Hi,
You could try:
res<-colMeans(aperm(moo,c(2,1,3)))
resOld<-apply(moo,c(1,3),mean)
identical(res,resOld)
#[1] TRUE
#Speed:
set.seed(285)
moo1<- array(runif(1400*9*15),dim=c(1400,9,15))
system.time({res1<- colMeans(aperm(moo1,c(2,1,3)))})
#user system elapsed
# 0.004 0.000 0.002
system.time({res2<- apply(moo1,c(1,3),mean)})
# user system elapsed
# 0.180 0.000 0.178
identical(res1,res2)
#[1] TRUE
A.K.
- Original Message -
From: Jonathan Greenberg
To: r-help
Cc:
Sent: Thursday, August 29, 2013 6:36 PM
Subject: [R] Vectorized version of colMeans/rowMeans for higher dimension
arrays?
For matrices, colMeans/rowMeans are quick, vectorized functions. But
say I have a higher dimensional array:
moo <- array(runif(400*9*3),dim=c(400,9,3))
And I want to get the mean along the 2nd dimension. I can, of course,
use apply:
moo1 <- apply(moo,c(1,3),mean)
But this is not a vectorized operation (so it doesn't execute as
quickly). How would one vectorize this operation (if possible)? Is
there an array equivalent of colMeans/rowMeans?
--j
--
Jonathan A. Greenberg, PhD
Assistant Professor
Global Environmental Analysis and Remote Sensing (GEARS) Laboratory
Department of Geography and Geographic Information Science
University of Illinois at Urbana-Champaign
607 South Mathews Avenue, MC 150
Urbana, IL 61801
Phone: 217-300-1924
http://www.geog.illinois.edu/~jgrn/
AIM: jgrn307, MSN: jgrn...@hotmail.com, Gchat: jgrn307, Skype: jgrn3007
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and provide commented, minimal, self-contained, reproducible code.