################################################################################
# CODE FOR PRODUCING GRAPHICS IN PRESENTATION
# January 27, 2010
# RYAN R. ROSARIO
# UCLA Statistical Consulting Center
# Department of Statistics
# University of California, Los Angeles
#
# Please do not redistribute without this header.
################################################################################

#PAGE 12
#Bivariate plot of textbook prices.
texts <- read.csv("http://www.stat.ucla.edu/~rosario/boot08/data/book-shopping.csv",header=TRUE)
plot(texts[,5],texts[,7],main="Bivariate Analysis of\n Textbook Prices",xlab="Amazon Sales Price",ylab="Borders Sales Price",pch='*',xaxt="n",yaxt="n",cex.lab=0.75,bg="grey")
mtext("Fall 2008",3,font=3)
axis(1,at=seq(0,200,25),paste("$",seq(0,200,25)),cex.axis=0.75,col="grey")
axis(2,at=seq(0,200,25),paste("$",seq(0,200,25)),cex.axis=0.75,col="grey")
axis(c(3:4),col="grey",tick=FALSE,labels=FALSE)
box("plot",col="grey")

#PAGE 28
#Plot types
par(mfrow=c(2,3))
plot(y~x,type="p",xlab="Time",ylab="Effort",xaxt="n",yaxt="n",main="type=\"p\" (points)")
axis(1,at=seq(0,600,200),labels=c(0,"T/3","2T/3","T"))
plot(y~x,type="b",xlab="Time",ylab="Effort",xaxt="n",yaxt="n",main="type=\"b\" (both lines and points)")
axis(1,at=seq(0,600,200),labels=c(0,"T/3","2T/3","T"))
mtext("type=o is similar",3)
plot(y~x,type="h",xlab="Time",ylab="Effort",xaxt="n",yaxt="n",main="type=\"h\" (histogram-like)")
axis(1,at=seq(0,600,200),labels=c(0,"T/3","2T/3","T"))
plot(y~x,type="s",xlab="Time",ylab="Effort",xaxt="n",yaxt="n",main="type=\"s\" (stair steps)")
axis(1,at=seq(0,600,200),labels=c(0,"T/3","2T/3","T"))
plot(y~x,type="S",xlab="Time",ylab="Effort",xaxt="n",yaxt="n",main="type=\"S\" (other steps)")
axis(1,at=seq(0,600,200),labels=c(0,"T/3","2T/3","T"))
plot(y~x,type="n",xlab="Time",ylab="Effort",xaxt="n",yaxt="n",main="type=\"n\" (none!)")
axis(1,at=seq(0,600,200),labels=c(0,"T/3","2T/3","T"))

#PAGE 30
#Color index
source("http://research.stowers-institute.org /efg/R/Color/Chart/ColorChart.R")


#PAGE 33
#Final Learning Curve graphic.
my.gamma <- rgamma(10000000,7,2)
y <- hist(my.gamma,br=100,plot=FALSE)$counts
x <- seq(0,max(my.gamma),length=length(y))
plot(y~x,xlab="Time",ylab="Effort",type="l",lwd=4,col="red",xaxt="n",yaxt="n", main="The R Graphics Learning Curve")
axis(1,at=seq(0,max(x),length=4),labels=c(0,"T/3","2T/3","T"))
#Cyan grid.
abline(v=seq(0,max(x),length=15),lty=3,col="cyan")
abline(h=seq(0,max(y),length=15),lty=3,col="cyan")



#PAGE 36
#EXERCISE 1
#Solution
my.norm <- rnorm(10000000,0,1)	
#easiest to use standard normal!
#large number makes the curve smooth.
y <- hist(my.norm,br=100,plot=FALSE)$counts	
#dummy x axis.
x <- seq(-3,3,length=length(y))
x.ticks <- seq(-3,3,1)
#Can specify the color in many different ways:
#With color name string
plot(y~x,type="l",lwd=4,col="forestgreen",yaxt="n",xaxt="n",xlab="z",ylab="",main="My Normal Distribution")
#With palette code
plot(y~x,type="l",lwd=4,col=139,yaxt="n",xaxt="n",xlab="z",ylab="",main="My Normal Distribution")
#Or with RGB color content
plot(y~x,type="l",lwd=4,col="#228B22",yaxt="n",xaxt="n",xlab="z",ylab="",main="My Normal Distribution")
axis(1,at=x.ticks,labels=x.ticks)

#PAGE 37
#Better solution.
x <- seq(-3,3,by=0.01)
plot(dnorm(x)~x,type="l",lwd=4,col=139,yaxt="n",xaxt="n",xlab="z",ylab="",main="My Normal Distribution")
axis(1,at=x.ticks,labels=x.ticks)

#Even better solution,
curve(dnorm(x),type="l",lwd=4,col=139,yaxt="n",xaxt="n",xlab="z",ylab="",main="My Normal Distribution")
axis(1,at=x.ticks,labels=x.ticks)


#PAGE 39
#Facebook Data
group.1 <- read.csv("http://www.stat.ucla.edu/~rosario/scc/facebook-2007.csv",header=TRUE)
group.2 <- read.csv("http://www.stat.ucla.edu/~rosario/scc/facebook-2009.csv",header=TRUE)


#PAGE 41
#Two plots, separate windows, width=4, height=4
dev.new(height=4,width=4)
plot(group.1$Wall.Posts~group.1$Friends,pch='.',main="Facebook 2007",xlab="Friends",ylab="Wall Posts")
dev.new(height=4,width=4)
plot(group.2$Wall.Posts~group.2$Friends,pch='.',main="Facebook 2009",xlab="Friends",ylab="Wall Posts")


#PAGE 42
#Two plots, same window
par(mfrow=c(1,2))
plot(group.1$Wall.Posts~group.1$Friends,pch='.',main="Facebook 2007",xlab="Friends",ylab="Wall Posts")
plot(group.2$Wall.Posts~group.2$Friends,pch='.',main="Facebook 2009",xlab="Friends",ylab="Wall Posts")


#PAGE 48
#Same window, same plot
plot(group.1$Wall.Posts~group.1$Friends,pch='.',main="Facebook 2007 vs. 2009",xlab="Friends",ylab="Wall Posts",xlim=c(0,max(group.2$Friends)+400),ylim=c(0,max(group.2$Wall.Posts)+500))
points(group.2$Wall.Posts~group.2$Friends,pch='.',col="red")
#some stuff is cutoff!
legend(1300,4000,c(2007,2009),col=c("black","red"),pch=c('.','.'),inset=1,title="Legend",pt.cex=5)


#PAGE 52
#EXERCISE 2
#Requirements:
data <- read.csv("http://www.stat.ucla.edu/~rosario/scc/textbooks.csv",header=TRUE)
attach(data)
#Solution
plot(Amazon.Sale.Price~Amazon.List.Price,pch='*',main="Comparison of UCLA Textbook Prices: Amazon vs. BN",xlab="List Price",ylab="Sales Price")
points(Barnes.Noble.Price~Amazon.List.Price,pch='o')
abline(a=0,b=1,lty=2,col="grey")
good.deals <- which(abs((Amazon.List.Price-Amazon.Sale.Price)/Amazon.List.Price) >= 0.25)
points(Amazon.Sale.Price[good.deals]~Amazon.List.Price[good.deals],pch='o',col="red")
detach(data)


#PAGES 64-72
#Mathematical typesetting.
f <- function(x) { return(cos(x)^3) }
my.title <- expression(paste("Computing the Integral ",integral(plain(cos)^3*symbol(theta) *d*symbol(theta), -symbol(pi)/2, symbol(pi)/2)) )
x.label <- expression(symbol(theta))
y.label <- expression(plain(cos)^3*symbol(theta))
curve(f,from=-pi,to=pi,n=10000,lwd=4,col="green", xaxt="n",yaxt="n",main=my.title ,xlab=x.label , ylab=y.label)
x.tick.locations <- seq(-pi,pi,pi/2)
x.tick.labels <- c(expression(-pi),expression(-frac(symbol(pi),2)),0,expression(frac(symbol(pi),2)),expression(symbol(pi)))
#y axis is even easier.
y.tick.locations <- c(-1,0,1)
y.tick.labels <- y.tick.locations
axis(1,at=x.tick.locations ,labels=x.tick.labels , cex.axis=0.5)
axis(2,at=y.tick.locations ,labels=y.tick.labels , cex.axis=0.5)
segments(-pi/2,-1,-pi/2,0,lty=2,col="grey")
segments(pi/2,-1,pi/2,0,lty=2,col="grey")


#PAGES 73-76
#Integration movie.
#The background of the movie:
f <- function(x) { return(cos(x)^3) }
my.plot <- function(i) {
	curve(f,from=-pi,to=pi,n=10000,lwd=4,col="green",xaxt="n",yaxt="n",main=my.title,xlab=x.label,ylab=y.label)
	axis(1,at=x.tick.locations,labels=x.tick.labels, cex.axis=0.5)
	axis(2,at=y.tick.locations,labels=y.tick.labels, cex.axis=0.5)
	segments(-pi/2,-1,-pi/2,0,lty=2,col="grey")
	segments(pi/2,-1,pi/2,0,lty=2,col="grey")
	e <- (pi/4)*(1/(2**i))
	rect(-pi/2+e*seq(0,(2**(i+2))-1),f(-pi),-pi/2+e*seq(1,(2**(i+2))),f(-pi/2+e*seq(1,(2**(i+2)))),col="black")
}

#Produce graphics frames for movie.
setwd(tempdir())
for (i in 1:5) {
  filename <- paste("plot",i,".jpg",sep="")
  jpeg(file=filename)
  my.plot(i)
  dev.off()
}

#Make the movie!
make.mov <- function(){
     unlink("plot.mpg")
     system("convert -delay 10 plot*.jpg plot.mpg")
}
make.mov()


#PAGE 75
#Example PDF
pdf(file="mypdf.pdf",height=7,width=7,onefile=TRUE)
#execute your plotting commands here...
plot(1:10,1:10)
#turn the plotting "device" off.
dev.off() 
#like closing a file in a programming language.

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# FIN
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