################
# Section 11
################


# Demonstrations of some R graphics
demo(graphics)
demo(image)

#Creating and managing windows
windows()
windows() # opening windows -- graphics devices
windows()

# On a Mac, instead of windows(), you can try:
x11()  # should work on Linux too
# or:
quartz()

dev.set() # will return the active device
dev.set()
dev.set()
dev.set(3) # setting the active device
dev.set(2)
dev.off()  # closes a graphics window



zvars<-rnorm(100)

plot(zvars)

# Simple plot of a one-dimensional data vector is not very informative

data(state)

state.dfr <- data.frame(I(state.abb),state.region,state.x77)

attach(state.dfr)

# A basic histogram:

hist(Population)

hist(Population, main="Population in 10,000s by State, 1977")

# plot of a nonparametric density estimate:

plot(density(Population))

density(zvars)  # summary statistics, no plot shown

plot(density(zvars))

plot(density(rnorm(1000)))

plot(density(rnorm(10000)))

# A simple boxplot

boxplot(zvars) 

# A basic stem-and-leaf plot

stem(zvars)

# Plots for categorical data:

VADeaths  # a two-way table for two categorical variables

barplot(VADeaths,legend=T) # default is stacked bars to show the two dimensions

barplot(t(VADeaths),legend=T) # problem with legend

barplot(t(VADeaths),legend=T,args.legend = list(x = "topleft"))  # much better

# Revisiting the "barplot" command
# beside=TRUE produces side-by-side bars for each group
# beside=FALSE (the default) produces the stacked bars

barplot(VADeaths, beside = TRUE,
col = c("lightblue", "mistyrose", "lightcyan",
"lavender", "cornsilk"),
legend = rownames(VADeaths), ylim = c(0, 100))

barplot(t(VADeaths), beside = TRUE,
col = c("lightblue", "mistyrose", "lightcyan",
"lavender"),
legend = colnames(VADeaths), ylim = c(0, 100))

pie(VADeaths) # basic pie chart

# Showing marginal distribributions:

pie(apply(VADeaths,1,sum))

pie(apply(VADeaths,2,sum))

barplot(apply(VADeaths,1,sum))

barplot(apply(VADeaths,2,sum))

# Two-Dimensional Scatterplots:

data(state)

Illiteracy<-state.x77[,3]

Murder<-state.x77[,5]

plot(Illiteracy,Murder) # basic scatterplot

?par # help file for graphics parameters

 par() # returns default values for graphics parameters

# Adding things onto a basic scatterplot:

plot(Illiteracy,Murder,las=1,lwd=2,cex=1.2,pch=19, xlab="Percent Illiterate",ylab="")

#las=1 prints axis labels horizontally

title("Murders per 100,000 vs. Percent Illiterate")

text(2,4,"The 50 States",cex=1.2, adj=0, col=2)

# placing text in an interactive way:

text(locator(1),"1977",cex=1.2, adj=0, col=2)

arrows(x0=2.4, y0=8, x1=2.7, y1=12)

text(2.4, 7.5, "Which state?")

# Plotting a simple function:

xgrid <- seq(0,10,length=25)

yhat <- sqrt(xgrid)

plot(xgrid,yhat,type='l')

# The 'lines' function puts a curve on top of an existing scatterplot:

plot(xgrid, runif(25,0,10))

lines(xgrid,yhat)


plot(xgrid, runif(25,0,10), xlim=c(0,20), ylim=c(0,20))  # controlling the plotting window limits

# The 'points' function plots points on top of an existing scatterplot:

plot(xgrid,yhat,type='l', xlim=c(0,10), ylim=c(0,10))
points(xgrid, runif(25,0,10))


# Plotting a regression function on top of data:

plot(Illiteracy,Murder)

Illiteracy2 <- Illiteracy^2

lm(Murder ~ Illiteracy + Illiteracy2)

Illgrid <- pretty(Illiteracy,50)

Murderhat <- 1.6627+5.5642*Illgrid-0.4586*Illgrid^2

lines(Illgrid,Murderhat,lty=2,lwd=2,col=2)

text(0.5,14,"With Fitted Quadratic", adj=0, col=2)

colors()  # shows possible colors for plots

# Plotting a standard normal density:

curve(dnorm,-4,4)
curve(dnorm,-4,4,ylab="Standard Normal Density")
curve(dnorm,-4,4,main="Standard Normal Density",ylab=expression(phi(x)))

xvec <- yvec <- c(0,1)
plot(xvec,yvec, type="n",xaxt="n",xlab="",yaxt="n",ylab="")

# Creates empty plot

text(.6,.4,"The BEATLES",cex=1.5, adj=0, lwd=5, col="gray")

# Multiple plots on a page

par(mfrow=c(1,2))

plot(rnorm(15))

#repeat above command

par(mfrow=c(2,3)) 

par(mfcol=c(2,3))

# A simple example
par(mfrow=c(1,2))
plot(Illiteracy,Murder)
plot(Frost,Illiteracy)

# Demonstrating plotting characters and line types:

windows()
par(mfrow=c(1,2),pty="s")
plot(1:25,1:25,type="n")
for (i in 1:25) points(i,i,pch=i,cex=0.7)
title("25 pch symbols")
plot(1:6,1:6,type="n")
for (i in 1:6) lines(c(1,6),c(i,i),lty=i,lwd=2)
title("6 lty line types")

#An improved display for the plotting characters
par(mfrow=c(1,1))
plot(c(0.5,5.5),c(0.5,5.5),type="n",xlab="",ylab="",main="Plotting symbols 1-25, row by row")
rowseq=rep(1:5,each=5)
colseq=rep(1:5,5)
pchval=(colseq-1)*5+rowseq
points(rowseq,colseq,pch=pchval,cex=3.0)
text(rowseq,colseq-.3,paste(pchval))

# 3-D plots
help(datasets)

data(volcano)

volcano

contour(volcano)  # a contour plot

# Some 3-D perspective plots:

persp(volcano, theta=30, phi=15)

persp(volcano, theta=60, phi=15)

persp(volcano, theta=90, phi=15)

persp(volcano, theta=150, phi=15)

persp(volcano, theta=0, phi=45)

persp(volcano, theta=0, phi=0)

persp(volcano, theta=0, phi=-30)

filled.contour(volcano)

#colors needs an argument
filled.contour(volcano,col=terrain.colors(10))
filled.contour(volcano,col=terrain.colors(25))

# A heat plot:

image(volcano)

# Two plots on same window:

image(volcano)
par(new=T)
# does not remove previous plot before doing next plot
contour(volcano)

# A better way:
image(volcano)
contour(volcano, add=T)

# Interactive graphics

plot(Illiteracy,Murder)

mypoints <- identify(Illiteracy,Murder,state.abb)

mypoints

state.abb[mypoints]

mypoints <- identify(Illiteracy,Murder,state.abb,pos=TRUE)

mypoints

state.abb[mypoints$ind]


#Scatterplot matrix:

pairs(state.x77[,3:6])

# Plotting scatterplots for separate categories:

coplot( Murder ~ Illiteracy | state.region)


#trellis graphs

# loading the "lattice" package:

library(lattice)

xyplot( Murder ~ Illiteracy | state.region)

### Saving graphics output as postscript or pdf files:

# File -> Change directory, then:

postscript("myplotname.eps",onefile=FALSE, horizontal=FALSE)
# plotting commands:
plot(Illiteracy,Murder)
# Closing graphics device:
dev.off()

# To save as a pdf:

pdf("myplotname.pdf",onefile=FALSE)
# plotting commands:
plot(Illiteracy,Murder)
# Closing graphics device:
dev.off()