labdsv (version 1.3-1)

plot.nmds: Plotting Routines For Nonmetric Multi-dimensional Scaling Ordinations

Description

A set of routines for plotting, highlighting points, or adding fitted surfaces to NMDSs.

Usage

## S3 method for class 'nmds':
plot(x, ax = 1, ay = 2, col = 1, title = "", pch = 1, \dots)
## S3 method for class 'nmds':
points(x, which, ax = 1, ay = 2, col = 2, pch = 1, cex = 1, breaks=FALSE, \dots)
## S3 method for class 'nmds':
plotid(ord, ids = seq(1:nrow(ord$points)), ax = 1, ay = 2,
    col = 1, ...)
## S3 method for class 'nmds':
hilight(ord, overlay, ax = 1, ay = 2, cols=c(2,3,4,5,6,7), glyph=c(1,3,5),
    origpch = 1, blank = '#FFFFFF', ...)
## S3 method for class 'nmds':
chullord(ord, overlay, ax = 1, ay = 2, cols=c(2,3,4,5,6,7), ltys = c(1,2,3), ...)
## S3 method for class 'nmds':
surf(ord, var, ax = 1, ay = 2, thinplate = TRUE, col = 2, labcex = 0.8,
    family = gaussian, gamma=1, grid=50, \dots)
## S3 method for class 'nmds':
density(ord, overlay, ax = 1, ay = 2, cols = c(2, 3, 4, 5,
    6, 7), ltys = c(1, 2, 3), niter, ...)

Arguments

x

an object of class nmds

ax

the dimension to use for the X axis

ay

the dimension to use for the Y axis

title

a title for the plot

which

a logical variable to specify points to be highlighted

breaks

a logical switch to control using variable glyph sizes in points

ord

an object of class nmds

overlay

a factor or integer vector to hilight or distinguish

cols

the sequence of color indices to be used

glyph

the sequence of glyphs (pch) to be used

origpch

the pch number of the glyph employed in the original plot (to be obliterated by blank)

blank

the color to use to erase the glyphs of the original plot

ltys

the sequence of line types to be used

var

a variable to be surfaced

thinplate

a logical variable to control the fitting routine: thinplate = TRUE (the default) fits a thinplate spline, thinplate = FALSE fits independent smooth splines

family

controls the link function passed to gam: one of gaussian, binomial, or poisson

gamma

controls the smoothness of the fit from gam

grid

the number of X and Y values to use in establishing a grid for use in surf

ids

identifier labels for samples. Defaults to 1:n

col

color index for points or contours

labcex

size of contour interval labels

pch

plot character: glyph to plot

cex

character expansion factor: size of plotted characters

niter

the number of iterations to use in estimating the probability of the observed density

...

arguments to pass to the plot function

Value

• Function plotid returns a vector of row numbers of identified plots

Details

Function plot produces a scatter plot of sample scores for the specified axes, erasing or over-plotting on the current graphic device. Axes dimensions are controlled to produce a graph with the correct aspect ratio. Functions points, plotid, and surf add detail to an existing plot. The axes specified must match the underlying plot exactly.

Function plotid identifies and labels samples (optionally with values from a third vector) in the NMDS, and requires interaction with the mouse: left button identifies, right button exits.

Function points is passed a logical vector to identify a set of samples by color of glyph. It can be used to identify a single set meeting almost any criterion that can be stated as a logical expression.

Function hilight is passed a factor vector or integer vector, and identifies factor values by color and glyph.

Function chullord is passed a factor vector or integer vector, and plots a convex hull around all points in each factor class. By specifying values for arguments cols and ltys it is possible to control the sequence of colors and linetypes of the convex hulls.

Function density calculates the fraction of points within the convex hull that belong to the specified type.

Function surf calculates and plots fitted surfaces for logical or quantitative variables. The function employs the gam function to fit a variable to the ordination coordinates, and to predict the values at all grid points. The grid is established with the expand.grid function, and the grid is then specified in a call to predict.gam. The predicted values are trimmed to the the convex hull of the data, and the contours are fit by contour. The default link function for fitting the GAMs is gaussian, suitable for unbounded continuous variables. For logical variables you should specify family = binomial to get a logistic GAM, and for integer counts you should specify family = poisson to get a Poisson GAM.

References

http://ecology..msu.montana.edu/labdsv/R/labdsv

Examples

data(bryceveg)
data(brycesite)
dis.bc <- dsvdis(bryceveg,'bray/curtis')
nmds.1 <- nmds(dis.bc,5)
plot(nmds.1)
points(nmds.1,brycesite$elev>8000)
surf(nmds.1,brycesite$elev)
plotid(nmds.1,ids=row.names(bryceveg))