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Fastest R equivalent to MATLAB reshape ()?

I am converting a MATLAB script to R and regret it so far, as it is currently slower. I try to use "vectorized functions" as much as possible, but I'm relatively new to R and don't know what that means. From my research, for loops, it is only slower than the apply () method in R if you use many operators (including brackets). Otherwise, I don’t see what R could do to slow it down further. Here is the code that works, which I want to speed up.

somPEs   <- 9;
inputPEs <- 6;
initial_w <- matrix(1, nrow=somPEs, ncol=inputPEs) 
w <- apply(initial_w, 1, function(i) runif(i));
# Reshape w to a 3D matrix of dimension: c(sqrt(somPEs), sqrt(somPEs), inputPEs)
nw <- array(0, dim=c(sqrt(somPEs), sqrt(somPEs), inputPEs))
for (i in 1:inputPEs) {
  nw[,,i] <- matrix(w[i,], nrow=sqrt(somPEs), ncol=sqrt(somPEs), byrow=TRUE)
}
w <- nw;

In MATLAB, this code is executed by a built-in function called "reshape", as is done below:

w = reshape(w,[sqrt(somPEs) sqrt(somPEs) inputPEs]);

R-, , , apply() .

user  system elapsed 
0.003   0.000   0.002
+4
2

w 6x9 3x3x6 size, , :

neww <- t(w)
dim(neww) <- c(sqrt(somPEs), sqrt(somPEs), inputPEs)

, , , . aperm :

neww <- aperm(neww, c(2, 1, 3))

, . , 10 000 100 ( 10x10x10k):

josilber <- function(w) {
  neww <- t(w)
  dim(neww) <- c(sqrt(dim(w)[2]), sqrt(dim(w)[2]), dim(w)[1])
  aperm(neww, c(2, 1, 3))
}
OP <- function(w) {
  nw <- array(0, dim=c(sqrt(dim(w)[2]), sqrt(dim(w)[2]), dim(w)[1]))
  for (i in 1:(dim(w)[1])) {
    nw[,,i] <- matrix(w[i,], nrow=sqrt(dim(w)[2]), ncol=sqrt(dim(w)[2]), byrow=TRUE)
  }
  nw
}
bigw <- matrix(runif(1000000), nrow=10000, ncol=100)
all.equal(josilber(bigw), OP(bigw))
# [1] TRUE
microbenchmark(josilber(bigw), OP(bigw))
# Unit: milliseconds
#            expr       min       lq      mean     median        uq       max neval
#  josilber(bigw)  8.483245  9.08430  14.46876   9.431534  11.76744  135.7204   100
#        OP(bigw) 83.379053 97.07395 133.86606 117.223236 129.28317 1553.4381   100

t, dim aperm 10 , .

+5

,

nw1 <- aperm(`dim<-`(t(w), list(3, 3, 6)), c(2, 1, 3))

> nw1
, , 1

          [,1]      [,2]      [,3]
[1,] 0.8257185 0.5475478 0.4157915
[2,] 0.8436991 0.3310513 0.1546463
[3,] 0.1794918 0.1836032 0.2675192

, , 2

          [,1]      [,2]      [,3]
[1,] 0.6914582 0.1674163 0.2921129
[2,] 0.2558240 0.4269716 0.7335542
[3,] 0.6416367 0.8771934 0.6553210

, , 3

          [,1]       [,2]      [,3]
[1,] 0.9761232 0.05223183 0.6651574
[2,] 0.5740032 0.80621864 0.2295017
[3,] 0.1138926 0.76009870 0.6932736

, , 4

            [,1]      [,2]      [,3]
[1,] 0.437871558 0.5172516 0.1145181
[2,] 0.006923583 0.3235762 0.3751655
[3,] 0.823235642 0.4586850 0.6013853

, , 5

          [,1]      [,2]      [,3]
[1,] 0.7425735 0.1665975 0.8659373
[2,] 0.1418979 0.1878132 0.2357267
[3,] 0.6963537 0.5391961 0.1112467

, , 6

          [,1]       [,2]       [,3]
[1,] 0.7246276 0.02896792 0.04692648
[2,] 0.7563403 0.22027518 0.41138672
[3,] 0.8303413 0.31908307 0.25180560
+2

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