How about starting your time from 1 instead of 0 to make indexing earier
(you can always substract one later). If so:
> x
time events
1 1 1
2 2 30
3 6 14
4 11 4
> y <- data.frame(time=seq(max(x$time)), events=rep(0, max(x$time)))
> y
time events
1 1 0
2 2 0
3 3 0
4 4 0
5 5 0
6 6 0
7 7 0
8 8 0
9 9 0
10 10 0
11 11 0
> y$events[x$time] <- x$events
> y
time events
1 1 1
2 2 30
3 3 0
4 4 0
5 5 0
6 6 14
7 7 0
8 8 0
9 9 0
10 10 0
11 11 4
>
On 5/30/06, Pete Cap <[EMAIL PROTECTED]> wrote:
>
> Hello List,
>
> I am working on creating periodograms from IP network traffic logs using
> the Fast Fourier Transform. The FFT requires all the data points to be
> evenly-spaced in the time domain (constant delta-T), so I have a step where
> I zero-pad the data.
>
> Lately I've been wondering if there is a faster way to do this. Here's
> what I've got:
>
> * data1 is a data frame consisting of a timestamp, in seconds, from the
> beginning of the network log, and the number of network events that fell on
> that timestamp.
> Example:
> time,events
> 0,1
> 1,30
> 5,14
> 10,4
>
> *data2 is the zero-padded data frame. It has length equal to the greatest
> value of "time" in data2:
> time,events
> 1,0
> 2,0
> 3,0
> 4,0
> 5,0
> 6,0
> 7,0
> 8,0
> 9,0
> 10,0
>
> So I run this for loop:
> for(i in 1:length(data1[,1])) {
> data2[data1[i,1],2]<-data1[i,2]
> }
>
> Which goes to each row in data1, reads the timestamp, and writes the
> "events" to the corresponding row in data2. The result is:
> time,events
> 0,1
> 1,30
> 2,0
> 3,0
> 4,0
> 5,14
> 6,0
> 7,0
> 9,0
> 9,0
> 10,4
>
> For a 24-hour log (86,400 seconds) this can take a while...Any advice on
> how to speed it up would be appreciated.
>
> Thanks,
> Pete Cap
>
>
> ---------------------------------
>
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>
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--
Jim Holtman
Cincinnati, OH
+1 513 646 9390 (Cell)
+1 513 247 0281 (Home)
What is the problem you are trying to solve?
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