EVOLUTION-MANAGER

Edit File: graphics.R

# Copyright (C) 1997-2009 The R Core Team require(datasets) require(grDevices); require(graphics) ## Here is some code which illustrates some of the differences between ## R and S graphics capabilities. Note that colors are generally specified ## by a character string name (taken from the X11 rgb.txt file) and that line ## textures are given similarly. The parameter "bg" sets the background ## parameter for the plot and there is also an "fg" parameter which sets ## the foreground color. x <- stats::rnorm(50) opar <- par(bg = "white") plot(x, ann = FALSE, type = "n") abline(h = 0, col = gray(.90)) lines(x, col = "green4", lty = "dotted") points(x, bg = "limegreen", pch = 21) title(main = "Simple Use of Color In a Plot", xlab = "Just a Whisper of a Label", col.main = "blue", col.lab = gray(.8), cex.main = 1.2, cex.lab = 1.0, font.main = 4, font.lab = 3) ## A little color wheel. This code just plots equally spaced hues in ## a pie chart. If you have a cheap SVGA monitor (like me) you will ## probably find that numerically equispaced does not mean visually ## equispaced. On my display at home, these colors tend to cluster at ## the RGB primaries. On the other hand on the SGI Indy at work the ## effect is near perfect. par(bg = "gray") pie(rep(1,24), col = rainbow(24), radius = 0.9) title(main = "A Sample Color Wheel", cex.main = 1.4, font.main = 3) title(xlab = "(Use this as a test of monitor linearity)", cex.lab = 0.8, font.lab = 3) ## We have already confessed to having these. This is just showing off X11 ## color names (and the example (from the postscript manual) is pretty "cute". pie.sales <- c(0.12, 0.3, 0.26, 0.16, 0.04, 0.12) names(pie.sales) <- c("Blueberry", "Cherry", "Apple", "Boston Cream", "Other", "Vanilla Cream") pie(pie.sales, col = c("purple","violetred1","green3","cornsilk","cyan","white")) title(main = "January Pie Sales", cex.main = 1.8, font.main = 1) title(xlab = "(Don't try this at home kids)", cex.lab = 0.8, font.lab = 3) ## Boxplots: I couldn't resist the capability for filling the "box". ## The use of color seems like a useful addition, it focuses attention ## on the central bulk of the data. par(bg="cornsilk") n <- 10 g <- gl(n, 100, n*100) x <- rnorm(n*100) + sqrt(as.numeric(g)) boxplot(split(x,g), col="lavender", notch=TRUE) title(main="Notched Boxplots", xlab="Group", font.main=4, font.lab=1) ## An example showing how to fill between curves. par(bg="white") n <- 100 x <- c(0,cumsum(rnorm(n))) y <- c(0,cumsum(rnorm(n))) xx <- c(0:n, n:0) yy <- c(x, rev(y)) plot(xx, yy, type="n", xlab="Time", ylab="Distance") polygon(xx, yy, col="gray") title("Distance Between Brownian Motions") ## Colored plot margins, axis labels and titles. You do need to be ## careful with these kinds of effects. It's easy to go completely ## over the top and you can end up with your lunch all over the keyboard. ## On the other hand, my market research clients love it. x <- c(0.00, 0.40, 0.86, 0.85, 0.69, 0.48, 0.54, 1.09, 1.11, 1.73, 2.05, 2.02) par(bg="lightgray") plot(x, type="n", axes=FALSE, ann=FALSE) usr <- par("usr") rect(usr[1], usr[3], usr[2], usr[4], col="cornsilk", border="black") lines(x, col="blue") points(x, pch=21, bg="lightcyan", cex=1.25) axis(2, col.axis="blue", las=1) axis(1, at=1:12, lab=month.abb, col.axis="blue") box() title(main= "The Level of Interest in R", font.main=4, col.main="red") title(xlab= "1996", col.lab="red") ## A filled histogram, showing how to change the font used for the ## main title without changing the other annotation. par(bg="cornsilk") x <- rnorm(1000) hist(x, xlim=range(-4, 4, x), col="lavender", main="") title(main="1000 Normal Random Variates", font.main=3) ## A scatterplot matrix ## The good old Iris data (yet again) pairs(iris[1:4], main="Edgar Anderson's Iris Data", font.main=4, pch=19) pairs(iris[1:4], main="Edgar Anderson's Iris Data", pch=21, bg = c("red", "green3", "blue")[unclass(iris$Species)]) ## Contour plotting ## This produces a topographic map of one of Auckland's many volcanic "peaks". x <- 10*1:nrow(volcano) y <- 10*1:ncol(volcano) lev <- pretty(range(volcano), 10) par(bg = "lightcyan") pin <- par("pin") xdelta <- diff(range(x)) ydelta <- diff(range(y)) xscale <- pin[1]/xdelta yscale <- pin[2]/ydelta scale <- min(xscale, yscale) xadd <- 0.5*(pin[1]/scale - xdelta) yadd <- 0.5*(pin[2]/scale - ydelta) plot(numeric(0), numeric(0), xlim = range(x)+c(-1,1)*xadd, ylim = range(y)+c(-1,1)*yadd, type = "n", ann = FALSE) usr <- par("usr") rect(usr[1], usr[3], usr[2], usr[4], col="green3") contour(x, y, volcano, levels = lev, col="yellow", lty="solid", add=TRUE) box() title("A Topographic Map of Maunga Whau", font= 4) title(xlab = "Meters North", ylab = "Meters West", font= 3) mtext("10 Meter Contour Spacing", side=3, line=0.35, outer=FALSE, at = mean(par("usr")[1:2]), cex=0.7, font=3) ## Conditioning plots par(bg="cornsilk") coplot(lat ~ long | depth, data = quakes, pch = 21, bg = "green3") par(opar)