You might try this to get the data into a dataframe that would be easier to
process.  You can subset and split the dataframe to look at different
combination.

> str01 <- "2007-10-12 11:50:05 state B. ,2007-10-12 11:50:05 state C.
,2007-10-12 13:23:24 state D. ,2007-10-12 13:23:43 state E. ,2007-10-14
15:43:19 state F. ,2007-10-14 15:43:20 state E. ,2007-10-14 15:43:25 state
G. ,2007-10-14 15:43:32 state H. ,2007-10-14 15:43:41 state I. ,2007-10-14
15:43:47 state F. ,2007-10-14 15:43:47 state G. ,2007-10-14 15:48:08 state
H. ,2007-10-16 10:10:20 state J. ,2007-10-19 11:12:54 state K ,2007-10-19
11:17:37 state D. ,2007-10-19 11:17:42 state E. ,2007-10-19 11:17:49 state
F. ,2007-10-19 11:17:51 state E. ,2007-10-19 11:17:58 state H. ,2007-10-19
11:18:05 state J. ,2007-10-19 11:21:45 state L."
> x.1 <- strsplit(str01, '[,]')[[1]]
> x.2 <- do.call(rbind, strsplit(x.1, ' '))
> # clean up the state to only letters
> x.2[,4] <- sub("([[:alnum:]]+).*", "\\1 <file://0.0.0.1/>", x.2[,4])
> states <- data.frame(time=as.POSIXct(paste(x.2[,1], x.2[,2])),
state=x.2[,4])
>
>
>
> states
                  time state
1  2007-10-12 11:50:05     B
2  2007-10-12 11:50:05     C
3  2007-10-12 13:23:24     D
4  2007-10-12 13:23:43     E
5  2007-10-14 15:43:19     F
6  2007-10-14 15:43:20     E
7  2007-10-14 15:43:25     G
8  2007-10-14 15:43:32     H
9  2007-10-14 15:43:41     I
10 2007-10-14 15:43:47     F
11 2007-10-14 15:43:47     G
12 2007-10-14 15:48:08     H
13 2007-10-16 10:10:20     J
14 2007-10-19 11:12:54     K
15 2007-10-19 11:17:37     D
16 2007-10-19 11:17:42     E
17 2007-10-19 11:17:49     F
18 2007-10-19 11:17:51     E
19 2007-10-19 11:17:58     H
20 2007-10-19 11:18:05     J
21 2007-10-19 11:21:45     L


On Tue, Jan 12, 2010 at 3:22 PM, Andreas Wittmann
<andreas_wittmann@gmx.de>wrote:

> Dear R-users,
>
> actually i try to parse some state protocols for my work. i an easy
> stetting the code below works fine, if states are reached only once. in
> harder settings it could be possible that one state gets visited more times.
> in this case for me its interesting to see how much waiting time lies
> between to states on the whole.
>
> by the way i didn't use R as a parsing tool so far, so any advice for doing
> this more effectivly are quite welcome.
>
> str01 <- "2007-10-12 11:50:05 state B. ,2007-10-12 11:50:05 state C.
> ,2007-10-12 13:23:24 state D. ,2007-10-12 13:23:43 state E. ,2007-10-14
> 15:43:19 state F. ,2007-10-14 15:43:20 state E. ,2007-10-14 15:43:25 state
> G. ,2007-10-14 15:43:32 state H. ,2007-10-14 15:43:41 state I. ,2007-10-14
> 15:43:47 state F. ,2007-10-14 15:43:47 state G. ,2007-10-14 15:48:08 state
> H. ,2007-10-16 10:10:20 state J. ,2007-10-19 11:12:54 state K ,2007-10-19
> 11:17:37 state D. ,2007-10-19 11:17:42 state E. ,2007-10-19 11:17:49 state
> F. ,2007-10-19 11:17:51 state E. ,2007-10-19 11:17:58 state H. ,2007-10-19
> 11:18:05 state J. ,2007-10-19 11:21:45 state L."
>
> str02 <- unlist(strsplit(str01, "\\,"))
>
> x1 <- grep("state B", str02)
> x2 <- grep("state C", str02)
> x3 <- grep("state D", str02)
> x4 <- grep("state E", str02)
> x5 <- grep("state F", str02)
> x6 <- grep("state G", str02)
> x7 <- grep("state H", str02)
> x8 <- grep("state I", str02)
> x9 <- grep("state J", str02)
> x10 <- grep("state K", str02)
> x11 <- grep("state L", str02)
>
> t1 <- substr(str02[x1], 1, 19)
> t1 <- as.POSIXct(strptime(t1, "%Y-%m-%d %H:%M:%S"))
> t2 <- substr(str02[x2], 1, 19)
> t2 <- as.POSIXct(strptime(t2, "%Y-%m-%d %H:%M:%S"))
> t3 <- substr(str02[x3], 1, 19)
> t3 <- as.POSIXct(strptime(t3, "%Y-%m-%d %H:%M:%S"))
> t4 <- substr(str02[x4], 1, 19)
> t4 <- as.POSIXct(strptime(t4, "%Y-%m-%d %H:%M:%S"))
> t5 <- substr(str02[x5], 1, 19)
> t5 <- as.POSIXct(strptime(t5, "%Y-%m-%d %H:%M:%S"))
> t6 <- substr(str02[x6], 1, 19)
> t6 <- as.POSIXct(strptime(t6, "%Y-%m-%d %H:%M:%S"))
> t7 <- substr(str02[x7], 1, 19)
> t7 <- as.POSIXct(strptime(t7, "%Y-%m-%d %H:%M:%S"))
> t8 <- substr(str02[x8], 1, 19)
> t8 <- as.POSIXct(strptime(t8, "%Y-%m-%d %H:%M:%S"))
> t9 <- substr(str02[x9], 1, 19)
> t9 <- as.POSIXct(strptime(t9, "%Y-%m-%d %H:%M:%S"))
> t10 <- substr(str02[x10], 1, 19)
> t10 <- as.POSIXct(strptime(t10, "%Y-%m-%d %H:%M:%S"))
> t11 <- substr(str02[x11], 1, 19)
> t11 <- as.POSIXct(strptime(t11, "%Y-%m-%d %H:%M:%S"))
>
> as.numeric(difftime(t11, t1, units="days"))
>
> ## waiting times between state E and F
> sum(as.numeric(difftime(t5, t4, units="days")))
>
>
> best regards
>
> Andreas
>
> ______________________________________________
> R-help@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<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?

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