A set of routines for plotting, highlighting points, or identifying the distribution of a third variable on an fso.
# S3 method for fso
plot(x, which="all", xlab = x$var, ylab="mu(x)",
title="",r=TRUE,pch=1,...)
# S3 method for fso
points(x, overlay, which="all", col=2, cex=1, pch=1, ...)
# S3 method for fso
plotid(ord, which="all", xlab=ord$var, ylab="mu(x)", title="",
r=TRUE, pch=1, labels=NULL, ...)
# S3 method for fso
hilight(ord, overlay, which=1, cols = c(2, 3, 4, 5,
6, 7), symbol = c(1, 3, 5), ...)
# S3 method for fso
chullord(ord, overlay, which = 1, cols = c(2, 3, 4, 5,
6, 7), ltys = c(1, 2, 3), ...)
# S3 method for fso
boxplot(x, ...)
an object of class ‘fso’
an object of class ‘fso’
a switch to control which axis is plotted
a switch to control printing the correlation coefficient in the plot
an object of class ‘fso’ from fso
a logical vector of the same length as the number of points in the plot
a vector of labels to print next to the identified points
an integer or vector of integers to control which symbols
are printed in which order on the plot by specifying values to
pch
an integer or vector of integers to control the line styles of convex hull polygons
text label for X axis
text label for Y axis
an overall title for the plot (equivalent to main)
the symbol for plotting
the color for plotted symbols
the character expansion factor (font size)
an integer vector specifying color order
arguments to pass to the underlying plot function
David W. Roberts droberts@montana.edu
Fuzzy set ordinations (FSO) are almost inherently graphical, and routines to facilitate plotting and overlaying are essential to work effectively with them.
A fuzzy set ordination object (an object of class ‘fso’) may contain one or more axes. In the simplest case, for a single-axis fso, the plot routine plots the underlying raw data on the X axis and the fuzzy set memberships on the Y axis, including by default the correlation coefficient in the upper left corner. For fsos containing multiple axes, the default (which="all") is to plot the raw data on the X axis, the respective fuzzy set memberships on the Y axis, plotting all axes in turn with a prompt to move to the next panel. This is often effective. It is also possible to plot a single panel out of the set of axes, specifying the axis as an integer with, e.g., "which = 2."
The ‘points’ function can be used to highlight or identify specific points in the plot. The ‘points’ function requires a logical vector (TRUE/FALSE) of the same length as the number of points in the plot. The default behavior is to color the points with a respective TRUE value red. It is possible to control the color (with col=), size (with cex=) and symbol (with pch=) of the points.
The ‘plotid’ function can be used to label or identify specific points with the mouse. Clicking the left mouse button adjacent to a point causes the point to be labeled, offset in the direction of the click relative to the point. Clicking the right mouse button exits the routine. The default (labels=NULL) is to label points with the row number in the data.frame (or position in the vector) for the point. Alternatively, specifying a vector of labels (labels=) prints the respective labels. If the data were derived from a data.frame, the row.names of the data.frame are often a good choice, but the labels can also be used with a factor vector to identify the distribution of values of a factor in the ordination (but see hilight as well).
The ‘hilight’ function identifies the factor values of points in the ordination, using color and symbols to identify unique values (up to 18 values by default). The colors and symbols used can be specified by the ‘cols=’ and ‘symbol=’ arguments, which should both be integers or integer vectors. The default of colors 2, 3, 4, 5, 6, 7 and symbols 1, 3, 5 shows well in most cases, but on colored backgrounds you may need to adjust ‘cols=’. If you have a factor with more than 18 classes you will need to augment the ‘symbol=’ vector with more values.
The ‘chullord’ function plots convex hulls around all points sharing the same value for a factor variable, and colors all points of that value to match. The convention on colors follows ‘hilight’.
The ‘boxplot’ function plots boxplots of the \(\mu\) membership values for the fuzzy sets in the fso.
require(labdsv) # to obtain access to data sets and dissimilarity function
data(bryceveg) # vegetation data
data(brycesite) # environmental data
dis.bc <- dsvdis(bryceveg,'bray/curtis') # produce \sQuote{dist} object
demo.fso <- fso(~elev+slope+av,dis.bc,data=brycesite)
if (FALSE) plot(demo.fso)
if (FALSE) hilight(demo.mfso,brycesite$quad)
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