Message-ID: <5E1B812FAC2C4A49B3D99593B5A52191448A36@PRDEXMBX-08.the-lab.llnl.gov>
Date: 2013-06-10T21:51:04Z
From: MacQueen, Don
Subject: Speed up or alternative to 'For' loop
In-Reply-To: <CAMDVrE3jbQochoPGOoc8zcDTPRO5AEhY1nZpHVBzz6JWNMPanA@mail.gmail.com>
How about
for (ir in unique(df$TreeID)) {
in.ir <- df$TreeID == ir
df$HeightGrowth[in.ir] <- cumsum(df$Height[in.ir])
}
Seemed fast enough to me.
In R, it is generally good to look for ways to operate on entire vectors
or arrays, rather than element by element within them. The cumsum()
function does that in this example.
-Don
--
Don MacQueen
Lawrence Livermore National Laboratory
7000 East Ave., L-627
Livermore, CA 94550
925-423-1062
On 6/10/13 10:28 AM, "Trevor Walker" <trevordaviswalker at gmail.com> wrote:
>I have a For loop that is quite slow and am wondering if there is a faster
>option:
>
>df <- data.frame(TreeID=rep(1:500,each=20), Age=rep(seq(1,20,1),500))
>df$Height <- exp(-0.1 + 0.2*df$Age)
>df$HeightGrowth <- NA #intialize with NA
>for (i in 2:nrow(df))
> {if(df$TreeID[i]==df$TreeID[i-1])
> {df$HeightGrowth[i] <- df$Height[i]-df$Height[i-1]
> }
> }
>
>Trevor Walker
>Email: trevordaviswalker at gmail.com
>
> [[alternative HTML version deleted]]
>
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