On 05/01/2013 11:20 AM, David Kulp wrote:
I'm using refClass for a complex multi-directional tree structure with
possibly 100,000s of nodes. The refClass design is very impressive and I'd
love to use it, but I've found that the size of refClass instances are very
large and creation time is slow. For example, below is a RefClass and normal
S4 class. The RefClass requires about 4KB per instance vs 500B for the S4
class -- based on adding the Ncells and Vcells of used memory reported by
gc(). And instantiation is more than twice as slow for a RefClass. (R
2.14.2)
Anyone have thoughts on this and whether there's any hope for improving
resources on either front?
Hi David -- not necessarily helpful but creating a few large objects is always
better than creating many small in R, so perhaps re-conceptualize your data
structure? As a rough analogy, instead of constructing a graph as a large number
of 'Node' instances each pointing to one another, a graph could be represented
as a data.frame containing columns of 'from' and 'to' indexes (neighbour-edge
list, a few large objects) or as an adjacency matrix. One would also implement
creation and update of the few large objects in an R-friendly (vectorized) way.
Perhaps there are existing packages that already model the data you're
interested in? If your multi-directional tree can be represented as a graph,
then perhaps
http://bioconductor.org/packages/release/bioc/html/graph.html
including facilities in the Boost graph library (RBGL, on the Bioconductor web
site, too) or the igraph package can be put to use.
Martin
I wonder what others are doing. I've been thinking about lightweight
alternative implementations, but nothing particularly elegant has come to
mind, yet!
Thanks!
simple <- setRefClass('simple', fields = list(a = "character", b="numeric")
) gc() system.time(simple.list <- lapply(1:100000, function(i) {
simple$new(a='foo',b=i) })) gc()
setClass('simple2', representation(a="character",b="numeric"))
setMethod("initialize", "simple2", function(.Object, a, b) { .Object@a <- a
.Object@b <- b .Object })
gc() system.time(simple2.list <- lapply(1:100000, function(i) {
new('simple2',a='foo',b=i) })) gc()
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