[R] How can this code be improved?

[jim holtman]

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
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
>



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

What is the problem that you are trying to solve?