Re: [Rd] grep with fixed=TRUE and

From: Petr Savicky <>
Date: Thu, 17 May 2007 11:03:00 +0200

> strncasecmp is not standard C (not even C99), but R does have a substitute
> for it. Unfortunately strncasecmp is not usable with multibyte charsets:
> Linux systems have wcsncasecmp but that is not portable. In these days of
> widespread use of UTF-8 that is a blocking issue, I am afraid.

What could help are the functions mbrtowc and towctrans and simple long integer comparison. Are the functions mbrtowc and towctrans available under Windows? mbrtowc seems to be available as Rmbrtowc in src/gnuwin32/extra.c.

I did not find towctrans defined in R sources, but it is in gnuwin32/Rdll.hide and used in do_tolower. Does this mean that tolower is not usable with utf-8 under Windows?

> In the case of grep I think all you need is
> grep(tolower(pattern), tolower(x), fixed = TRUE)
> and similarly for regexpr.

Yes. this is correct, but it has disadvantages. It needs more space and, if value=TRUE, we would have to do something like

   x[grep(tolower(pattern), tolower(x), fixed = TRUE, value=FALSE)] This is hard to implement in src/library/base/R/grep.R, where the call to .Internal(grep(pattern,...)) is the last command and I think this should be preserved.

> >Ignore case option is not meaningfull in gsub.
> sub("abc", "123", c("ABCD", "abcd"),
> is different from '', and I see the meaning as clear.
> So what did you mean? (Unfortunately the tolower trick does not work for
> [g]sub.)

The meaning of in [g]sub is problematic due to the following.   sub("abc", "xyz", c("ABCD", "abcd"), produces
  [1] "xyzD" "xyzd"
but the user may in fact need the following   [1] "XYZD" "xyzd"

It is correct that "xyzD" "xyzd" is produced, but the user should be aware of the fact that several substitutions like   x <- sub("abc", "xyz", c("ABCD", "abcd")) #   sub("ABC", "XYZ", x) # may be more useful.

I have another question concerning the speed of grep. I expected that fgrep_one function is slower than calling a library routine for regular expressions. In particular, if the pattern has a lot of long partial matches in the target string, I expected that it may be much slower. A short example is
  y <- "aaaaaaaaab"

  x <- "aaaaaaaaaaaaaaaaaaab"

which requires 110 comparisons (10 comparisons for each of 11 possible beginnings of y in x). In general, the complexity in the worst case is O(m*n), where m,n are the lengths of y,x resp. I would expect that the library function for matching regular expressions needs time O(m+n) and so will be faster. However, the result obtained on a larger example is
  > x1 <- paste(c(rep("a", times = 1000), "b"), collapse = "")
  > x2 <- paste(c("b", rep("a", times = 1000)), collapse = "")
  > y <- paste(c(rep("a", times = 10000), x2), collapse = "")
  > z <- rep(y, times = 100)

  > system.time(i <- grep(x1, z, fixed = T))   [1] 1.970 0.000 1.985 0.000 0.000

  > system.time(i <- grep(x1, z, fixed = F)) # reg. expr. surprisingly slow (*)   [1] 40.374 0.003 40.381 0.000 0.000

  > system.time(i <- grep(x2, z, fixed = T))   [1] 0.113 0.000 0.113 0.000 0.000

  > system.time(i <- grep(x2, z, fixed = F)) # reg. expr. faster than fgrep_one   [1] 0.019 0.000 0.019 0.000 0.000

Do you have an explanation of these results, in particular (*)?

Petr. mailing list Received on Thu 17 May 2007 - 09:07:20 GMT

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