plotpc: Plot principal component histograms around a scatter plot

In plotpc: 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 x will be calculated treating each column as a variable.
hist	Default TRUE to plot histograms. Set to FALSE to plot densities instead. The various "histogram" arguments will then apply to densities rather than to histograms.
xrange	The range of the x axis. That is, xlim will be c(mean(x[,1]) - xrange/2, mean(x[,1]) + xrange/2), and ylim will have the same range about mean(x[,2]). Default NULL, meaning automatically deduce axis limits from the x argument.
main	Main title. Default "Principal components".
xlab	x axis label. Default NULL, meaning create the label automatically from the column names of x.
ylab	y axis label. Default NULL, meaning create the label automatically from the column names of x.
gp.points	Graphic parameters for the plotted points. Default gpar(cex=.6).
pch	Plot character for the plotted points. Default 20. The following arguments apply to all histograms. These can be overridden by using the histogram-specific argument e.g. override the height argument for the first principal component by specifying height1.
height	Height of histograms. Default xrange/10. Use a negative height to flip a histogram around its base.
breaks	Passed on to hist. Default "Sturges". Using something like breaks=12 can be useful.
adjust	Passed on to density. Default 1. Use something like adjust=.5 for more details in the density plots.
gp.hist	Graphic parameters for the histograms or densities. If hist==TRUE then the default is gpar(col="gray", fill="gray") where col is the color of the lines delineating the histograms, and fill is the color filling the histograms. If hist==FALSE then the default is gpar(col="black").
gp.axis	Graphic parameters for the axis drawn through the scatter of points. Default gpar(col="gray", lwd=2) meaning draw the axes as thickish gray lines.
sd.ellipse	If greater than 0, draw a confidence ellipse for the principal components at sd.ellipse standard deviations. Default is NA, meaning do not draw an ellipse.
gp.ellipse	Graphic parameters for the ellipse. Default gpar(col="gray", lwd=2).
gp.text	Graphic parameters for text above the histograms. Default gpar(cex=.8, font=2). The following arguments apply to the histogram on the x axis.
heightx	Default NULL, meaning use height. Use 0 to not plot the x histogram.
breaksx	Default NULL, meaning use breaks.
adjustx	Default NULL, meaning use adjust.
gp.histx	Default NULL, meaning use gp.hist.
textx	Text drawn above the histogram. Default "", meaning no text. The text is drawn using gp.textx.
gp.textx	Graphic parameters for the text above the histogram. Default NULL, meaning use gp.text.
axis.lenx	Length of horizontal line drawn through the center of the points. Units are standard deviations of x[,1]. Default 0, meaning do not plot a horizontal axis.
gp.axisx	Default NULL, meaning use gp.axis.
heighty, breaksy, adjusty, gp.histy, texty, gp.texty, axis.leny, gp.axisy	As above but for the histogram on the y axis. The following arguments apply to the first principal component.
height1	Default NULL, meaning use height. Use 0 to not plot the histogram for the first principal component.
flip1	Flip the position of the histogram around the axis of the first principal component. Default FALSE, meaning do not flip.
breaks1	Default NULL, meaning use breaks.
adjust1	Default NULL, meaning use adjust.
gp.hist1	Default NULL, meaning use gp.hist.
offset1	Distance of the histogram plot from the center of the graph, in native units. Default NULL, meaning automatic.
text1	Text drawn above the histogram. Default NULL, meaning generate the text automatically. Use "" for no text. The text is drawn using gp.text1.
gp.text1	Graphic parameters for the text above the histogram. Default NULL, meaning use gp.text.
axis.len1	Length of line drawn along the first principal axis. Units are standard deviations of the points projected onto that axis. Default 2, meaning draw a line of length plus and minus two standard deviations. Use 0 for no axis.
gp.axis1	Default NULL, meaning use gp.axis.
height2, flip2, breaks2, adjust2, gp.hist2, offset2, text2, gp.text2, axis.len2, gp.axis2	As above but for the second principal component. The following arguments apply to the optional histogram at angle3. By default, angle3=NA, meaning do not plot the histogram. Use, say, angle3=45 to plot a histogram at 45 degrees. By setting angle3 to angle7 you can plot up to five extra histograms at any angles.
angle3	Default NA, meaning do not plot a histogram. Use, say, angle3=45 to plot a histogram at 45 degrees.
height3	Default NULL, meaning use height.
flip3	Default FALSE.
breaks3	Default NULL, meaning use breaks.
adjust3	Default NULL, meaning use adjust.
gp.hist3	Default NULL, meaning use gp.hist.
offset3	Default NULL, meaning automatic.
text3	Default NULL, meaning automatic.
gp.text3	Default NULL, meaning use gp.text.
axis.len3	Length of axis drawn at angle3 through the scatter of points. Default 0, meaning do not plot the axis.
gp.axis3	Default NULL, meaning use gp.axis.
angle4, height4, flip4, breaks4, adjust4, gp.hist4, offset4, text4, gp.text4, axis.len4, gp.axis4	As above but for the angle4 histogram.
angle5, height5, flip5, breaks5, adjust5, gp.hist5, offset5, text5, gp.text5, axis.len5, gp.axis5	As above but for the angle5 histogram.
angle6, height6, flip6, breaks6, adjust6, gp.hist6, offset6, text6, gp.text6, axis.len6, gp.axis6	As above but for the angle6 histogram.
angle7, height7, flip7, breaks7, adjust7, gp.hist7, offset7, text7, gp.text7, axis.len7, gp.axis7	As above but for the angle7 histogram. The following arguments apply to the optional "y on x" regression line.
yonx	TRUE to plot a "y on x" linear regression line. Default FALSE.
offset.yonx	Position of text plotted on regression line. Default -xrange/2.5.
text.yonx	Text plotted on the regression line. Default "y~x".
gp.text.yonx	Graphic parameters for the text plotted on the regression line. Default NULL, meaning use gp.text.
axis.len.yonx	Length of regression line in gpar "native" units. Default -xrange/2.5.
gp.axis.yonx	Graphic parameters for the regression line. Default gpar(col=1).
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()

plotpc documentation built on May 1, 2019, 6:33 p.m.