How can this code be improved?

Run the script on a small subset of the data and use Rprof to profile
the code.  This will give you an idea of where time is being spent and
where to focus for improvement.  I would suggest that you do not
convert the output of the 'table(t)' do a dataframe.  You can just
extract the 'names' to get the words.  You might be spending some of
the time in the accessing the information in the dataframe, which is
really not necessary for your code.

On Thu, Nov 12, 2009 at 2:12 AM, Richard R. Liu <richard.liu at pueo-owl.ch 

wrote:
I am running the following code on a MacBook Pro 17" Unibody early  
2009 with
8GB RAM, OS X 10.5.8, R 2.10.0 Patch from Nov. 2, 2009, in 64-bit  
mode.

freq.stopwords <- numeric(0)
freq.nonstopwords <- numeric(0)
token.tables <- list(0)
i.ss <- c(0)
cat("Beginning at ", date(), ".\n")
for (i.d in 1:length(tokens)) {
       tt <- list(0)
       for (i.s in 1:length(tokens[[i.d]])) {
               t <- tolower(tokens[[i.d]][[i.s]])
               t <- sub("^[[:punct:]]*", "", t)
               t <- sub("[[:punct:]]*$", "", t)
               t <- as.data.frame(table(t))
               i.m <- match(t$t, stopwords)
               i.m.is.na <- is.na(i.m)
               i.ss <- i.ss + 1
               freq.stopwords[i.ss] <- sum(t$Freq * !i.m.is.na)
               freq.nonstopwords[i.ss] <- sum(t$Freq * i.m.is.na)
               tt[[i.s]] <- data.frame(token = t$t, freq = t$Freq,
matches.stopword = i.m)
       }
       token.tables[[i.d]] <- tt
       if (i.d %% 5 == 0) cat(i.d, "reports completed at ", date(),  
".\n")
}
cat("Terminating at ", date(), ".\n")

The object in the innermost loop are:
* tokens:  a list of lists.  In the expression tokens[[i.d]] 
[[i.s]], the
first index runs over 1697 reports, the second over the sentences  
in the
report, each of which consists of a vector of tokens, i.e., the  
character
strings between the white spaces in the sentence.  One of the largest
reports takes up 58MB on the harddisk.  Thus, the number of  
sentences can be
quite large, and some of the sentences are quite long (measure in  
tokens as
well as in characters).
* stopwords:  is a vector of 571 words that occur very often in  
written
English.

The code operates on sentences, converting each token in the  
sentence to
lowercase, removing punctuation at the beginning and end of the  
token,
tabulating the frequency of the unique tokens, and generating an  
array that
indicates which tokens correspond to stopwords.  It also sums the
frequencies of the stopwords and that of the non-stopwords.  The  
result is a
list of list of dataframes.

I began running on Thursday Nov. 12, 2009 at 01:56:36.  As of  
7:52:00 510
reports had been processed.  The Activity Monitor indicates no memory
bottleneck.  R is using 4.31 GB of real memory, 7.23 GB of virtual  
memory,
and 1.67 GB of real memory are free.

I admit that I am an R newbie.  From my understanding of the "apply"
functions (e.g., lapply), I see no way to use them to simplify the  
loops.  I
would appreciate any suggestions about making the code more "R- 
like" and,
above all, much faster.

Regards,
Richard

-- 
Jim Holtman
Cincinnati, OH
+1 513 646 9390

What is the problem that you are trying to solve?