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技术 2022年11月18日
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吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

吴裕雄–天生自然 R语言开发学习:图形初阶

# ----------------------------------------------------#
# R in Action (2nd ed): Chapter 3 #
# Getting started with graphs #
# requires that the Hmisc and RColorBrewer packages #
# have been installed #
# install.packages(c("Hmisc", "RColorBrewer")) #
#-----------------------------------------------------#par(ask=TRUE)
opar <- par(no.readonly=TRUE) # make a copy of current settingsattach(mtcars) # be sure to execute this lineplot(wt, mpg)
abline(lm(mpg~wt))
title("Regression of MPG on Weight")
# Input data for drug example
dose <- c(20, 30, 40, 45, 60)
drugA <- c(16, 20, 27, 40, 60)
drugB <- c(15, 18, 25, 31, 40)plot(dose, drugA, type="b")opar <- par(no.readonly=TRUE) # make a copy of current settings
par(lty=2, pch=17) # change line type and symbol
plot(dose, drugA, type="b") # generate a plot
par(opar) # restore the original settings plot(dose, drugA, type="b", lty=3, lwd=3, pch=15, cex=2)# choosing colors
library(RColorBrewer)
n <- 7
mycolors <- brewer.pal(n, "Set1")
barplot(rep(1,n), col=mycolors)n <- 10
mycolors <- rainbow(n)
pie(rep(1, n), labels=mycolors, col=mycolors)
mygrays <- gray(0:n/n)
pie(rep(1, n), labels=mygrays, col=mygrays)# Listing 3.1 - Using graphical parameters to control graph appearance
dose <- c(20, 30, 40, 45, 60)
drugA <- c(16, 20, 27, 40, 60)
drugB <- c(15, 18, 25, 31, 40)
opar <- par(no.readonly=TRUE)
par(pin=c(2, 3))
par(lwd=2, cex=1.5)
par(cex.axis=.75, font.axis=3)
plot(dose, drugA, type="b", pch=19, lty=2, col="red")
plot(dose, drugB, type="b", pch=23, lty=6, col="blue", bg="green")
par(opar) # Adding text, lines, and symbols
plot(dose, drugA, type="b",
col="red", lty=2, pch=2, lwd=2,
main="Clinical Trials for Drug A",
sub="This is hypothetical data",
xlab="Dosage", ylab="Drug Response",
xlim=c(0, 60), ylim=c(0, 70))# Listing 3.2 - An Example of Custom Axes
x <- c(1:10)
y <- x
z <- 10/x
opar <- par(no.readonly=TRUE)
par(mar=c(5, 4, 4, 8) + 0.1)
plot(x, y, type="b",
pch=21, col="red",
yaxt="n", lty=3, ann=FALSE)
lines(x, z, type="b", pch=22, col="blue", lty=2)
axis(2, at=x, labels=x, col.axis="red", las=2)
axis(4, at=z, labels=round(z, digits=2),
col.axis="blue", las=2, cex.axis=0.7, tck=-.01)
mtext("y=1/x", side=4, line=3, cex.lab=1, las=2, col="blue")
title("An Example of Creative Axes",
xlab="X values",
ylab="Y=X")
par(opar)# Listing 3.3 - Comparing Drug A and Drug B response by dose
dose <- c(20, 30, 40, 45, 60)
drugA <- c(16, 20, 27, 40, 60)
drugB <- c(15, 18, 25, 31, 40)
opar <- par(no.readonly=TRUE)
par(lwd=2, cex=1.5, font.lab=2)
plot(dose, drugA, type="b",
pch=15, lty=1, col="red", ylim=c(0, 60),
main="Drug A vs. Drug B",
xlab="Drug Dosage", ylab="Drug Response")
lines(dose, drugB, type="b",
pch=17, lty=2, col="blue")
abline(h=c(30), lwd=1.5, lty=2, col="gray")
library(Hmisc)
minor.tick(nx=3, ny=3, tick.ratio=0.5)
legend("topleft", inset=.05, title="Drug Type", c("A","B"),
lty=c(1, 2), pch=c(15, 17), col=c("red", "blue"))
par(opar)# Example of labeling points
attach(mtcars)
plot(wt, mpg,
main="Mileage vs. Car Weight",
xlab="Weight", ylab="Mileage",
pch=18, col="blue")
text(wt, mpg,
row.names(mtcars),
cex=0.6, pos=4, col="red")
detach(mtcars)# View font families
opar <- par(no.readonly=TRUE)
par(cex=1.5)
plot(1:7,1:7,type="n")
text(3,3,"Example of default text")
text(4,4,family="mono","Example of mono-spaced text")
text(5,5,family="serif","Example of serif text")
par(opar)# Combining graphs
attach(mtcars)
opar <- par(no.readonly=TRUE)
par(mfrow=c(2,2))
plot(wt,mpg, main="Scatterplot of wt vs. mpg")
plot(wt,disp, main="Scatterplot of wt vs. disp")
hist(wt, main="Histogram of wt")
boxplot(wt, main="Boxplot of wt")
par(opar)
detach(mtcars)attach(mtcars)
opar <- par(no.readonly=TRUE)
par(mfrow=c(3,1))
hist(wt)
hist(mpg)
hist(disp)
par(opar)
detach(mtcars)attach(mtcars)
layout(matrix(c(1,1,2,3), 2, 2, byrow = TRUE))
hist(wt)
hist(mpg)
hist(disp)
detach(mtcars)attach(mtcars)
layout(matrix(c(1, 1, 2, 3), 2, 2, byrow = TRUE),
widths=c(3, 1), heights=c(1, 2))
hist(wt)
hist(mpg)
hist(disp)
detach(mtcars)# Listing 3.4 - Fine placement of figures in a graph
opar <- par(no.readonly=TRUE)
par(fig=c(0, 0.8, 0, 0.8))
plot(mtcars$mpg, mtcars$wt,
xlab="Miles Per Gallon",
ylab="Car Weight")
par(fig=c(0, 0.8, 0.55, 1), new=TRUE)
boxplot(mtcars$mpg, horizontal=TRUE, axes=FALSE)
par(fig=c(0.65, 1, 0, 0.8), new=TRUE)
boxplot(mtcars$wt, axes=FALSE)
mtext("Enhanced Scatterplot", side=3, outer=TRUE, line=-3)
par(opar)
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