Comparing speed when populating an environment and a preallocated list

listORenv.R

library(MSnbase)
n <- 10000
ll <- vector("list",length=n)
e <- new.env()
tl <- system.time(for (i in 1:n)
                  ll[[i]] <- new("Spectrum2"))
te <- system.time(for (i in 1:n)
                  assign(paste("X",i,sep=""),new("Spectrum2"),e))

## Results for n=10000
##> te
##   user  system elapsed
## 10.640   0.020  10.728
##> tl
##   user  system elapsed
##  9.900   0.020  10.139

## BUT -- A common problem is with subset-assign on list elements
## Thanks to Martin Morgan for this example

setClass("Lst", representation=representation(l="list"))
Lst <- function(l, ...) new("Lst", l=l, ...)
setClass("Env", representation=representation(e="environment"))
Env <- function(e, ...) new("Env", e=e, ...)

l <- replicate(5, matrix(0, 1e3, 1e3),simplify=FALSE)
names(l) <- letters[seq_len(length(l))]
lst <- Lst(l=l)
env <- Env(e=list2env(l))


##> system.time(lst@l[["a"]][1,1] <- 1)
##   user  system elapsed 
##  0.080   0.000   0.077 
##> system.time(env@e[["a"]][1,1] <- 1)
##   user  system elapsed 
##  0.000   0.000   0.005 

## Because lst@l is copying the entire object
## which also implies memory overhead