Hi Martin,
On 03/22/2016 10:20 AM, Martin Maechler wrote:
>>>>>Dénes Tóth<toth.de...@ttk.mta.hu>
>>>>> on Fri, 18 Mar 2016 22:56:23 +0100 writes:
> Hi Roy,
> R (usually) makes a copy if the dimensionality of an array is modified,
> even if you use this syntax:
> x <- array(1:24, c(2, 3, 4))
> dim(x) <- c(6, 4)
> See also ?tracemem, ?data.table::address, ?pryr::address and other tools
> to trace if an internal copy is done.
Well, without using strange (;-) packages, indeed standard R's
tracemem(), notably the help page is a good pointer.
According to the help page memory tracing is enabled in the
default R binaries for Windows and OS X.
For Linux (where I, as R developer, compile R myself anyway),
one needs to configure with --enable-memory-profiling .
Now, let's try:
> x <- array(rnorm(47), dim = c(1000,50, 40))
> tracemem(x)
[1] "<0x7f79a498a010>"
> dim(x) <- c(1000* 50, 40)
> x[5] <- pi
> tracemem(x)
[1] "<0x7f79a498a010>"
>
So,*BOTH* the re-dimensioning*AND* the sub-assignment did
*NOT* make a copy.
This is interesting. First I wanted to demonstrate to Roy that recent R
versions are smart enough not to make any copy during reshaping an
array. Then I put together an example (similar to yours) and realized
that after several reshapes, R starts to copy the array. So I had to
modify my suggestion... And now, I realized that this was an
RStudio-issue. At least on Linux, a standard R terminal behaves as you
described, however, RStudio (version 0.99.862, which is not the very
latest) tends to create copies (quite randomly, at least to me). If I
have time I will test this more thoroughly and file a report to RStudio
if it turns out to be a bug.
Denes
Indeed, R has become much smarter in these things in recent
years ... not thanks to me, but very much thanks to
Luke Tierney (from R-core), and also thanks to contributions from "outside",
notably Tomas Kalibera.
And hence:*NO* such strange workarounds are needed in this specific case:
> Workaround: use data.table::setattr or bit::setattr to modify the
> dimensions in place (i.e., without making a copy). Risk: if you modify
> an object by reference, all other objects which point to the same memory
> address will be modified silently, too.
Martin Maechler, ETH Zurich (and R-core)
> HTH,
> Denes
(generally, your contributions help indeed, Denes, thank you!)
> On 03/18/2016 10:28 PM, Roy Mendelssohn - NOAA Federal wrote:
>> Hi All:
>>
>> I am working with a very large array. if noLat is the number of
latitudes, noLon the number of longitudes and noTime the number of time periods, the
array is of the form:
>>
>> myData[noLat, no Lon, noTime].
>>
>> It is read in this way because that is how it is stored in a (series)
of netcdf files. For the analysis I need to do, I need instead the array:
>>
>> myData[noLat*noLon, noTime]. Normally this would be easy:
>>
>> myData<- array(myData,dim=c(noLat*noLon,noTime))
>>
>> My question is how does this command work in R - does it make a copy of
the existing array, with different indices for the dimensions, or does it just redo
the indices and leave the given array as is? The reason for this question is my
array is 30GB in memory, and I don’t have enough space to have a copy of the array in
memory. If the latter I will have to figure out a work around to bring in only part
of the data at a time and put it into the proper locations.
>>
>> Thanks,
>>
>> -Roy
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