
memberPlot(bindat, features = NULL, pal = NULL, xlab = "Members",
ylab = "Categories", ...)
Value
The transformed input matrix is returned invisibly. The main purpose
of the function is teh "side-effect" or producing a plot.
Arguments
bindat
A binary matrix where rows are categories, columns are
members, 1 debnotes membership and 0 denotes nonmembership. Muissing
data is not permitted.
pal
A character vector of colors. The first color is used for
non-members; all other colors are used to denote different categories.
features
A numeric vector listing the number of features
measured in each membership data set.
xlab
The usual graphical parameter.
ylab
The usual graphical parameter.
...
Additional plot parameters, especially "main" or "sub".
Author
Kevin R. Coombes <krc@silicovore.com>
Details
Membership plots are implemented as an image, where each row
represents a different category and is shown in a different
color. Non-membership is indicated by the same color regardless fo
category; by dafault, we use "gray" for non-members. The data are
sorted so that the number of members per category decreases from the
bottom tot he top of the plot. They are also sorted so that membership
in larger categories is prioritized from left to right.