On 29.04.2011 22:14, kparamas wrote:
Hi,
I am calculation pairwise correlation coefficient for a matrix of 234 X
30000.
I am getting the following error,
Error in cbind(as.vector(row(cl)), as.vector(col(cl)), as.vector(cl)) :
allocMatrix: too many elements specified
The problem is that you try to create a matrix with 3 * nrow(cl) *
ncol(cl) elements here. The maximal number of elements in one single
vector or matrix is 2^31 - 1. You can have several of those, if you have
a sufficient amount of RAM, tough.
Uwe Ligges
In addition: There were 50 or more warnings (use warnings() to see the first
50)
The function used is,
corGraphPearson = function(cData, COR) #COR is threshold 0.5,0.7, etc
{
cl = unname(cor(cData, use="pairwise.complete.obs", method="pearson"))
result = cbind(as.vector(row(cl)),as.vector(col(cl)),as.vector(cl))
result = result[result[,1] != result[,2],]
corm = result
# remove low cor pairs
corm =corm[abs(corm[,3])>= COR, ]
# the network
net<- network(corm, directed = F)
}
I am running this in a cluster with 4 machines with 24 GB memory each.
How should I start R so that I make max use of the memory availbale?
Or how to overcome this issue?
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and provide commented, minimal, self-contained, reproducible code.