Berton Gunter <gunter.berton <at> gene.com> writes:
:
: How about:
:
: X<-as.matrix(yourframe)
: apply(X,2, '==',X[,1])%*%rep(1,ncol(X)) == ncol(x)
:
: avoiding the rowwise apply overhead?
Following up on your idea we can use rowSums instead of matrix multiplication
to speed it up even more:
R> x <- data.frame(X1 = c(1.5, 1.5, 2.5, 4.5),
+ X2 = c(4.5, 1.5, 2.5, 5.5), X3 = c(2.5, 1.5, 2.5, 2.5))
R> set.seed(1)
R> x1 <- x2 <- x[sample(4,100000,rep=T),]
R> gc();system.time({x1$new <- (rowSums(x1==x1[,1])==ncol(x))+0})
used (Mb) gc trigger (Mb)
Ncells 634654 17.0 1590760 42.5
Vcells 1017322 7.8 3820120 29.2
[1] 0.48 0.00 0.48 NA NA
R> gc(); system.time({X <- as.matrix(x2); x2$new <- c(apply(X,2, '==',X[,1])%*%
rep(1,ncol(X)) == ncol(x))+0})
used (Mb) gc trigger (Mb)
Ncells 634668 17.0 1590760 42.5
Vcells 1517333 11.6 3820120 29.2
[1] 1.39 0.03 1.50 NA NA
R> all.equal(x1,x2)
[1] TRUE
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