[R] Sourcing data files into different array fields

[Gabor Grothendieck]

Use the local= argument of source.

Here we createa a list, L, whose ith component is an environment,
viz. the environment of the instance of f that did the sourcing,
containing the sourced objects.  First we create some test
files: /a1 and /a2 and then we create L.  The components
of L can be referred to as L[[1]], L[[2]] or using filenames
L[["a1"]], L[["a2"]] and the components can be extracted
via L[["a1"]]$a, etc.

# create test files
files <- paste("/a", 1:2, sep = "")
for(i in seq(files)) cat("a <-", i, "\n", file = files[i])

# read them back
f <- function(.x) { source(.x, local = TRUE); environment() }
L <- sapply(files, f, simplify = FALSE)
ls(L[[1]]) # "a"
L[[1]]$a # 1
L[["/a2"]][["a"]] # 2

On 4/1/06, Werner Wernersen <pensterfuzzer at yahoo.de> wrote:
> Hi,
>
> I make a number of experiments with a software which
> spits out one .R file of data objects to be sourced
> for each experiment. Now, the files repeat the data
> object names but ultimately I also want to perform
> comparision statistics between several objects.
>
> Now my question is, is there a slick way to "wrap"
> those data objects while sourcing each experiment file
> so that for instance I get an array m[] for each
> experiment and can access the objects by using
> m[1].object1 and so on?
>
> I am thankful for any suggestion!
>  Werner
>
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