plot.pco {labdsv} | R Documentation |
A set of routines for plotting, highlighting points, or adding fitted surfaces to PCOs.
## S3 method for class 'pco': plot(x, ax = 1, ay = 2, col = 1, title = "", pch = 1, ...) ## S3 method for class 'pco': points(x, which, ax = 1, ay = 2, col = 2, pch = 1, cex = 1, ...) ## S3 method for class 'pco': plotid(ord, ids = seq(1:nrow(ord$points)), ax = 1, ay = 2, col = 1, ...) ## S3 method for class 'pco': 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 'pco': chullord(ord, overlay, ax = 1, ay = 2, cols=c(2,3,4,5,6,7), ltys = c(1,2,3), ...) ## S3 method for class 'pco': density(ord, overlay, ax = 1, ay = 2, cols = c(2, 3, 4, 5, 6, 7), ltys = c(1, 2, 3), niter=100, ...) ## S3 method for class 'pco': surf(ord, var, ax = 1, ay = 2, thinplate=TRUE, col = 2, labcex = 0.8, family = gaussian, grid=50, gamma=1, ...)
x |
an object of class ‘pco’ |
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 |
ord |
an object of class ‘pco’ |
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 ed |
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 |
niter |
number of iterations to use in estimating the probility of obtaining the observed density |
var |
a variable to be surfaced |
thinplate |
a logical variable to control how the surface is fit: 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 points to use in establishing a grid for 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 |
... |
arguments to pass to the plot function |
Function ‘plot’ produces a scatterplot 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’, ‘hilight’, ‘chullord’, 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 PCO, 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. By specifying values for arguments ‘cols’ and ‘glyph’ it is possible to control the sequence of colors and pch glyphs used in the hilight.
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.
Function ‘plotid’ returns a vector of row numbers of identified plots
Previous versions of surf relied on the ‘interp’ function of
package akima
. The revised routine using
predict.gam
was suggested by Jari Oksanen as used in
packageordisurf
.
David W. Roberts droberts@montana.edu
http://ecology.msu.montana.edu/labdsv/R/labdsv
data(bryceveg) data(brycesite) dis.bc <- dsvdis(bryceveg,'bray/curtis') pco.1 <- pco(dis.bc,5) plot(pco.1) points(pco.1,brycesite$elev>8000) surf(pco.1,brycesite$elev) ## Not run: plotid(pco.1,ids=row.names(bryceveg))