[R] Speeding up small functions
Christos Hatzis
christos at nuverabio.com
Sun Nov 19 23:11:20 CET 2006
Wee-Jin,
The other option that you have is to set up your function as an expression
and then evaluate the expression for each new value of x. This might be
faster in some cases.
sigmoid.fun <- function(x) 1/(1+exp(-x))
sigmoid.expr <- expression( 1/(1+exp(-x)) )
x <- runif(10^6)
# non-vectorized function
system.time(
for(i in seq(along=x)) sigmoid.fun(x[i])
)
[1] 6.76 0.01 7.13 NA NA
# vectorized function
system.time(
sigmoid.fun(x)
)
[1] 0.56 0.00 0.59 NA NA
# vectorized expression
system.time(
eval(sigmoid.expr)
)
[1] 0.37 0.01 0.39 NA NA
-Christos
Christos Hatzis, Ph.D.
Nuvera Biosciences, Inc.
400 West Cummings Park
Suite 5350
Woburn, MA 01801
Tel: 781-938-3830
www.nuverabio.com
-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Wee-Jin Goh
Sent: Sunday, November 19, 2006 4:26 PM
To: r-help at stat.math.ethz.ch
Subject: [R] Speeding up small functions
Greetings list,
In my code, I have a few small functions that are called very very
frequently. An example of one such function is the following :
sigmoid<-function(x) 1/(1+exp(-x))
Now, is there anyway to make this go faster? For example, in C++ we could
make it inline. Is there a corresponding feature in R?
Cheers,
Wee-Jin
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