Hi,
Not sure this helps:
ml <- data.frame(matrix(sample(1:50,80, replace=TRUE),20,4))
mm <- apply(ml, 2, cumsum)
starts<- data.frame(matrix(0,600,4))
starts1<- data.frame(matrix(0,600,4))
for (i in 1:4){
starts1[,i][mm[,i]] <-1
}
starts2<-as.data.frame(do.call(cbind,lapply(1:4,function(i)
{starts[,i][mm[,i]]<-1;starts[,i]})))
colnames(starts2)<- colnames(starts1)
identical(starts1,starts2)
#[1] TRUE
#loop should be fast compared to lapply
ml <- data.frame(matrix(sample(1:1e4,1e3, replace=TRUE),100,4))
mm <- apply(ml, 2, cumsum)
starts<- data.frame(matrix(0,1e6,4))
starts1<- data.frame(matrix(0,1e6,4))
system.time({for (i in 1:4){
starts1[,i][mm[,i]] <-1
}})
#user system elapsed
# 0.63 0.30 0.92
system.time(starts2<-as.data.frame(do.call(cbind,lapply(1:4,function(i)
{starts[,i][mm[,i]]<-1;starts[,i]}))))
# user system elapsed
# 0.74 0.26 1.03
colnames(starts2)<- colnames(starts1)
identical(starts1,starts2)
#[1] TRUE
A.K.
----- Original Message -----
From: Brett Robinson <brett.robin...@7dials.com>
To: "r-help@r-project.org" <r-help@r-project.org>
Cc:
Sent: Saturday, February 2, 2013 11:38 AM
Subject: [R] vectorisation
Hi
I'm trying to set up a simulation problem without resorting to (m)any loops. I
want to set entries in a data frame of zeros ('starts' in the code below) to 1
at certain points and the points have been randomly generated and stored in a
separate data.frame ('sl'), which has the same number of columns.
An example of the procedure is as follows:
ml <- data.frame(matrix(sample(1:50,80, replace=TRUE),20,4))
mm <- apply(ml, 2, cumsum)
starts<- data.frame(matrix(0,600,4))
I can achieve the result I want with a loop:
for (i in 1:4){
lstarts[,i][mm[,i]] <-1
}
But as I want to use a large number of columns I would like to do away with the
loop
Can anyone suggest how this might be done?
Thanks in advance
Brett Robinson
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and provide commented, minimal, self-contained, reproducible code.
