Faster process for creating a matrix based on matrix element comparison
dat
[,1] [,2] [,3]
[1,] 0 0 1
[2,] 0 1 0
[3,] 0 1 1
[4,] NA 1 1
1 - is.na(dat)
[,1] [,2] [,3]
[1,] 1 1 1
[2,] 1 1 1
[3,] 1 1 1
[4,] 0 1 1
D.
On Fri, Oct 28, 2011 at 11:40 AM, Evgenia <evgts at aueb.gr> wrote:
I have matrix data
data<-matrix(cbind(c(0,0,0),c(NA,0,1),c(1,1,1),c(0,1,1)),ncol=3)
and I want to create a new matrix by checking each element of the data and
put value 0 if i have NA and 1 otherwise.
For this reason i made the function below
pdata<-matrix(NA,ncol=ncol(data),nrow=nrow(data))
pdata<-sapply(1:nrow(data),function(i) sapply (1:ncol(data),function(j)
if (is.na(data[i,j])) {pdata[i,j]<-0} else {pdata[i,j]<-1}
))
pdata<-matrix(t(pdata),ncol=ncol(data),nrow=nrow(data))
with pdata
pdata
? ? [,1] [,2] [,3] [1,] ? ?1 ? ?1 ? ?1 [2,] ? ?1 ? ?1 ? ?1 [3,] ? ?1 ? ?1 ? ?1 [4,] ? ?0 ? ?1 ? ?1 But in my case I have a matrix with 50000 rows and 10 colums and the creation of pdata takes alot of time. Could anyone have any suggestion to make pdata faster? Thanks -- View this message in context: http://r.789695.n4.nabble.com/Faster-process-for-creating-a-matrix-based-on-matrix-element-comparison-tp3948841p3948841.html Sent from the R help mailing list archive at Nabble.com.
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