Hmisc (version 5.3-0)

labcurve: Label Curves, Make Keys, and Interactively Draw Points and Curves

Description

labcurve optionally draws a set of curves then labels the curves. A variety of methods for drawing labels are implemented, ranging from positioning using the mouse to automatic labeling to automatic placement of key symbols with manual placement of key legends to automatic placement of legends. For automatic positioning of labels or keys, a curve is labeled at a point that is maximally separated from all of the other curves. Gaps occurring when curves do not start or end at the same x-coordinates are given preference for positioning labels. If labels are offset from the curves (the default behaviour), if the closest curve to curve i is above curve i, curve i is labeled below its line. If the closest curve is below curve i, curve i is labeled above its line. These directions are reversed if the resulting labels would appear outside the plot region.

Both ordinary lines and step functions are handled, and there is an option to draw the labels at the same angle as the curve within a local window.

Unless the mouse is used to position labels or plotting symbols are placed along the curves to distinguish them, curves are examined at 100 (by default) equally spaced points over the range of x-coordinates in the current plot area. Linear interpolation is used to get y-coordinates to line up (step function or constant interpolation is used for step functions). There is an option to instead examine all curves at the set of unique x-coordinates found by unioning the x-coordinates of all the curves. This option is especially useful when plotting step functions. By setting adj="auto" you can have labcurve try to optimally left- or right-justify labels depending on the slope of the curves at the points at which labels would be centered (plus a vertical offset). This is especially useful when labels must be placed on steep curve sections.

You can use the on top method to write (short) curve names directly on the curves (centered on the y-coordinate). This is especially useful when there are many curves whose full labels would run into each other. You can plot letters or numbers on the curves, for example (using the keys option), and have labcurve use the key function to provide long labels for these short ones (see the end of the example). There is another option for connecting labels to curves using arrows. When keys is a vector of integers, it is taken to represent plotting symbols (pchs), and these symbols are plotted at equally-spaced x-coordinates on each curve (by default, using 5 points per curve). The points are offset in the x-direction between curves so as to minimize the chance of collisions.

To add a legend defining line types, colors, or line widths with no symbols, specify keys="lines", e.g., labcurve(curves, keys="lines", lty=1:2).

putKey provides a different way to use key() by allowing the user to specify vectors for labels, line types, plotting characters, etc. Elements that do not apply (e.g., pch for lines (type="l")) may be NA. When a series of points is represented by both a symbol and a line, the corresponding elements of both pch and lty, col., or lwd will be non-missing.

putKeyEmpty, given vectors of all the x-y coordinates that have been plotted, uses largest.empty to find the largest empty rectangle large enough to hold the key, and draws the key using putKey.

drawPlot is a simple mouse-driven function for drawing series of lines, step functions, polynomials, Bezier curves, and points, and automatically labeling the point groups using labcurve or putKeyEmpty. When drawPlot is invoked it creates temporary functions Points, Curve, and Abline. The user calls these functions inside the call to drawPlot to define groups of points in the order they are defined with the mouse. Abline is used to call abline and not actually great a group of points. For some curve types, the curve generated to represent the corresponding series of points is drawn after all points are entered for that series, and this curve may be different than the simple curve obtained by connecting points at the mouse clicks. For example, to draw a general smooth Bezier curve the user need only click on a few points, and she must overshoot the final curve coordinates to define the curve. The originally entered points are not erased once the curve is drawn. The same goes for step functions and polynomials. If you plot() the object returned by drawPlot, however, only final curves will be shown. The last examples show how to use drawPlot.

The largest.empty function finds the largest rectangle that is large enough to hold a rectangle of a given height and width, such that the rectangle does not contain any of a given set of points. This is used by labcurve and putKeyEmpty to position keys at the most empty part of an existing plot. The default method was created by Hans Borchers.

Usage

labcurve(curves, labels=names(curves),
         method=NULL, keys=NULL, keyloc=c("auto","none"),
         type="l", step.type=c("left", "right"), 
         xmethod=if(any(type=="s")) "unique" else "grid", 
         offset=NULL, xlim=NULL,
         tilt=FALSE, window=NULL, npts=100, cex=NULL, 
         adj="auto", angle.adj.auto=30,
         lty=pr$lty, lwd=pr$lwd, col.=pr$col, transparent=TRUE,
         arrow.factor=1, point.inc=NULL, opts=NULL, key.opts=NULL,
         empty.method=c('area','maxdim'), numbins=25, 
         pl=!missing(add), add=FALSE, 
         ylim=NULL, xlab="", ylab="",
         whichLabel=1:length(curves),
         grid=FALSE, xrestrict=NULL, ...)
putKey(z, labels, type, pch, lty, lwd,
       cex=par('cex'), col=rep(par('col'),nc),
       transparent=TRUE, plot=TRUE, key.opts=NULL, grid=FALSE)
putKeyEmpty(x, y, labels, type=NULL,
            pch=NULL, lty=NULL, lwd=NULL,
            cex=par('cex'), col=rep(par('col'),nc),
            transparent=TRUE, plot=TRUE, key.opts=NULL,
            empty.method=c('area','maxdim'), 
            numbins=25, 
            xlim=pr$usr[1:2], ylim=pr$usr[3:4], grid=FALSE)
drawPlot(..., xlim=c(0,1), ylim=c(0,1), xlab='', ylab='',
         ticks=c('none','x','y','xy'),
         key=FALSE, opts=NULL)
# Points(label=' ', type=c('p','r'),
#        n, pch=pch.to.use[1], cex=par('cex'), col=par('col'),
#        rug = c('none','x','y','xy'), ymean)
# Curve(label=' ',
#       type=c('bezier','polygon','linear','pol','loess','step','gauss'),
#       n=NULL, lty=1, lwd=par('lwd'), col=par('col'), degree=2,
#      evaluation=100, ask=FALSE)
# Abline(\dots)
# S3 method for drawPlot
plot(x, xlab, ylab, ticks,
     key=x$key, keyloc=x$keyloc, ...)
largest.empty(x, y, width=0, height=0, 
              numbins=25, method=c('exhaustive','rexhaustive','area','maxdim'),
              xlim=pr$usr[1:2], ylim=pr$usr[3:4],
              pl=FALSE, grid=FALSE)

Value

labcurve returns an invisible list with components x, y, offset, adj, cex, col, and if tilt=TRUE, angle. offset is the amount to add to y to draw a label. offset is negative if the label is drawn below the line. adj is a vector containing the values 0, .5, 1.

largest.empty returns a list with elements x and y

specifying the coordinates of the center of the rectangle which was found, and element rect containing the 4 x and y

coordinates of the corners of the found empty rectangle. The area of the rectangle is also returned.

Details

The internal functions Points, Curve, Abline have unique arguments as follows.

label:

for Points and Curve is a single character string to label that group of points

n:

number of points to accept from the mouse. Default is to input points until a right mouse click.

rug:

for Points. Default is "none" to not show the marginal x or y distributions as rug plots, for the points entered. Other possibilities are used to execute scat1d to show the marginal distribution of x, y, or both as rug plots.

ymean:

for Points, subtracts a constant from each y-coordinate entered to make the overall mean ymean

degree:

degree of polynomial to fit to points by Curve

evaluation:

number of points at which to evaluate Bezier curves, polynomials, and other functions in Curve

ask:

set ask=TRUE to give the user the opportunity to try again at specifying points for Bezier curves, step functions, and polynomials

The labcurve function used some code from the function plot.multicurve written by Rod Tjoelker of The Boeing Company ().

If there is only one curve, a label is placed at the middle x-value, and no fancy features such as angle or positive/negative offsets are used.

key is called once (with the argument plot=FALSE) to find the key dimensions. Then an empty rectangle with at least these dimensions is searched for using largest.empty. Then key is called again to draw the key there, using the argument corner=c(.5,.5) so that the center of the rectangle can be specified to key.

If you want to plot the data, an easier way to use labcurve is through xYplot as shown in some of its examples.

See Also

approx, text, legend, scat1d, xYplot, abline

Examples

n <- 2:8
m <-  length(n)
type <- c('l','l','l','l','s','l','l')
# s=step function l=ordinary line (polygon)
curves <- vector('list', m)


plot(0,1,xlim=c(0,1),ylim=c(-2.5,4),type='n')


set.seed(39)


for(i in 1:m) {
  x <- sort(runif(n[i]))
  y <- rnorm(n[i])
  lines(x, y, lty=i, type=type[i], col=i)
  curves[[i]] <- list(x=x,y=y)
}


labels <- paste('Label for',letters[1:m])
labcurve(curves, labels, tilt=TRUE, type=type, col=1:m)


# Put only single letters on curves at points of 
# maximum space, and use key() to define the letters,
# with automatic positioning of the key in the most empty
# part of the plot
# Have labcurve do the plotting, leaving extra space for key


names(curves) <- labels
labcurve(curves, keys=letters[1:m], type=type, col=1:m,
         pl=TRUE, ylim=c(-2.5,4))


# Put plotting symbols at equally-spaced points,
# with a key for the symbols, ignoring line types


labcurve(curves, keys=1:m, lty=1, type=type, col=1:m,
         pl=TRUE, ylim=c(-2.5,4))




# Plot and label two curves, with line parameters specified with data
set.seed(191)
ages.f <- sort(rnorm(50,20,7))
ages.m <- sort(rnorm(40,19,7))
height.f <- pmin(ages.f,21)*.2+60
height.m <- pmin(ages.m,21)*.16+63


labcurve(list(Female=list(ages.f,height.f,col=2),
              Male  =list(ages.m,height.m,col=3,lty='dashed')),
         xlab='Age', ylab='Height', pl=TRUE)
# add ,keys=c('f','m') to label curves with single letters
# For S-Plus use lty=2


# Plot power for testing two proportions vs. n for various odds ratios, 
# using 0.1 as the probability of the event in the control group.  
# A separate curve is plotted for each odds ratio, and the curves are
# labeled at points of maximum separation


n  <- seq(10, 1000, by=10)
OR <- seq(.2,.9,by=.1)
pow <- lapply(OR, function(or,n)list(x=n,y=bpower(p1=.1,odds.ratio=or,n=n)),
              n=n)
names(pow) <- format(OR)
labcurve(pow, pl=TRUE, xlab='n', ylab='Power')


# Plot some random data and find the largest empty rectangle
# that is at least .1 wide and .1 tall


x <- runif(50)
y <- runif(50)
plot(x, y)
z <- largest.empty(x, y, .1, .1)
z
points(z,pch=3)  # mark center of rectangle, or
polygon(z$rect, col='blue')  # to draw the rectangle, or
#key(z$x, z$y, \dots stuff for legend)




# Use the mouse to draw a series of points using one symbol, and
# two smooth curves or straight lines (if two points are clicked), 
# none of these being labeled


# d <- drawPlot(Points(), Curve(), Curve())
# plot(d)


if (FALSE) {
# Use the mouse to draw a Gaussian density, two series of points
# using 2 symbols, one Bezier curve, a step function, and raw data
# along the x-axis as a 1-d scatter plot (rug plot).  Draw a key.
# The density function is fit to 3 mouse clicks
# Abline draws a dotted horizontal reference line
d <- drawPlot(Curve('Normal',type='gauss'),
              Points('female'), Points('male'), 
              Curve('smooth',ask=TRUE,lty=2), Curve('step',type='s',lty=3), 
              Points(type='r'), Abline(h=.5, lty=2),
              xlab='X', ylab='y', xlim=c(0,100), key=TRUE)
plot(d, ylab='Y')
plot(d, key=FALSE)  # label groups using labcurve
}