plotpc {plotpc} | R Documentation |
Plot principal component histograms around a scatter plot
Description
Plot principal component histograms around the scatter plot of two variables. Mostly useful as a tool for teaching principal components.
Usage
plotpc(x,
xrange=NULL,
hist=TRUE,
main="Principal components",
xlab=NULL,
ylab=NULL,
gp.points=gpar(cex=.6),
pch=20,
height=xrange/10,
breaks="Sturges",
adjust=1,
gp.hist=if(hist) gp.hist <- gpar(col="gray", fill="gray")
else gp.hist <- gpar(col="black"),
gp.text=gpar(cex=.8, font=2),
gp.axis=gpar(col="gray", lwd=2),
sd.ellipse=NA,
gp.ellipse=gpar(col="gray", lwd=2),
heightx=NULL, breaksx=NULL, adjustx=NULL, gp.histx=NULL,
textx="", gp.textx=NULL, axis.lenx=0, gp.axisx=NULL,
heighty=NULL, breaksy=NULL, adjusty=NULL, gp.histy=NULL,
texty="", gp.texty=NULL, axis.leny=0, gp.axisy=NULL,
height1=NULL, flip1=FALSE,
breaks1=NULL, adjust1=NULL, gp.hist1=NULL, offset1=NULL,
text1=NULL, gp.text1=NULL, axis.len1=2, gp.axis1=NULL,
height2=NULL, flip2=FALSE,
breaks2=NULL, adjust2=NULL, gp.hist2=NULL, offset2=NULL,
text2=NULL, gp.text2=NULL, axis.len2=2, gp.axis2=NULL,
angle3=NA, height3=NULL, flip3=FALSE,
breaks3=NULL, adjust3=NULL, gp.hist3=NULL, offset3=NULL,
text3=NULL, gp.text3=NULL, axis.len3=0, gp.axis3=NULL,
angle4=NA, height4=NULL, flip4=FALSE,
breaks4=NULL, adjust4=NULL, gp.hist4=NULL, offset4=NULL,
text4=NULL, gp.text4=NULL, axis.len4=0, gp.axis4=NULL,
angle5=NA, height5=NULL, flip5=FALSE,
breaks5=NULL, adjust5=NULL, gp.hist5=NULL, offset5=NULL,
text5=NULL, gp.text5=NULL, axis.len5=0, gp.axis5=NULL,
angle6=NA, height6=NULL, flip6=FALSE,
breaks6=NULL, adjust6=NULL, gp.hist6=NULL, offset6=NULL,
text6=NULL, gp.text6=NULL, axis.len6=0, gp.axis6=NULL,
angle7=NA, height7=NULL, flip7=FALSE,
breaks7=NULL, adjust7=NULL, gp.hist7=NULL, offset7=NULL,
text7=NULL, gp.text7=NULL, axis.len7=0, gp.axis7=NULL,
yonx = FALSE, offset.yonx=-xrange/2.5,
text.yonx="y~x", gp.text.yonx=NULL,
axis.len.yonx=xrange/2.5, gp.axis.yonx=gpar(col=1),
xony = FALSE, offset.xony=-xrange/2.5,
text.xony="x~y", gp.text.xony=NULL,
axis.len.xony=xrange/2.5, gp.axis.xony=gpar(col=1))
Arguments
Many users will find that they need only the first argument.
Use the xrange
argument to add whitespace around the histograms.
Set hist=FALSE
to plot densities rather than histograms.
Use heightx
and the height arguments to adjust
the height of histograms or to remove histograms from the plot.
Use offset1
and the other offset arguments to adjust
the positions of the histograms relative to the center of the graph.
Use angle1
and the other angle arguments to add extra histograms
to the plot at arbitrary angles.
Use yonx
and xony
to add linear regression lines to the plot.
x |
A two column matrix or dataframe.
The principal components of the |
hist |
Default |
xrange |
The range of the x axis.
That is, |
main |
Main title.
Default |
xlab |
x axis label.
Default |
ylab |
y axis label.
Default |
gp.points |
Graphic parameters for the plotted points.
Default |
pch |
Plot character for the plotted points.
Default |
height |
Height of histograms.
Default |
breaks |
Passed on to |
adjust |
Passed on to |
gp.hist |
Graphic parameters for the histograms or densities. |
gp.axis |
Graphic parameters for the axis drawn through the scatter of points.
Default |
sd.ellipse |
If greater than 0, draw a confidence ellipse
for the principal components at |
gp.ellipse |
Graphic parameters for the ellipse.
Default |
gp.text |
Graphic parameters for text above the histograms.
Default |
heightx |
Default |
breaksx |
Default |
adjustx |
Default |
gp.histx |
Default |
textx |
Text drawn above the histogram.
Default |
gp.textx |
Graphic parameters for the text above the histogram.
Default |
axis.lenx |
Length of horizontal line drawn through the center of the points.
Units are standard deviations of |
gp.axisx |
Default |
heighty , breaksy , adjusty , gp.histy , texty , gp.texty , axis.leny , gp.axisy |
As above but for the histogram on the y axis.
|
height1 |
Default |
flip1 |
Flip the position of the histogram around the axis of the first principal component.
Default |
breaks1 |
Default |
adjust1 |
Default |
gp.hist1 |
Default |
offset1 |
Distance of the histogram plot from the center of the graph, in native units.
Default |
text1 |
Text drawn above the histogram.
Default |
gp.text1 |
Graphic parameters for the text above the histogram.
Default |
axis.len1 |
Length of line drawn along the first principal axis.
Units are standard deviations of the points projected onto that axis.
Default |
gp.axis1 |
Default |
height2 , flip2 , breaks2 , adjust2 , gp.hist2 , offset2 , text2 , gp.text2 , axis.len2 , gp.axis2 |
As above but for the second principal component.
|
angle3 |
Default |
height3 |
Default |
flip3 |
Default |
breaks3 |
Default |
adjust3 |
Default |
gp.hist3 |
Default |
offset3 |
Default |
text3 |
Default |
gp.text3 |
Default |
axis.len3 |
Length of axis drawn at |
gp.axis3 |
Default |
angle4 , height4 , flip4 , breaks4 , adjust4 , gp.hist4 , offset4 , text4 , gp.text4 , axis.len4 , gp.axis4 |
As above but for the |
angle5 , height5 , flip5 , breaks5 , adjust5 , gp.hist5 , offset5 , text5 , gp.text5 , axis.len5 , gp.axis5 |
As above but for the |
angle6 , height6 , flip6 , breaks6 , adjust6 , gp.hist6 , offset6 , text6 , gp.text6 , axis.len6 , gp.axis6 |
As above but for the |
angle7 , height7 , flip7 , breaks7 , adjust7 , gp.hist7 , offset7 , text7 , gp.text7 , axis.len7 , gp.axis7 |
As above but for the |
yonx |
TRUE to plot a "y on x" linear regression line. Default FALSE. |
offset.yonx |
Position of text plotted on regression line.
Default |
text.yonx |
Text plotted on the regression line. Default |
gp.text.yonx |
Graphic parameters for the text plotted on the regression line.
Default |
axis.len.yonx |
Length of regression line in |
gp.axis.yonx |
Graphic parameters for the regression line.
Default |
xony , offset.xony , text.xony , gp.text.xony , axis.len.xony , gp.axis.xony |
As above but for a "x on y" regression. |
Value
Invisibly returns the viewport
used to create the
plotpc
axes.
This allows you to add text using the
"native"
coordinates of the plot. See the examples below.
Note
Here is how to draw scatter plots for all pairs of principal components:
data(iris) pc <- princomp(iris[, -5]) # -5 to drop Species pairs(pc$scores, col=c(2,3,4)[unclass(iris$Species)])
Author(s)
Stephen Milborrow. Users are encouraged to send feedback — use milboATsonicPERIODnet http://www.milbo.users.sonic.net.
See Also
plotld
,
princomp
,
hist
,
density
,
Examples
data(iris)
x <- iris[,c(3,4)] # select Petal.Length and Petal.Width
plotpc(x, main="Example 1\n")
# example with some parameters and showing densities
plotpc(x,
main="Example 2:\nPrincipal component densities\n",
hist=FALSE, # plot densities not histograms
adjust=.5, # finer resolution in the density plots
gp.axis=gpar(lty=3), # gpar of axes
heightx=0, # don't display x histogram
heighty=0, # don't display y histogram
text1="Principal Component 1", # text above hist for 1st principal component
text2="Principal Component 2", # text above hist for 2nd principal component
axis.len2=4, # length of 2nd principal axis (in std devs)
offset1=2.5, # offset of component 1 density plot
offset2=5) # offset of component 2 density plot
# example using "angles"
vp <- plotpc(x,
main="Example 3:\nProjections\n",
xrange=25, # give ourselves some space
heightx=0, # don't display x histogram
heighty=0, # don't display y histogram
angle3=-60, # project at -60 degrees
angle4=-25, # project at -25 degrees
angle5=20, # project at 20 degrees
angle6=70) # project at 70 degrees
# add text to the graph, can use native coords
pushViewport(vp)
grid.text("Projections at\nvarious angles",
x=unit(10, "native"), y=unit(12.5, "native"),
gp=gpar(col="red"))
popViewport()
# example showing principal axes
x <- iris[iris$Species=="versicolor",c(3,4)]
vp <- plotpc(x,
main="Example 4:\nPrincipal axes with confidence ellipse\n",
sd.ellipse=2, # ellipse at two standard devs
heightx=0, heighty=0, height1=0, height2=0, # no histograms
gp.ellipse=gpar(col=1), # ellipse in black
axis.lenx=4, axis.leny=5, # lengthen horiz and vertical axes
axis.len1=4, gp.axis1=gpar(col=1), # lengthen pc1 axis, draw in black
axis.len2=8, gp.axis2=gpar(col=1)) # lengthen pc2 axis, draw in black
pushViewport(vp) # add text to the graph
un <- function(x) unit(x, "native")
grid.text("PC1", x=un(2.2), y=un(.6), gp=gpar(cex=.8, font=2))
grid.text("PC2", x=un(3.9), y=un(2.35), gp=gpar(cex=.8, font=2))
grid.text("X1", x=un(2.2), y=un(1.4), gp=gpar(cex=.8, font=2))
grid.text("X2", x=un(4.3), y=un(2.5), gp=gpar(cex=.8, font=2))
popViewport()
# example comparing linear regression to principal axis
x <- iris[iris$Species=="setosa",c(3,4)]
vp <- plotpc(x,
main="Example 5:\nRegression lines and\nfirst principal component",
heightx=0, heighty=0, height1=0, height2=0, # no histograms
gp.points=gpar(col="steelblue"), # color of points
axis.len1=4, gp.axis1=gpar(col="gray", lwd=3),
axis.len2=.15, gp.axis2=gpar(col=1), # just a little blip of an axis
yonx=TRUE, xony=TRUE) # display regression lines
pushViewport(vp) # add text to the principal component line
grid.text("PC1", x=unit(.8, "native"), y=unit(0, "native"),
gp=gpar(col="gray", cex=.8, font=2))
popViewport()