I thought the "apply" functions are faster than for loops, but my most
recent test shows that apply actually takes a significantly longer than a
for loop. Am I missing something?
It doesn't matter much if I do column wise calculations rather than row wise
## Example of how apply is SLOWER than for loop:
#rm(list=ls())
## DEFINE VARIABLES
mu=0.05 ; sigma=0.20 ; dt=.25 ; T=50 ; sims=1e5
timesteps = T/dt
## MAKE PHI AND DS
phi = matrix(rnorm(timesteps*sims), nrow=sims, ncol=timesteps)
ds = mu*dt + sigma * sqrt(dt) * phi
## USE APPLY TO CALCULATE ROWWISE CUMULATIVE PRODUCT
system.time(y1 <- apply(1+ds, 1, cumprod))
## UNTRANSFORM Y1, BECAUSE ROW APPLY FLIPS THE MATRIX
y1=t(y1)
## USE FOR LOOP TO CALCULATE ROWWISE CUMULATIVE PRODUCT
y2=matrix(NA,nrow(ds),ncol(ds))
system.time(
for (i in 1:nrow(ds)){
y2[i,]<-cumprod(1+ds[i,])
}
)
## COMPARE RESULTS TO MAKE SURE THEY DID THE SAME THING
str(y1)
str(y2)
all(y1==y2)
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I should add that I'm using R 2.10.1 on a Windows 7 machine, thanks! On Fri, Jul 9, 2010 at 3:11 PM, Gene Leynes <gleynes+r@gmail.com<gleynes%2Br@gmail.com>> wrote:> I thought the "apply" functions are faster than for loops, but my most > recent test shows that apply actually takes a significantly longer than a > for loop. Am I missing something? > > It doesn't matter much if I do column wise calculations rather than row > wise > > ## Example of how apply is SLOWER than for loop: > > #rm(list=ls()) > > ## DEFINE VARIABLES > mu=0.05 ; sigma=0.20 ; dt=.25 ; T=50 ; sims=1e5 > timesteps = T/dt > > ## MAKE PHI AND DS > phi = matrix(rnorm(timesteps*sims), nrow=sims, ncol=timesteps) > ds = mu*dt + sigma * sqrt(dt) * phi > > ## USE APPLY TO CALCULATE ROWWISE CUMULATIVE PRODUCT > system.time(y1 <- apply(1+ds, 1, cumprod)) > ## UNTRANSFORM Y1, BECAUSE ROW APPLY FLIPS THE MATRIX > y1=t(y1) > > ## USE FOR LOOP TO CALCULATE ROWWISE CUMULATIVE PRODUCT > y2=matrix(NA,nrow(ds),ncol(ds)) > system.time( > for (i in 1:nrow(ds)){ > y2[i,]<-cumprod(1+ds[i,]) > } > ) > > ## COMPARE RESULTS TO MAKE SURE THEY DID THE SAME THING > str(y1) > str(y2) > all(y1==y2) > > > > > > > >[[alternative HTML version deleted]]
On 09/07/2010 4:11 PM, Gene Leynes wrote:> I thought the "apply" functions are faster than for loops, but my most > recent test shows that apply actually takes a significantly longer than a > for loop. Am I missing something? >Probably not. apply() needs to figure out the shape of the results it gets from each row in order to put them into the final result matrix. You know that in advance, and set up the result to hold them, so your calculation would be more efficient. The *apply functions are designed to be convenient and clear to read, not necessarily fast. Duncan Murdoch> It doesn't matter much if I do column wise calculations rather than row wise > > ## Example of how apply is SLOWER than for loop: > > #rm(list=ls()) > > ## DEFINE VARIABLES > mu=0.05 ; sigma=0.20 ; dt=.25 ; T=50 ; sims=1e5 > timesteps = T/dt > > ## MAKE PHI AND DS > phi = matrix(rnorm(timesteps*sims), nrow=sims, ncol=timesteps) > ds = mu*dt + sigma * sqrt(dt) * phi > > ## USE APPLY TO CALCULATE ROWWISE CUMULATIVE PRODUCT > system.time(y1 <- apply(1+ds, 1, cumprod)) > ## UNTRANSFORM Y1, BECAUSE ROW APPLY FLIPS THE MATRIX > y1=t(y1) > > ## USE FOR LOOP TO CALCULATE ROWWISE CUMULATIVE PRODUCT > y2=matrix(NA,nrow(ds),ncol(ds)) > system.time( > for (i in 1:nrow(ds)){ > y2[i,]<-cumprod(1+ds[i,]) > } > ) > > ## COMPARE RESULTS TO MAKE SURE THEY DID THE SAME THING > str(y1) > str(y2) > all(y1==y2) > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at 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 > and provide commented, minimal, self-contained, reproducible code. >
On Fri, Jul 9, 2010 at 9:11 PM, Gene Leynes <gleynes+r at gmail.com> wrote:> I thought the "apply" functions are faster than for loops, but my most > recent test shows that apply actually takes a significantly longer than a > for loop. ?Am I missing something? >Check Rnews for an article discussing "proper" usage of apply and for. Liviu