# Exiting R
    q()

# commands for line editing in the R interpreter window:
#  ^p get back the previous command line for editing and executing
#  ^b step back one character in the command line
#  ^f step forward ...
#  ^a move to the beginning of the line
#  ^e move to the end of the line
#  ^d or Delete delete the character under the cursor 
#  ^h or Backspace to delete the previous character 
#  ^k kill the rest of the line starting from the cursor
#  otherwise: you are in insert mode
    
# Note: "^p" means you hold down the modifier key <Ctrl> and hit "p",
#       just like the modifier key <Shift> used for capitalization.

# Assignments:
    x <- sqrt(2 * 3)    # root of product of 2 and 3
    y <- c(1,3,10,1,1,1111,0,1,1,1,1,1,1)  
      # combine the values 1,3,10 into a vector
    
# Side effects:
    x                   # print or return x
    
# Syntax: largely scientific/math notation; 10 
#         considerable set of functions;
#         comments run from a "#" to the end of the line.

# Help: side effect of help(function) or help("function")
    help(sqrt)
    help(c)
    help("c")   # same as help(c)
    help("*")   # works in both

# Listing R objects, including data and functions:
    ls()        # your current data
    ls(pos=1)
    ls(pos=2)
    ls(pos=3)
    ls(pos=4)   # probably this one will list 1500 functions
    
# manual entry:
    x <- c(-1,2,5)
    
# equispaced sequences of numbers:
    x <- 3:10
    x <- seq(3, 10)
    x <- seq(3, 10, by=1/3)
    x <- seq(3, 10, len=8)
    x <- rep(3, 10)
    x <- rep(1:3, 5)
    x <- rep(c(1,2,3,4), c(2,3,2,3))
    x <- rep(1:3, rep(2,3))
    
# logical values T(=TRUE) and F(=FALSE):
    x <- c(T,T,F,T,T,T,F)
    x <- rep(T,5)
    x <- ((1:10) > 5)

# matrices
    x <- matrix(c(1,2,3,4,5,6),ncol=2,byrow=T)
    dimnames(x)<-list(c("Roe 1","Roe 2","Roe 3"),c("Var1","Var2"))

# data frames
    x<-data.frame(x)
    attach(x)
    Var1
    Var2
    detach(x)

# lists: ordered collections of objects
    x <- list(name="Cox", wife="Mary", husband="Fred", no.child=3,
           child.ages=c(4,8,9))
    x <- list(name=c("Cox","Wang"), wife=c("Mary","Pearl"), 
           husband=c("Fred","Val"), no.child=c(3,2),
           child.ages=c(c(4,8,9),c(1,5)))
    x$name
    x$no.child
    
# reading/writing data from/to files
# for data of the form
#  Name  Price Floor Area Rooms Cent.Heat
#  Coral 52.00   111  830     5        no
#  Teal  54.75   128  710     5        no
#  Ocean 57.50   101 1000     7       yes
#  ...
    x <- read.table("C:\\temp\\houses.asc",
      header=T, row.names=1)
    x <- read.table("C:\\temp\\houses.asc")
    
# writing data
    write.table(x,file="C:\\temp\\houses2.asc",
      row.names=T,col.names=T,sep=" ",quote=F,
      append=T)

    x<-runif(100000)
    cat(x,sep="\n",file="C:\\temp\\sp.dat")

# read vector from file: (first n values)
    x <- scan("C:\\temp\\sp.dat", n=1000)
    x <- scan("C:\\temp\\sp.dat", n=50000)
    options(memory=1E10, object.size=1E10)
    x <- scan("C:\\temp\\sp.dat")

# subsetting/selecting from a vector
    x <- 1:100 * 10 # same as: seq(10,1000,by=10), or: seq(10,1000,length=100)
    x[c(1,11,21)]
    x[seq(1,21,by=10)]
    x[1:10]
    x[50:150]
    x[x>500]
    
# simple statistics:
    length(x)
    sum(x)
    mean(x)
    var(x)
    sqrt(var(x))
    min(x)
    max(x)
    range(x)
    median(x)
    
    x <- runif(10, -100, 100)
    y <- round(x)
    abs(x)
    x*x;  x^2
    log(x^2);  2*log(abs(x))
    x > 0

# ranking, sorting:
    rank(x)
    order(x)
    sort(x);  x[order(x)]
    
    m <- cbind(1:5, x[1:5])
    m <- rbind(1:5, x[1:5])
    m <- matrix(1:36, ncol=4)
    m <- matrix(1:12, ncol=3, byrow=T)

# subselecting rows and columns:
    m
    m[1:2,]       # first 2 rows
    m[,1:2]       # first 2 columns
    m[1:2,c(1,3)] # first 2 rows, 1st,3rd columns
    
# operating on rows of matrices:
    apply(m, 1, min)  # return a vector with minima of the rows
# operating on columns of matrices:
    apply(m, 2, mean)        # return a vector with the means of the columns
    sqrt(apply(m, 2, var))   # return a vector with the sdevs of the columns
    
# looping
    x <- runif(100)
    x <- sort(x)
    y <- NULL
    for (i in 1:length(x))
      y <- c(y, x[i]*i)

    y <- NULL
    for (i in 1:length(x)) {
      z <- x[i]*i
      if (z < 10)
        y <- c(y, z)
    }

    y <- 0
    while (y < 10)
      y <- y+1

# graphics
   x <- runif(100)
   x<-sort(x)
   y <- x^2+rnorm(100)*0.1
   plot(x,y)
   plot(x,y,pch=16)
   plot(x,y,xlim=c(0,0.5))
   plot(x,y,xlab="Cost",ylab="Number",main="Houses data")
   par(mfrow=c(2,2))
   for (i in 1:4) {
     plot(x[((i-1)*25+1):(i*25)],y[((i-1)*25+1):(i*25)],
       xlim=range(x),ylim=range(y),xlab="x",ylab="y")
     abline(lsfit(x[((i-1)*25+1):(i*25)],y[((i-1)*25+1):(i*25)])$coef)
   }
   par(mar=c(0.2,0.2,0.2,0.2))
   for (i in 1:4) {
     plot(x[((i-1)*25+1):(i*25)],y[((i-1)*25+1):(i*25)],
       xlim=range(x),ylim=range(y),xaxt="n",yaxt="n")
     abline(lsfit(x[((i-1)*25+1):(i*25)],y[((i-1)*25+1):(i*25)])$coef,lwd=2*i)
   }

# function computes standard deviation of a vector
   sd <- function(x) {
     return(sqrt(var(x)))
   }
   x<-matrix(runif(100),ncol=5)
   for (i in 1:5)
     x[,i]<-x[,i]*i
   apply(x,2,sd)

# loading functions from files
   source("C:\\temp\\mosaic.plot")