Dear All,
I spent an entire evening in debugging a small, fairly simple program in R
- without success. It was my Guru in Bayesian Analysis, Thomas Fridtjof,
who was able to diagonose the problem. He said that it took a long time
for him also to locate the problem.
This program illustrates in some ways the shortcomings of the error
messages that R responds with. In this case, it was quite misleading and
directs attention to a location far removed the actual problem statement.
Without any more introductory comments, let me directly discuss the
essential problem. I am enclosing the entire program after a brief
discussion.
The problem arises from the following statement (nr is an integer
constant) :
for ( i in 1:nr-1) {.......}
The unexpected problem (at least for me) is that R reads the above
statement as (i in (1:nr)-1) {.....}. This makes i be initially as zero
which leads to an error because the for loop in R starts from 1. The
problem is easily fixed by writing the for loop as ( i in 1:(nr-1))
{.......}. This would be an easy problem to fix if R directly indicates
what the problem is. Instead, it gives mystifying error messages which are
totally misleading. For example, to the program given below, I got the
following error message (these point to commands elsewhere in the program)
:
Error in if ((x >= 0) & (x < s2)) return(x/2) else if ((x >= s2) & (x < :
missing value where TRUE/FALSE needed
I would like clarifications on the following points :
1. I am just curious to know if the priority of operators in the for
statement ( the colon before the minus operator, for example) is a
deliberate design decision. I have tested Matlab and found that it
interprets my original statement correctly without an extra paranthesis.
2. Faced with a similiar problem in the future, what is a smart way of
debugging in R to locate a problem. With this problem, I checked and
double checked every single statement in the program, except the for
statement because I just did not expect any problem there. I have seen
that there is a debug package but I have not used it. Can such tools be
used to locate a problem with greater ease? Can somebody give a concrete
example (for the following program, for example) of a debugging routine.
*************************************************************************'
# Bayesian Data Analysis
## source("M:/programming/Rfolder/Assignments/fortest.txt")
# #Remove all objects from the workspace
rm(list=ls())
# #We will also try to note the time that the program takes
# #We will start the clock at starttime
starttime <- proc.time()[3];
my.function<-function(x) {
s2<-sqrt(2);
if ((x>=0) & (x<s2)) return(x/2)
else
if ((x>=s2) & (x<1+s2)) return(0.2)
else
if ((x>=1+s2) & (x<1.5+s2)) return(0.6)
else
if ((x>1.5+s2) | (x<0)) return(0)
}
alphayx<-function(y,x) {
fy<-my.function(y)
fx<-my.function(x)
fyx<-fy/fx
# to account for 0/0 division
if (is.na(fyx)) fyx<-0
#fyx<-ifelse(is.na(fyx),0,fyx);
alpha<-min(1,fyx)
return(alpha)
}
sigma<-0.5;
#nr is the number of iterations
nr<-20
x<-numeric(nr);
x[1]<-1;
t<-1:nr;
for (i in 1:nr-1) {
xi<-x[i];
yi<-rnorm(1,mean=xi,sd=sigma);
ui<-runif(1,0,1);
ualphai<-alphayx(yi,xi);
xn<-ifelse(ui<=ualphai,yi,xi);
x[i+1]<-xn;
}
plot(t,x,type="p")
endtime<-proc.time()[3];
elapsedTime<-endtime-starttime;
cat("Elapsed time is", elapsedTime, "seconds", "\n")
*****************************************************************************'
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