Arithmetic mean on a multidimensional array on R and MATLAB: drastic difference of performances

Question

I am working with multidimensional array both on R and MATLAB, these arrays have five dimensions (total of 14.5M of elements). I have to remove a dimension applying an arith

Answer 1

mean is particularly slow because of S3 method dispatch. This is faster:

set.seed(42)
a = array(data = runif(144*73*6*23*10), dim = c(144,73,10,6,23))

system.time({b = apply(a, c(1,2,4,5), mean.default)})
# user  system elapsed 
#16.80    0.03   16.94

If you don't need to handle NAs you can use the internal function:

system.time({b1 = apply(a, c(1,2,4,5),  function(x) .Internal(mean(x)))})
# user  system elapsed 
# 6.80    0.04    6.86

For comparison:

system.time({b2 = apply(a, c(1,2,4,5),  function(x) sum(x)/length(x))})
# user  system elapsed 
# 9.05    0.01    9.08 

system.time({b3 = apply(a, c(1,2,4,5),  sum)
             b3 = b3/dim(a)[[3]]})
# user  system elapsed 
# 7.44    0.03    7.47

(Note that all timings are only approximate. Proper benchmarking would require running this repreatedly, e.g., using one of the bechmarking packages. But I'm not patient enough for that right now.)

It might be possible to speed this up with an Rcpp implementation.