On Thu, May 14, 2009 at 6:21 PM, Ping-Hsun Hsieh <hsi...@ohsu.edu> wrote:
> Hi All,
>
> I have a 1000x1000000 matrix.
> The calculation I would like to do is actually very simple: for each row,
> calculate the frequency of a given pattern. For example, a toy dataset is as
> follows.
>
> Col1 Col2 Col3 Col4
> 01 02 02 00 => Freq of “02” is 0.5
> 02 02 02 01 => Freq of “02” is 0.75
> 00 02 01 01 …
>
> My code is quite simple as the following to find the pattern “02”.
>
> OccurrenceRate_Fun<-function(dataMatrix)
> {
> tmp<-NULL
> tmpMatrix<-apply(dataMatrix,1,match,"02")
> for ( i in 1: ncol(tmpMatrix))
> {
> tmpRate<-table(tmpMatrix[,i])[[1]]/ nrow(tmpMatrix)
> tmp<-c(tmp,tmpHET)
> }
> rm(tmpMatrix)
> rm(tmpRate)
> return(tmp)
> gc()
> }
>
> The problem is the memory usage grows very fast and hard to be handled on
> machines with less RAM.
> Could anyone please give me some comments on how to reduce the space
> complexity in this calculation?
rowMeans(dataMatrix == "02") ?
Hadley
--
http://had.co.nz/
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