To run R in Unix using ssh from your PC:
In the computer-lab click on the Putty window and login in Unity
login.stat.ncsu.edu
Then click
on an ICON named XWin32 (A blue X icon)
Go to the directory of interest, using the command cd in Unix
% add R
% R
Computing on the R language and calling FORTRAN and UNIX
--------------------------------------------------------
Topics:
* computing on the R language and calling FORTRAN and UNIX
* 3 approaches to call Fortran in R
#
assign function
assign("zork", 1:5)
# equivalent to
temp<- get( "zork") # equivalent to
temp
zork<- 1:5
temp <- zork
# The advantage of assign and get is that they take a
# character string as the data set name
EXAMPLE OF COMPUTING IN R:
_________________________
# here is an example of creating a bunch of data sets
# and looping over them using their names
# first make them up
dnames<- paste( "data", 1:10,sep=".")
dnames # this a character vector with names that we want to use for the
#
10
datasets
#
# Note that something like
dnames[1] <- 1:5
# will NOT assign 1:5 to the data set data.1 ! What will happen?
#
# creating 10 variables.
set.seed(123) # we will all get the same random numbers
for(k in 1:10) {
N<- rpois(n=1, lambda=100) # a value simulated from a poisson distribution
cat( dnames[k], N, fill=T)
# things to watch
temp<-sort( runif( N)) # simulate N values from a Uniform and order the values
assign( dnames[k], temp) # the assignment
}
data.1
#data.1 is a variable with sorted uniform values.
PLOT THE DATASETS:
# Now we want to loop through these to make some plots
plot.data<- function(){
par(mfrow=c(5,2))
for ( k in 1:10) {
temp<- get( dnames[k]) #get the dataset
N<- length( temp) # find its length
plot( temp, 1:N, xlab="time", ylab=" events", type="l")
title( dnames[k])
}
}
plot.data()
#
Lets remove all these datasets
remove( dnames)
-------------------------------------1. Using Fortran within R
----------------------## How to call UNIX form within R:
---------------------------------system( "ls") # will list the UNIX files from your current directory
system( "ls")
system("who", TRUE)
# Example in Unix to get netscape in R (you can SAS too).
system('"C:/Program Files/Internet Explorer/iexplore.exe"
"http://www.google.com"',wait=FALSE)
Single quotes on outside allow file locations to contain spaces.
# A very useful trick is to use the system command, R IO to run a
# FORTRAN program. This is not the elegant way to call FORTRAN
# from R but is very easy and quick.
###DOWNLOAD FROM THE WEB THE FILES: lab8.f, lab8.in, msort.f
# msort.f has the subroutines that do the looping over columns and
# the sorting
#
#
#
#
%
this is a stand alone program to read in a matrix and sort it
compile it
call the program lab8.x
IN UNIX:
f77 lab8.f msort.f -o lab8.x
% cat lab8.in
# some sample input
# run it
% lab8.x < lab8.in
# redirect the output to a file
% lab8.x < lab8.in > look
cat look
#
# Now get back in to S
#
# In SPLUS now try
> system( "lab8.x < lab8.in")
2. Another way to run fortran in R:
-------------------------------# so here is a function to sort columns of a matrix in R
# by running this program
msort<- function(x){
m<- nrow(x)
n<- ncol( x)
write( c(m,n), "temp.in") # write out the number of rows and columns
#
to a UNIX file
write( x, "temp.in", append=T) # append the values of x
# run the program in the UNIX shell
system( "lab8.x < temp.in > temp.out")
# after it has run read in the results
scan( "temp.out")-> hold
matrix( hold, ncol=n, nrow=m) # return values as a matrix
}
zork <- matrix( 12:1, ncol=3)
msort(zork)
3.The best approach
--------------#
#
#
#
#
this is not the best solution because of all the extra reading
and writing of the matrix to files.
A more efficient way ( but more difficult way) is to
load just the subroutines ( in the file msort.o) and then call
these directly from R
# recall that the calling sequence for msort is
#
#
subroutine msort( m,n,x)
#
real*8 x(m,1)
#
integer m,n
#
... etc.
msort2<- function( mat)
{
m<- as.integer( nrow(mat))
n<- as.integer( ncol(mat))
#
make sure these are integers so that the FORTRAN is not confused
#
out<- .Fortran("msort",m=m,n=n, x=as.double(mat))
# .Fortran returns a list, but we only want the x component
# reformed as a matrix
matrix( out$x,ncol=n)
}
# now first dynamically load msort.o
# in Unix (we compile msort.f)
% f77 msort.f -c
#
# Now in R use the function (after you open access to the Fortran subroutine)
dyn.load("msort.o")
zork <- matrix( 12:1, ncol=3)
msort2(zork)
# Note that for either case msort or msort2 R is using a
# FORTRAN sub to do the heavy lifting but this is transparent
# at the command line level