Hi,
Just to add:
N <- 1000
M <- 5
P <- 5000
set.seed(15)
A <- matrix(runif(N,1,1000),nrow=N,ncol=M)
set.seed(425)
B <- matrix(runif(M,1,1000),nrow=P,ncol=M)
Marius.3.0<-function(A,B){do.call(cbind,lapply(split(B,row(B)),function(x)
colSums(x>=t(A))==ncol(A)))}
Marius.2.0 <- function(A, B){
nA <- nrow(A)
nB <- nrow(B)
C <- do.call(rbind, rep(list(B), nA)) >= matrix(rep(A, each=nB),
ncol=ncol(B))
matrix(rowSums(C) == ncol(A), nA, nB, byrow=TRUE)
}
system.time(z3.0<-Marius.3.0(A,B))
# user system elapsed
# 0.524 0.020 0.548
system.time(z2.0<-Marius.2.0(A,B))
# user system elapsed
# 0.968 0.216 1.189
system.time(z1<-perhaps(A,B))
# user system elapsed
# 1.264 0.204 1.473
attr(z3.0,"dim")<-dim(z2.0)
identical(z3.0,z2.0)
#[1] TRUE
identical(z1,z3.0)
#[1] TRUE
A.K.
----- Original Message -----
From: Marius Hofert <marius.hof...@math.ethz.ch>
To: R-help <r-help@r-project.org>
Cc:
Sent: Saturday, December 8, 2012 6:28 AM
Subject: [R] How to efficiently compare each row in a matrix with each row in
another matrix?
Dear expeRts,
I have two matrices A and B. They have the same number of columns but possibly
different number of rows. I would like to compare each row of A with each row
of B and check whether all entries in a row of A are less than or equal to all
entries in a row of B. Here is a minimal working example:
A <- rbind(matrix(1:4, ncol=2, byrow=TRUE), c(6, 2)) # (3, 2) matrix
B <- matrix(1:10, ncol=2) # (5, 2) matrix
( ind <- apply(B, 1, function(b) apply(A, 1, function(a) all(a <= b))) ) # (3,
5) = (nrow(A), nrow(B)) matrix
The question is: How can this be implemented more efficiently in R, that is, in
a faster way?
Thanks & cheers,
Marius
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______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
